Integration of sampling based battery state of health estimation method in electric vehicles

International Nuclear Information System (INIS)

Ozkurt, Celil; Camci, Fatih; Atamuradov, Vepa; Odorry, Christopher

2016-01-01

Highlights: • Presentation of a prototype system with full charge discharge cycling capability. • Presentation of SoH estimation results for systems degraded in the lab. • Discussion of integration alternatives of the presented method in EVs. • Simulation model based on presented SoH estimation for a real EV battery system. • Optimization of number of battery cells to be selected for SoH test. - Abstract: Battery cost is one of the crucial parameters affecting high deployment of Electric Vehicles (EVs) negatively. Accurate State of Health (SoH) estimation plays an important role in reducing the total ownership cost, availability, and safety of the battery avoiding early disposal of the batteries and decreasing unexpected failures. A circuit design for SoH estimation in a battery system that bases on selected battery cells and its integration to EVs are presented in this paper. A prototype microcontroller has been developed and used for accelerated aging tests for a battery system. The data collected in the lab tests have been utilized to simulate a real EV battery system. Results of accelerated aging tests and simulation have been presented in the paper. The paper also discusses identification of the best number of battery cells to be selected for SoH estimation test. In addition, different application options of the presented approach for EV batteries have been discussed in the paper.

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

Directory of Open Access Journals (Sweden)

Salomon Joshua A

2003-12-01

Full Text Available Abstract Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99. Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions

State-Level Estimates of Obesity-Attributable Costs of Absenteeism

Science.gov (United States)

Andreyeva, Tatiana; Luedicke, Joerg; Wang, Y. Claire

2014-01-01

Objective To provide state-level estimates of obesity-attributable costs of absenteeism among working adults in the U.S. Methods Nationally-representative data from the National Health and Nutrition Examination Survey (NHANES) for 1998–2008 and from the Behavioral Risk Factor Surveillance System (BRFSS) for 2012 are examined. The outcome is obesity-attributable workdays missed in the previous year due to health, and their costs to states. Results Obesity, but not overweight, is associated with a significant increase in workdays absent, from 1.1 to 1.7 extra days missed annually compared to normal weight employees. Obesity-attributable absenteeism among American workers costs the nation an estimated $8.65 billion per year. Conclusion Obesity imposes a considerable financial burden on states, accounting for 6.5%–12.6% of total absenteeism costs in the workplace. State legislature and employers should seek effective ways to reduce these costs. PMID:25376405

Estimating GSP and labor productivity by state

OpenAIRE

Paul W. Bauer; Yoonsoo Lee

2006-01-01

In gauging the health of state economies, arguably the two most important series to track are employment and output. While employment by state is available about three weeks after the end of a month, data on output, as measured by Gross State Product (GSP), are only available annually and with a significant lag. This Policy Discussion Paper details how more current estimates of GSP can be generated using U.S. Gross Domestic Product and personal income along with individual states’ personal in...

Experience-based utility and own health state valuation for a health state classification system: why and how to do it.

Science.gov (United States)

Brazier, John; Rowen, Donna; Karimi, Milad; Peasgood, Tessa; Tsuchiya, Aki; Ratcliffe, Julie

2017-10-11

In the estimation of population value sets for health state classification systems such as the EuroQOL five dimensions questionnaire (EQ-5D), there is increasing interest in asking respondents to value their own health state, sometimes referred to as "experience-based utility values" or, more correctly, own rather than hypothetical health states. Own health state values differ to hypothetical health state values, and this may be attributable to many reasons. This paper critically examines whose values matter; why there is a difference between own and hypothetical values; how to measure own health state values; and why to use own health state values. Finally, the paper examines other ways that own health state values can be taken into account, such as including the use of informed general population preferences that may better take into account experience-based values.

Estimating active transportation behaviors to support health impact assessment in the United States

Directory of Open Access Journals (Sweden)

Theodore J Mansfield

2016-05-01

Full Text Available Health impact assessment (HIA has been promoted as a means to encourage transportation and city planners to incorporate health considerations into their decision-making. Ideally, HIAs would include quantitative estimates of the population health effects of alternative planning scenarios, such as scenarios with and without infrastructure to support walking and cycling. However, the lack of baseline estimates of time spent walking or biking for transportation (together known as active transportation, which are critically related to health, often prevents planners from developing such quantitative estimates. To address this gap, we use data from the 2009 US National Household Travel Survey to develop a statistical model that estimates baseline time spent walking and biking as a function of the type of transportation used to commute to work along with demographic and built environment variables. We validate the model using survey data from the Raleigh-Durham-Chapel Hill, NC, metropolitan area. We illustrate how the validated model could be used to support transportation-related HIAs by estimating the potential health benefits of built environment modifications that support walking and cycling. Our statistical model estimates that on average, individuals who commute on foot spend an additional 19.8 (95% CI 16.9–23.2 minutes per day walking compared to automobile commuters. Public transit riders walk an additional 5.0 (95% CI 3.5–6.4 minutes per day compared to automobile commuters. Bicycle commuters cycle for an additional 28.0 (95% CI 17.5–38.1 minutes per day compared to automobile commuters. The statistical model was able to predict observed transportation physical activity in the Raleigh-Durham-Chapel Hill region to within 0.5 MET-hours per day (equivalent to about 9 minutes of daily walking time for 83% of observations. Across the Raleigh-Durham-Chapel Hill region, an estimated 38 (95% CI 15–59 premature deaths potentially could be

Estimating Active Transportation Behaviors to Support Health Impact Assessment in the United States.

Science.gov (United States)

Mansfield, Theodore J; Gibson, Jacqueline MacDonald

2016-01-01

Health impact assessment (HIA) has been promoted as a means to encourage transportation and city planners to incorporate health considerations into their decision-making. Ideally, HIAs would include quantitative estimates of the population health effects of alternative planning scenarios, such as scenarios with and without infrastructure to support walking and cycling. However, the lack of baseline estimates of time spent walking or biking for transportation (together known as "active transportation"), which are critically related to health, often prevents planners from developing such quantitative estimates. To address this gap, we use data from the 2009 US National Household Travel Survey to develop a statistical model that estimates baseline time spent walking and biking as a function of the type of transportation used to commute to work along with demographic and built environment variables. We validate the model using survey data from the Raleigh-Durham-Chapel Hill, NC, USA, metropolitan area. We illustrate how the validated model could be used to support transportation-related HIAs by estimating the potential health benefits of built environment modifications that support walking and cycling. Our statistical model estimates that on average, individuals who commute on foot spend an additional 19.8 (95% CI 16.9-23.2) minutes per day walking compared to automobile commuters. Public transit riders walk an additional 5.0 (95% CI 3.5-6.4) minutes per day compared to automobile commuters. Bicycle commuters cycle for an additional 28.0 (95% CI 17.5-38.1) minutes per day compared to automobile commuters. The statistical model was able to predict observed transportation physical activity in the Raleigh-Durham-Chapel Hill region to within 0.5 MET-hours per day (equivalent to about 9 min of daily walking time) for 83% of observations. Across the Raleigh-Durham-Chapel Hill region, an estimated 38 (95% CI 15-59) premature deaths potentially could be avoided if the entire

National and State Estimates of the Numbers of Adults and Children with Active Epilepsy - United States, 2015.

Science.gov (United States)

Zack, Matthew M; Kobau, Rosemarie

2017-08-11

Epilepsy, a brain disorder leading to recurring seizures, has garnered increased public health focus because persons with epilepsy experience pronounced and persistent health and socioeconomic disparities despite treatment advances, public awareness programs, and expanded rights for persons with disabilities (1,2). For almost all states, epilepsy prevalence estimates do not exist. CDC used national data sources including the 2015 National Health Interview Survey (NHIS) for adults (aged ≥18 years), the 2011-2012 National Survey of Children's Health (NSCH), and the 2015 Current Population Survey data, describing 2014 income levels, to estimate prevalent cases of active epilepsy, overall and by state, to provide information for state public health planning. In 2015, 1.2% of the U.S. population (3.4 million persons: 3 million adults and 470,000 children) reported active epilepsy (self-reported doctor-diagnosed epilepsy and under treatment or with recent seizures within 12 months of interview) or current epilepsy (parent-reported doctor-diagnosed epilepsy and current epilepsy). Estimated numbers of persons with active epilepsy, after accounting for income and age differences by state, ranged from 5,900 in Wyoming to 427,700 in California. NHIS data from 2010-2015 indicate increases in the number of persons with active epilepsy, probably because of population growth. This study provides updated national and modeled state-specific numbers of active epilepsy cases. Public health practitioners, health care providers, policy makers, epilepsy researchers, and other epilepsy stakeholders, including family members and people with epilepsy, can use these findings to ensure that evidence-based programs meet the complex needs of adults and children with epilepsy and reduce the disparities resulting from it.

State estimation in networked systems

NARCIS (Netherlands)

Sijs, J.

2012-01-01

This thesis considers state estimation strategies for networked systems. State estimation refers to a method for computing the unknown state of a dynamic process by combining sensor measurements with predictions from a process model. The most well known method for state estimation is the Kalman

Estimating Active Transportation Behaviors to Support Health Impact Assessment in the United States

Science.gov (United States)

Mansfield, Theodore J.; Gibson, Jacqueline MacDonald

2016-01-01

Health impact assessment (HIA) has been promoted as a means to encourage transportation and city planners to incorporate health considerations into their decision-making. Ideally, HIAs would include quantitative estimates of the population health effects of alternative planning scenarios, such as scenarios with and without infrastructure to support walking and cycling. However, the lack of baseline estimates of time spent walking or biking for transportation (together known as “active transportation”), which are critically related to health, often prevents planners from developing such quantitative estimates. To address this gap, we use data from the 2009 US National Household Travel Survey to develop a statistical model that estimates baseline time spent walking and biking as a function of the type of transportation used to commute to work along with demographic and built environment variables. We validate the model using survey data from the Raleigh–Durham–Chapel Hill, NC, USA, metropolitan area. We illustrate how the validated model could be used to support transportation-related HIAs by estimating the potential health benefits of built environment modifications that support walking and cycling. Our statistical model estimates that on average, individuals who commute on foot spend an additional 19.8 (95% CI 16.9–23.2) minutes per day walking compared to automobile commuters. Public transit riders walk an additional 5.0 (95% CI 3.5–6.4) minutes per day compared to automobile commuters. Bicycle commuters cycle for an additional 28.0 (95% CI 17.5–38.1) minutes per day compared to automobile commuters. The statistical model was able to predict observed transportation physical activity in the Raleigh–Durham–Chapel Hill region to within 0.5 MET-hours per day (equivalent to about 9 min of daily walking time) for 83% of observations. Across the Raleigh–Durham–Chapel Hill region, an estimated 38 (95% CI 15–59) premature deaths potentially could

Estimation of the state of health of students of the I course of build university attributed to task medical force.

Directory of Open Access Journals (Sweden)

Kozlova A.Yu.

2012-11-01

Full Text Available The different approaches are considered near the estimation of the state of health of students. General description of the state of health and activity of students is resulted on its maintenance. It is marked that different rejections have 30% students in a state of health, disease of temporal or permanent character. The students of the first course of university took part in research. It is set that unsatisfactory physical preparation is observed 43% students, good - at 37,2%, excellent at 20%. On the whole there is a tendency to the decline of motive activity of students of the I course, frequent violations of the mode of sleep and feed. The system of recommendations is developed for employments by a physical culture and sport. It is marked that for maintenance and optimization of resources of organism of students of the I course the correctly organized athletic health work is needed.

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

Science.gov (United States)

Simon, Dan; Simon, Donald L.

2005-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Parameter and State Estimator for State Space Models

Directory of Open Access Journals (Sweden)

Ruifeng Ding

2014-01-01

Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

Modeling per capita state health expenditure variation: state-level characteristics matter.

Science.gov (United States)

Cuckler, Gigi; Sisko, Andrea

2013-01-01

In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation.

Administrative waste in the U.S. health care system in 2003: the cost to the nation, the states, and the District of Columbia, with state-specific estimates of potential savings.

Science.gov (United States)

Himmelstein, David U; Woolhandler, Steffie; Wolfe, Sidney M

2004-01-01

This report provides nationwide and state-specific estimates of U.S. health care administration spending and potential savings in 2003 were the United States to institute a Canadian-style national health insurance system. The United States wastes more on health care bureaucracy than it would cost to provide health care to all its uninsured. Administrative expenses will consume at least dollar 399.4 billion of a total health expenditure of dollar 1,660.5 billion in 2003. Streamlining administrative overhead to Canadian levels would save approximately dollar 286.0 billion in 2003, dollar 6,940 for each of the 41.2 million Americans who were uninsured as of 2001. This is substantially more than would be needed to provide full insurance coverage. The cost of excess health bureaucracy in individual states is equally striking. For example, Massachusetts, with 560,000 uninsured state residents, could save about dollar 8,556 million in 2003 (dollar 16,453 per uninsured resident of that state) if it streamlined administration to Canadian levels. New Mexico, with 373,000 uninsured, could save dollar 1,500 million on health bureaucracy (dollar 4,022 per uninsured resident). Only a single-payer national health insurance system could garner these massive administrative savings, allowing universal coverage without any increase in total health spending. Because incremental reforms necessarily preserve the current fragmented and duplicative payment structure, they cannot achieve significant bureaucratic savings.

Health Insurance Coverage: Early Release of Estimates from the National Health Interview Survey, January -- June 2013

Science.gov (United States)

... from 2010 to 2013 were also evaluated using logistic regression analysis. State-specific health insurance estimates are ... coverage options; compare health insurance plans based on cost, benefits, and other important features; choose a plan; ...

Estimating the Cost of Providing Foundational Public Health Services.

Science.gov (United States)

Mamaril, Cezar Brian C; Mays, Glen P; Branham, Douglas Keith; Bekemeier, Betty; Marlowe, Justin; Timsina, Lava

2017-12-28

To estimate the cost of resources required to implement a set of Foundational Public Health Services (FPHS) as recommended by the Institute of Medicine. A stochastic simulation model was used to generate probability distributions of input and output costs across 11 FPHS domains. We used an implementation attainment scale to estimate costs of fully implementing FPHS. We use data collected from a diverse cohort of 19 public health agencies located in three states that implemented the FPHS cost estimation methodology in their agencies during 2014-2015. The average agency incurred costs of $48 per capita implementing FPHS at their current attainment levels with a coefficient of variation (CV) of 16 percent. Achieving full FPHS implementation would require $82 per capita (CV=19 percent), indicating an estimated resource gap of $34 per capita. Substantial variation in costs exists across communities in resources currently devoted to implementing FPHS, with even larger variation in resources needed for full attainment. Reducing geographic inequities in FPHS may require novel financing mechanisms and delivery models that allow health agencies to have robust roles within the health system and realize a minimum package of public health services for the nation. © Health Research and Educational Trust.

Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health

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Kathryn C. Conlon

2016-08-01

Full Text Available There is interest among agencies and public health practitioners in the United States (USA to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida.

Global health worker salary estimates: an econometric analysis of global earnings data.

Science.gov (United States)

Serje, Juliana; Bertram, Melanie Y; Brindley, Callum; Lauer, Jeremy A

2018-01-01

Human resources are consistently cited as a leading contributor to health care costs; however the availability of internationally comparable data on health worker earnings for all countries is a challenge for estimating the costs of health care services. This paper describes an econometric model using cross sectional earnings data from the International Labour Organization (ILO) that the World Health Organizations (WHO)-Choosing Interventions that are Cost-effective programme (CHOICE) has used to prepare estimates of health worker earnings (in 2010 USD) for all WHO member states. The ILO data contained 324 observations of earnings data across 4 skill levels for 193 countries. Using this data, along with the assumption that data were missing not at random, we used a Heckman two stage selection model to estimate earning data for each of the 4 skill levels for all WHO member states. It was possible to develop a prediction model for health worker earnings for all countries for which GDP data was available. Health worker earnings vary both within country due to skill level, as well as across countries. As a multiple of GDP per capita, earnings show a negative correlation with GDP-that is lower income countries pay their health workers relatively more than higher income countries. Limited data on health worker earnings is a limiting factor in estimating the costs of global health programmes. It is hoped that these estimates will support robust health care intervention costings and projections of resources needs over the Sustainable Development Goal period.

Health states for schizophrenia and bipolar disorder within the Global Burden of Disease 2010 Study

Directory of Open Access Journals (Sweden)

Ferrari Alize J

2012-08-01

Full Text Available Abstract A comprehensive revision of the Global Burden of Disease (GBD study is expected to be completed in 2012. This study utilizes a broad range of improved methods for assessing burden, including closer attention to empirically derived estimates of disability. The aim of this paper is to describe how GBD health states were derived for schizophrenia and bipolar disorder. These will be used in deriving health state-specific disability estimates. A literature review was first conducted to settle on a parsimonious set of health states for schizophrenia and bipolar disorder. A second review was conducted to investigate the proportion of schizophrenia and bipolar disorder cases experiencing these health states. These were pooled using a quality-effects model to estimate the overall proportion of cases in each state. The two schizophrenia health states were acute (predominantly positive symptoms and residual (predominantly negative symptoms. The three bipolar disorder health states were depressive, manic, and residual. Based on estimates from six studies, 63% (38%-82% of schizophrenia cases were in an acute state and 37% (18%-62% were in a residual state. Another six studies were identified from which 23% (10%-39% of bipolar disorder cases were in a manic state, 27% (11%-47% were in a depressive state, and 50% (30%-70% were in a residual state. This literature review revealed salient gaps in the literature that need to be addressed in future research. The pooled estimates are indicative only and more data are required to generate more definitive estimates. That said, rather than deriving burden estimates that fail to capture the changes in disability within schizophrenia and bipolar disorder, the derived proportions and their wide uncertainty intervals will be used in deriving disability estimates.

Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self-assessed Health and an Efficient Discrete Choice Experiment.

Science.gov (United States)

Jonker, Marcel F; Attema, Arthur E; Donkers, Bas; Stolk, Elly A; Versteegh, Matthijs M

2017-12-01

Health state valuations of patients and non-patients are not the same, whereas health state values obtained from general population samples are a weighted average of both. The latter constitutes an often-overlooked source of bias. This study investigates the resulting bias and tests for the impact of reference dependency on health state valuations using an efficient discrete choice experiment administered to a Dutch nationally representative sample of 788 respondents. A Bayesian discrete choice experiment design consisting of eight sets of 24 (matched pairwise) choice tasks was developed, with each set providing full identification of the included parameters. Mixed logit models were used to estimate health state preferences with respondents' own health included as an additional predictor. Our results indicate that respondents with impaired health worse than or equal to the health state levels under evaluation have approximately 30% smaller health state decrements. This confirms that reference dependency can be observed in general population samples and affirms the relevance of prospect theory in health state valuations. At the same time, the limited number of respondents with severe health impairments does not appear to bias social tariffs as obtained from general population samples. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Involving Members of the Public in Health Economics Research: Insights from Selecting Health States for Valuation to Estimate Quality-Adjusted Life-Year (QALY) Weights.

Science.gov (United States)

Goodwin, Elizabeth; Boddy, Kate; Tatnell, Lynn; Hawton, Annie

2018-04-01

Over recent years, public involvement in health research has expanded considerably. However, public involvement in designing and conducting health economics research is seldom reported. Here we describe the development, delivery and assessment of an approach for involving people in a clearly defined piece of health economics research: selecting health states for valuation in estimating quality-adjusted life-years (QALYs). This involvement formed part of a study to develop a condition-specific preference-based measure of health-related quality of life, the Multiple Sclerosis Impact Scale (MSIS-8D), and the work reported here relates to the identification of plausible, or realistic, health states for valuation. An Expert Panel of three people with multiple sclerosis (MS) was recruited from a local involvement network, and two health economists designed an interactive task that enabled the Panel to identify health states that were implausible, or unlikely to be experienced. Following some initial confusion over terminology, which was resolved by discussion with the Panel, the task worked well and can be adapted to select health states for valuation in the development of any preference-based measure. As part of the involvement process, five themes were identified by the Panel members and the researchers which summarised our experiences of public involvement in this health economics research example: proportionality, task design, prior involvement, protectiveness and partnerships. These are described in the paper, along with their practical implications for involving members of the public in health economics research. Our experience demonstrates how members of the public and health economists can work together to improve the validity of health economics research. Plain Language Summary It has become commonplace to involve members of the public in health service research. However, published reports of involving people in designing health economics research are rare. We

Nongovernment Philanthropic Spending on Public Health in the United States.

Science.gov (United States)

Shaw-Taylor, Yoku

2016-01-01

The objective of this study was to estimate the dollar amount of nongovernment philanthropic spending on public health activities in the United States. Health expenditure data were derived from the US National Health Expenditures Accounts and the US Census Bureau. Results reveal that spending on public health is not disaggregated from health spending in general. The level of philanthropic spending is estimated as, on average, 7% of overall health spending, or about $150 billion annually according to National Health Expenditures Accounts data tables. When a point estimate of charity care provided by hospitals and office-based physicians is added, the value of nongovernment philanthropic expenditures reaches approximately $203 billion, or about 10% of all health spending annually.

A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve

Science.gov (United States)

Yang, Duo; Zhang, Xu; Pan, Rui; Wang, Yujie; Chen, Zonghai

2018-04-01

The state-of-health (SOH) estimation is always a crucial issue for lithium-ion batteries. In order to provide an accurate and reliable SOH estimation, a novel Gaussian process regression (GPR) model based on charging curve is proposed in this paper. Different from other researches where SOH is commonly estimated by cycle life, in this work four specific parameters extracted from charging curves are used as inputs of the GPR model instead of cycle numbers. These parameters can reflect the battery aging phenomenon from different angles. The grey relational analysis method is applied to analyze the relational grade between selected features and SOH. On the other hand, some adjustments are made in the proposed GPR model. Covariance function design and the similarity measurement of input variables are modified so as to improve the SOH estimate accuracy and adapt to the case of multidimensional input. Several aging data from NASA data repository are used for demonstrating the estimation effect by the proposed method. Results show that the proposed method has high SOH estimation accuracy. Besides, a battery with dynamic discharging profile is used to verify the robustness and reliability of this method.

Reexamination of optimal quantum state estimation of pure states

International Nuclear Information System (INIS)

Hayashi, A.; Hashimoto, T.; Horibe, M.

2005-01-01

A direct derivation is given for the optimal mean fidelity of quantum state estimation of a d-dimensional unknown pure state with its N copies given as input, which was first obtained by Hayashi in terms of an infinite set of covariant positive operator valued measures (POVM's) and by Bruss and Macchiavello establishing a connection to optimal quantum cloning. An explicit condition for POVM measurement operators for optimal estimators is obtained, by which we construct optimal estimators with finite POVMs using exact quadratures on a hypersphere. These finite optimal estimators are not generally universal, where universality means the fidelity is independent of input states. However, any optimal estimator with finite POVM for M(>N) copies is universal if it is used for N copies as input

Introduction to quantum-state estimation

CERN Document Server

Teo, Yong Siah

2016-01-01

Quantum-state estimation is an important field in quantum information theory that deals with the characterization of states of affairs for quantum sources. This book begins with background formalism in estimation theory to establish the necessary prerequisites. This basic understanding allows us to explore popular likelihood- and entropy-related estimation schemes that are suitable for an introductory survey on the subject. Discussions on practical aspects of quantum-state estimation ensue, with emphasis on the evaluation of tomographic performances for estimation schemes, experimental realizations of quantum measurements and detection of single-mode multi-photon sources. Finally, the concepts of phase-space distribution functions, which compatibly describe these multi-photon sources, are introduced to bridge the gap between discrete and continuous quantum degrees of freedom. This book is intended to serve as an instructive and self-contained medium for advanced undergraduate and postgraduate students to gra...

State Estimation for Tensegrity Robots

Science.gov (United States)

Caluwaerts, Ken; Bruce, Jonathan; Friesen, Jeffrey M.; Sunspiral, Vytas

2016-01-01

Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robot's success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.

Health Spending By State 1991-2014: Measuring Per Capita Spending By Payers And Programs.

Science.gov (United States)

Lassman, David; Sisko, Andrea M; Catlin, Aaron; Barron, Mary Carol; Benson, Joseph; Cuckler, Gigi A; Hartman, Micah; Martin, Anne B; Whittle, Lekha

2017-07-01

As the US health sector evolves and changes, it is informative to estimate and analyze health spending trends at the state level. These estimates, which provide information about consumption of health care by residents of a state, serve as a baseline for state and national-level policy discussions. This study examines per capita health spending by state of residence and per enrollee spending for the three largest payers (Medicare, Medicaid, and private health insurance) through 2014. Moreover, it discusses in detail the impacts of the Affordable Care Act implementation and the most recent economic recession and recovery on health spending at the state level. According to this analysis, these factors affected overall annual growth in state health spending and the payers and programs that paid for that care. They did not, however, substantially change state rankings based on per capita spending levels over the period. Project HOPE—The People-to-People Health Foundation, Inc.

Estimating state-contingent production functions

DEFF Research Database (Denmark)

Rasmussen, Svend; Karantininis, Kostas

The paper reviews the empirical problem of estimating state-contingent production functions. The major problem is that states of nature may not be registered and/or that the number of observation per state is low. Monte Carlo simulation is used to generate an artificial, uncertain production...... environment based on Cobb Douglas production functions with state-contingent parameters. The pa-rameters are subsequently estimated based on different sizes of samples using Generalized Least Squares and Generalized Maximum Entropy and the results are compared. It is concluded that Maximum Entropy may...

How do Zimbabweans value health states?

DEFF Research Database (Denmark)

Jelsma, Jennifer; Hansen, Kristian; De Weerdt, Willy

2003-01-01

coefficient, followed by the inability to wash and dress oneself. CONCLUSION: Despite a generally lower education level than their European counterparts, urban Zimbabweans appear to value health states in a consistent manner, and the determination of a global method of establishing quality of life weights may...... residential plots of land in a high-density suburb of Harare valued descriptors of 38 health states based on different combinations of the five domains of the EQ-5D (mobility, self-care, usual activities, pain or discomfort and anxiety or depression). The English version of the EQ-5D was used. The time trade......-off method was used to determine the values, and 19,020 individual preferences for health states were analysed. A residual maximum likelihood linear mixed model was used to estimate a function for predicting the values of all possible combinations of levels on the five domains. The model was fit to a random...

An Empirical Method to Fuse Partially Overlapping State Vectors for Distributed State Estimation

NARCIS (Netherlands)

Sijs, J.; Hanebeck, U.; Noack, B.

2013-01-01

State fusion is a method for merging multiple estimates of the same state into a single fused estimate. Dealing with multiple estimates is one of the main concerns in distributed state estimation, where an estimated value of the desired state vector is computed in each node of a networked system.

Terrorism and emergency preparedness in state and territorial public health departments--United States, 2004.

Science.gov (United States)

2005-05-13

After the events of September 11, 2001, federal funding for state public health preparedness programs increased from $67 million in fiscal year (FY) 2001 to approximately $1 billion in FY 2002. These funds were intended to support preparedness for and response to terrorism, infectious disease outbreaks, and other public health threats and emergencies. The Council of State and Territorial Epidemiologists (CSTE) assessed the impact of funding on epidemiologic capacity, including terrorism preparedness and response, in state health departments in November 2001 and again in May 2004, after distribution of an additional $1 billion in FY 2003. This report describes the results of those assessments, which indicated that increased funding for terrorism preparedness and emergency response has rapidly increased the number of epidemiologists and increased capacity for preparedness at the state level. However, despite the increase in epidemiologists, state public health officials estimate that 192 additional epidemiologists, an increase of 45.3%, are needed nationwide to fully staff terrorism preparedness programs.

State Alcohol-Impaired-Driving Estimates

Science.gov (United States)

... 2012 Data DOT HS 812 017 May 2014 State Alcohol-Impaired-Driving Estimates This fact sheet contains ... alcohol involvement in fatal crashes for the United States and individually for the 50 States, the District ...

Bad Data Detection and Identification for State Estimation

DEFF Research Database (Denmark)

Khazraj, Hesam; Silva, Filipe Miguel Faria da; Bak, Claus Leth

2017-01-01

state estimations. To achieve this object largest normalized residual test (rNmax) is applied to detect and analysis bad data in phasor measurements, power flow and power injections of buses used for the novel PMU-based state estimation. The main advantage of new PMU-based static state estimation......Bad data analysis is an important part of both dynamic and static state estimations. This paper present novel algorithm of phase measurement unit (PMU)-based static state estimation to detect and identify multiple bad data in critical measurements, which is not possible with traditional static...... is that phasor measurements can be added separately into the proposed state estimation. This paper proposes an ideal method to combine the phasor measurements into the conventional state estimator in a systematic way, so that no significant modification is necessary to the existing algorithm. The main advantage...

Estimation of utility weights for human papilloma virus-related health states according to disease severity.

Science.gov (United States)

Ock, Minsu; Park, Jeong-Yeol; Son, Woo-Seung; Lee, Hyeon-Jeong; Kim, Seon-Ha; Jo, Min-Woo

2016-11-28

A cost-utility study of a human papilloma virus (HPV) vaccine requires that the utility weights for HPV-related health states (i.e., cervical intraepithelial neoplasia (CIN), cervical cancer, and condyloma) be evaluated. The aim of the present study was to determine the utility weights for HPV-related health states. Hypothetical standardised health states related to HPV were developed based on patient education material and previous publications. To fully reflect disease progression from diagnosis to prognosis, each health state comprised four parts (diagnosis, symptoms, treatment, and progression and prognosis). Nine-hundred members from the Korean general population evaluated the HPV-related health states using a visual analogue scale (VAS) and a standard gamble (SG) approach, which were administered face-to-face via computer-assisted interview. The mean utility values were calculated for each HPV-related health state. According to the VAS, the highest utility (0.73) was HPV-positive status, followed by condyloma (0.66), and CIN grade I (0.61). The lowest utility (0.18) was cervical cancer requiring chemotherapy without surgery, followed by cervical cancer requiring chemoradiation therapy (0.42). SG revealed that the highest utility (0.83) was HPV-positive status, followed by condyloma (0.78), and CIN grade I (0.77). The lowest utility (0.43) was cervical cancer requiring chemotherapy without surgery, followed by cervical cancer requiring chemoradiation therapy (0.60). This study was based on a large sample derived from the general Korean population; therefore, the calculated utility weights might be useful for evaluating the economic benefit of cancer screening and HPV vaccination programs.

Efficiency of Health Care Sector at Sub-State Level in India: A Case of Punjab

Directory of Open Access Journals (Sweden)

Brijesh C. Purohit

2009-11-01

Full Text Available In recent years, WHO and other individual researchers have advocated estimation of health system performance through stochastic frontier models. It provides an idealized yardstick to evaluate economic performance of health system. So far attempts in India have remained focused at state level analysis. This paper attempts a sub-state level analysis for an affluent Indian state, namely Punjab, by using stochastic frontier technique. Our results provide pertinent insight into state health system and facilitate health facility planning at the sub-state level. Carried out in two stages of estimation, our results suggest that life expectancy in the Indian state could be enhanced considerably by correcting the factors that are adversely influencing the sub-state level health system efficiency. A higher budgetary allocation for health manpower is recommended by us to improve efficiency in poorly performing districts. This may be supported by policy initiatives outside the health system by empowering women through better education and work participation.

State estimation for a hexapod robot

CSIR Research Space (South Africa)

Lubbe, Estelle

2015-09-01

Full Text Available This paper introduces a state estimation methodology for a hexapod robot that makes use of proprioceptive sensors and a kinematic model of the robot. The methodology focuses on providing reliable full pose state estimation for a commercially...

State energy data report 1994: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-10-01

This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

State energy data report 1994: Consumption estimates

International Nuclear Information System (INIS)

1996-10-01

This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA's energy models. Division is made for each energy type and end use sector. Nuclear electric power is included

State energy data report 1995 - consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-01

The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.

Development of realtime cognitive state estimator

International Nuclear Information System (INIS)

Takahashi, Makoto; Kitamura, Masashi; Yoshikaea, Hidekazu

2004-01-01

The realtime cognitive state estimator based on the set of physiological measures has been developed in order to provide valuable information on the human behavior during the interaction through the Man-Machine Interface. The artificial neural network has been adopted to categorize the cognitive states by using the qualitative physiological data pattern as the inputs. The laboratory experiments, in which the subjects' cognitive states were intentionally controlled by the task presented, were performed to obtain training data sets for the neural network. The developed system has been shown to be capable of estimating cognitive state with higher accuracy and realtime estimation capability has also been confirmed through the data processing experiments. (author)

UAV State Estimation Modeling Techniques in AHRS

Science.gov (United States)

Razali, Shikin; Zhahir, Amzari

2017-11-01

Autonomous unmanned aerial vehicle (UAV) system is depending on state estimation feedback to control flight operation. Estimation on the correct state improves navigation accuracy and achieves flight mission safely. One of the sensors configuration used in UAV state is Attitude Heading and Reference System (AHRS) with application of Extended Kalman Filter (EKF) or feedback controller. The results of these two different techniques in estimating UAV states in AHRS configuration are displayed through position and attitude graphs.

Comparing population health in the United States and Canada

Directory of Open Access Journals (Sweden)

Huguet Nathalie

2010-04-01

Full Text Available Abstract Background The objective of the paper is to compare population health in the United States (US and Canada. Although the two countries are very similar in many ways, there are potentially important differences in the levels of social and economic inequality and the organization and financing of and access to health care in the two countries. Methods Data are from the Joint Canada/United States Survey of Health 2002/03. The Health Utilities Index Mark 3 (HUI3 was used to measure overall health-related quality of life (HRQL. Mean HUI3 scores were compared, adjusting for major determinants of health, including body mass index, smoking, education, gender, race, and income. In addition, estimates of life expectancy were compared. Finally, mean HUI3 scores by age and gender and Canadian and US life tables were used to estimate health-adjusted life expectancy (HALE. Results Life expectancy in Canada is higher than in the US. For those Conclusions The population of Canada appears to be substantially healthier than the US population with respect to life expectancy, HRQL, and HALE. Factors that account for the difference may include access to health care over the full life span (universal health insurance and lower levels of social and economic inequality, especially among the elderly.

Willingness to pay for improved respiratory and cardiovascular health: a multiple-format, stated-preference approach.

Science.gov (United States)

Johnson, F R; Banzhaf, M R; Desvousges, W H

2000-06-01

This study uses stated-preference (SP) analysis to measure willingness to pay (WTP) to reduce acute episodes of respiratory and cardiovascular ill health. The SP survey employs a modified version of the health state descriptions used in the Quality of Well Being (QWB) Index. The four health state attributes are symptom, episode duration, activity restrictions and cost. Preferences are elicited using two different SP formats: graded-pair and discrete-choice. The different formats cause subjects to focus on different evaluation strategies. Combining two elicitation formats yields more valid and robust estimates than using only one approach. Estimates of indirect utility function parameters are obtained using advanced panel econometrics for each format separately and jointly. Socio-economic differences in health preferences are modelled by allowing the marginal utility of money relative to health attributes to vary across respondents. Because the joint model captures the combined preference information provided by both elicitation formats, these model estimates are used to calculate WTP. The results demonstrate the feasibility of estimating meaningful WTP values for policy-relevant respiratory and cardiac symptoms, even from subjects who never have personally experienced these conditions. Furthermore, because WTP estimates are for individual components of health improvements, estimates can be aggregated in various ways depending upon policy needs. Thus, using generic health attributes facilitates transferring WTP estimates for benefit-cost analysis of a variety of potential health interventions. Copyright 2000 John Wiley & Sons, Ltd.

State energy data report 1993: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-07-01

The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.

Self-learning estimation of quantum states

International Nuclear Information System (INIS)

Hannemann, Th.; Reiss, D.; Balzer, Ch.; Neuhauser, W.; Toschek, P.E.; Wunderlich, Ch.

2002-01-01

We report the experimental estimation of arbitrary qubit states using a succession of N measurements on individual qubits, where the measurement basis is changed during the estimation procedure conditioned on the outcome of previous measurements (self-learning estimation). Two hyperfine states of a single trapped 171 Yb + ion serve as a qubit. It is demonstrated that the difference in fidelity between this adaptive strategy and passive strategies increases in the presence of decoherence

State Energy Data Report, 1991: Consumption estimates

International Nuclear Information System (INIS)

1993-05-01

The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA's energy models

Generating Health Estimates by Zip Code: A Semiparametric Small Area Estimation Approach Using the California Health Interview Survey.

Science.gov (United States)

Wang, Yueyan; Ponce, Ninez A; Wang, Pan; Opsomer, Jean D; Yu, Hongjian

2015-12-01

We propose a method to meet challenges in generating health estimates for granular geographic areas in which the survey sample size is extremely small. Our generalized linear mixed model predicts health outcomes using both individual-level and neighborhood-level predictors. The model's feature of nonparametric smoothing function on neighborhood-level variables better captures the association between neighborhood environment and the outcome. Using 2011 to 2012 data from the California Health Interview Survey, we demonstrate an empirical application of this method to estimate the fraction of residents without health insurance for Zip Code Tabulation Areas (ZCTAs). Our method generated stable estimates of uninsurance for 1519 of 1765 ZCTAs (86%) in California. For some areas with great socioeconomic diversity across adjacent neighborhoods, such as Los Angeles County, the modeled uninsured estimates revealed much heterogeneity among geographically adjacent ZCTAs. The proposed method can increase the value of health surveys by providing modeled estimates for health data at a granular geographic level. It can account for variations in health outcomes at the neighborhood level as a result of both socioeconomic characteristics and geographic locations.

Survey of State-Level Cost and Benefit Estimates of Renewable Portfolio Standards

Energy Technology Data Exchange (ETDEWEB)

Heeter, J.; Barbose, G.; Bird, L.; Weaver, S.; Flores-Espino, F.; Kuskova-Burns, K.; Wiser, R.

2014-05-01

Most renewable portfolio standards (RPS) have five or more years of implementation experience, enabling an assessment of their costs and benefits. Understanding RPS costs and benefits is essential for policymakers evaluating existing RPS policies, assessing the need for modifications, and considering new policies. This study provides an overview of methods used to estimate RPS compliance costs and benefits, based on available data and estimates issued by utilities and regulators. Over the 2010-2012 period, average incremental RPS compliance costs in the United States were equivalent to 0.8% of retail electricity rates, although substantial variation exists around this average, both from year-to-year and across states. The methods used by utilities and regulators to estimate incremental compliance costs vary considerably from state to state and a number of states are currently engaged in processes to refine and standardize their approaches to RPS cost calculation. The report finds that state assessments of RPS benefits have most commonly attempted to quantitatively assess avoided emissions and human health benefits, economic development impacts, and wholesale electricity price savings. Compared to the summary of RPS costs, the summary of RPS benefits is more limited, as relatively few states have undertaken detailed benefits estimates, and then only for a few types of potential policy impacts. In some cases, the same impacts may be captured in the assessment of incremental costs. For these reasons, and because methodologies and level of rigor vary widely, direct comparisons between the estimates of benefits and costs are challenging.

Estimates of lifetime infertility from three states: the behavioral risk factor surveillance system.

Science.gov (United States)

Crawford, Sara; Fussman, Chris; Bailey, Marie; Bernson, Dana; Jamieson, Denise J; Murray-Jordan, Melissa; Kissin, Dmitry M

2015-07-01

Knowledge of state-specific infertility is limited. The objectives of this study were to explore state-specific estimates of lifetime prevalence of having ever experienced infertility, sought treatment for infertility, types of treatments sought, and treatment outcomes. Male and female adult residents aged 18-50 years from three states involved in the States Monitoring Assisted Reproductive Technology Collaborative (Florida, Massachusetts, and Michigan) were asked state-added infertility questions as part of the 2012 Behavioral Risk Factor Surveillance System, a state-based, health-related telephone survey. Analysis involved estimation of lifetime prevalence of infertility. The estimated lifetime prevalence of infertility among 1,285 adults in Florida, 1,302 in Massachusetts, and 3,360 in Michigan was 9.7%, 6.0%, and 4.2%, respectively. Among 736 adults in Florida, 1,246 in Massachusetts, and 2,742 in Michigan that have ever tried to get pregnant, the lifetime infertility prevalence was 25.3% in Florida, 9.9% in Massachusetts, and 5.8% in Michigan. Among those with a history of infertility, over half sought treatment (60.7% in Florida, 70.6% in Massachusetts, and 51.6% in Michigan), the most common being non-assisted reproductive technology fertility treatments (61.3% in Florida, 66.0% in Massachusetts, and 75.9% in Michigan). State-specific estimates of lifetime infertility prevalence in Florida, Massachusetts, and Michigan varied. Variations across states are difficult to interpret, as they likely reflect both true differences in prevalence and differences in data collection questionnaires. State-specific estimates are needed for the prevention, detection, and management of infertility, but estimates should be based on a common set of questions appropriate for these goals.

Societal Preferences for EQ-5D Health States from a Brazilian Population Survey.

Science.gov (United States)

Viegas Andrade, Mônica; Noronha, Kenya; Kind, Paul; Maia, Ana Carolina; Miranda de Menezes, Renata; De Barros Reis, Carla; Nepomuceno Souza, Michelle; Martins, Diego; Gomes, Lucas; Nichele, Daniel; Calazans, Julia; Mascarenhas, Tamires; Carvalho, Lucas; Lins, Camila

2013-12-01

To elicit preference weights for a subset of EuroQol five-dimensional (EQ-5D) questionnaire health states from a representative sample for the state of Minas Gerais, Brazil, using a time trade-off (TTO) method and to analyze these data so as to estimate social preference weights for the complete set of 243 states. Data came from a valuation study with 3362 literate individuals aged between 18 and 64 years living in urban areas. The present study was based on quota sampling by age and sex. Face-to-face interviews were conducted in participants' own homes. A total of 99 EQ-5D questionnaire health states were selected, presorted into 26 blocks of six unique health states. Each participant valued one block together with the full health, worst health, and dead states. Each health state was evaluated by more than 100 individuals. TTO data were modeled at both individual and aggregate levels by using ordinary least squares and random effects methods. Values estimated by different models yielded very similar results with satisfactory goodness-of-fit statistics: the mean absolute error was around 0.03 and fewer than 25% of the states had a mean absolute error greater than 0.05. Dummies coefficients for each level within the EQ-5D questionnaire dimensions of health displayed an internally consistent ordering, with the mobility dimension demonstrating the largest value decrement. The values of mean observed transformed TTO values range from 0.869 to-0.235. The study demonstrates the feasibility of conducting face-to-face interviews using TTO in a Brazilian population setting. The estimated values for EQ-5D questionnaire health states based on this Minas Gerais survey represent an important first step in establishing national Brazilian social preference weights for the EQ-5D questionnaire. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Particle-filtering-based estimation of maximum available power state in Lithium-Ion batteries

International Nuclear Information System (INIS)

Burgos-Mellado, Claudio; Orchard, Marcos E.; Kazerani, Mehrdad; Cárdenas, Roberto; Sáez, Doris

2016-01-01

Highlights: • Approach to estimate the state of maximum power available in Lithium-Ion battery. • Optimisation problem is formulated on the basis of a non-linear dynamic model. • Solutions of the optimisation problem are functions of state of charge estimates. • State of charge estimates computed using particle filter algorithms. - Abstract: Battery Energy Storage Systems (BESS) are important for applications related to both microgrids and electric vehicles. If BESS are used as the main energy source, then it is required to include adequate procedures for the estimation of critical variables such as the State of Charge (SoC) and the State of Health (SoH) in the design of Battery Management Systems (BMS). Furthermore, in applications where batteries are exposed to high charge and discharge rates it is also desirable to estimate the State of Maximum Power Available (SoMPA). In this regard, this paper presents a novel approach to the estimation of SoMPA in Lithium-Ion batteries. This method formulates an optimisation problem for the battery power based on a non-linear dynamic model, where the resulting solutions are functions of the SoC. In the battery model, the polarisation resistance is modelled using fuzzy rules that are function of both SoC and the discharge (charge) current. Particle filtering algorithms are used as an online estimation technique, mainly because these algorithms allow approximating the probability density functions of the SoC and SoMPA even in the case of non-Gaussian sources of uncertainty. The proposed method for SoMPA estimation is validated using the experimental data obtained from an experimental setup designed for charging and discharging the Lithium-Ion batteries.

Multilevel model to estimate county-level untreated dental caries among US children aged 6-9years using the National Health and Nutrition Examination Survey.

Science.gov (United States)

Lin, Mei; Zhang, Xingyou; Holt, James B; Robison, Valerie; Li, Chien-Hsun; Griffin, Susan O

2018-06-01

Because conducting population-based oral health screening is resource intensive, oral health data at small-area levels (e.g., county-level) are not commonly available. We applied the multilevel logistic regression and poststratification method to estimate county-level prevalence of untreated dental caries among children aged 6-9years in the United States using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010 linked with various area-level data at census tract, county and state levels. We validated model-based national estimates against direct estimates from NHANES. We also compared model-based estimates with direct estimates from select State Oral Health Surveys (SOHS) at state and county levels. The model with individual-level covariates only and the model with individual-, census tract- and county-level covariates explained 7.2% and 96.3% respectively of overall county-level variation in untreated caries. Model-based county-level prevalence estimates ranged from 4.9% to 65.2% with median of 22.1%. The model-based national estimate (19.9%) matched the NHANES direct estimate (19.8%). We found significantly positive correlations between model-based estimates for 8-year-olds and direct estimates from the third-grade State Oral Health Surveys (SOHS) at state level for 34 states (Pearson coefficient: 0.54, P=0.001) and SOHS estimates at county level for 53 New York counties (Pearson coefficient: 0.38, P=0.006). This methodology could be a useful tool to characterize county-level disparities in untreated dental caries among children aged 6-9years and complement oral health surveillance to inform public health programs especially when local-level data are not available although the lack of external validation due to data unavailability should be acknowledged. Published by Elsevier Inc.

An Empirical State Error Covariance Matrix for Batch State Estimation

Science.gov (United States)

Frisbee, Joseph H., Jr.

2011-01-01

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the

A framework with nonlinear system model and nonparametric noise for gas turbine degradation state estimation

International Nuclear Information System (INIS)

Hanachi, Houman; Liu, Jie; Banerjee, Avisekh; Chen, Ying

2015-01-01

Modern health management approaches for gas turbine engines (GTEs) aim to precisely estimate the health state of the GTE components to optimize maintenance decisions with respect to both economy and safety. In this research, we propose an advanced framework to identify the most likely degradation state of the turbine section in a GTE for prognostics and health management (PHM) applications. A novel nonlinear thermodynamic model is used to predict the performance parameters of the GTE given the measurements. The ratio between real efficiency of the GTE and simulated efficiency in the newly installed condition is defined as the health indicator and provided at each sequence. The symptom of nonrecoverable degradations in the turbine section, i.e. loss of turbine efficiency, is assumed to be the internal degradation state. A regularized auxiliary particle filter (RAPF) is developed to sequentially estimate the internal degradation state in nonuniform time sequences upon receiving sets of new measurements. The effectiveness of the technique is examined using the operating data over an entire time-between-overhaul cycle of a simple-cycle industrial GTE. The results clearly show the trend of degradation in the turbine section and the occasional fluctuations, which are well supported by the service history of the GTE. The research also suggests the efficacy of the proposed technique to monitor the health state of the turbine section of a GTE by implementing model-based PHM without the need for additional instrumentation. (paper)

Effects of state-level Earned Income Tax Credit laws in the U.S. on maternal health behaviors and infant health outcomes.

Science.gov (United States)

Markowitz, Sara; Komro, Kelli A; Livingston, Melvin D; Lenhart, Otto; Wagenaar, Alexander C

2017-12-01

The purpose of this paper is to investigate the effects of state-level Earned Income Tax Credit (EITC) laws in the U.S. on maternal health behaviors and infant health outcomes. Using multi-state, multi-year difference-in-differences analyses, we estimated effects of state EITC generosity on maternal health behaviors, birth weight and gestation weeks. We find little difference in maternal health behaviors associated with state-level EITC. In contrast, results for key infant health outcomes of birth weight and gestation weeks show small improvements in states with EITCs, with larger effects seen among states with more generous EITCs. Our results provide evidence for important health benefits of state-level EITC policies. Copyright © 2017 Elsevier Ltd. All rights reserved.

State estimation for large-scale wastewater treatment plants.

Science.gov (United States)

Busch, Jan; Elixmann, David; Kühl, Peter; Gerkens, Carine; Schlöder, Johannes P; Bock, Hans G; Marquardt, Wolfgang

2013-09-01

Many relevant process states in wastewater treatment are not measurable, or their measurements are subject to considerable uncertainty. This poses a serious problem for process monitoring and control. Model-based state estimation can provide estimates of the unknown states and increase the reliability of measurements. In this paper, an integrated approach is presented for the optimization-based sensor network design and the estimation problem. Using the ASM1 model in the reference scenario BSM1, a cost-optimal sensor network is designed and the prominent estimators EKF and MHE are evaluated. Very good estimation results for the system comprising 78 states are found requiring sensor networks of only moderate complexity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Estimation of Branch Topology Errors in Power Networks by WLAN State Estimation

Energy Technology Data Exchange (ETDEWEB)

Kim, Hong Rae [Soonchunhyang University(Korea); Song, Kyung Bin [Kei Myoung University(Korea)

2000-06-01

The purpose of this paper is to detect and identify topological errors in order to maintain a reliable database for the state estimator. In this paper, a two stage estimation procedure is used to identify the topology errors. At the first stage, the WLAV state estimator which has characteristics to remove bad data during the estimation procedure is run for finding out the suspected branches at which topology errors take place. The resulting residuals are normalized and the measurements with significant normalized residuals are selected. A set of suspected branches is formed based on these selected measurements; if the selected measurement if a line flow, the corresponding branch is suspected; if it is an injection, then all the branches connecting the injection bus to its immediate neighbors are suspected. A new WLAV state estimator adding the branch flow errors in the state vector is developed to identify the branch topology errors. Sample cases of single topology error and topology error with a measurement error are applied to IEEE 14 bus test system. (author). 24 refs., 1 fig., 9 tabs.

Estimating the impact of state budget cuts and redirection of prevention resources on the HIV epidemic in 59 California local health departments.

Science.gov (United States)

Lin, Feng; Lasry, Arielle; Sansom, Stephanie L; Wolitski, Richard J

2013-01-01

In the wake of a national economic downturn, the state of California, in 2009-2010, implemented budget cuts that eliminated state funding of HIV prevention and testing. To mitigate the effect of these cuts remaining federal funds were redirected. This analysis estimates the impact of these budget cuts and reallocation of resources on HIV transmission and associated HIV treatment costs. We estimated the effect of the budget cuts and reallocation for California county health departments (excluding Los Angeles and San Francisco) on the number of individuals living with or at-risk for HIV who received HIV prevention services. We used a Bernoulli model to estimate the number of new infections that would occur each year as a result of the changes, and assigned lifetime treatment costs to those new infections. We explored the effect of redirecting federal funds to more cost-effective programs, as well as the potential effect of allocating funds proportionately by transmission category. We estimated that cutting HIV prevention resulted in 55 new infections that were associated with $20 million in lifetime treatment costs. The redirection of federal funds to more cost-effective programs averted 15 HIV infections. If HIV prevention funding were allocated proportionately to transmission categories, we estimated that HIV infections could be reduced below the number that occurred annually before the state budget cuts. Reducing funding for HIV prevention may result in short-term savings at the expense of additional HIV infections and increased HIV treatment costs. Existing HIV prevention funds would likely have a greater impact on the epidemic if they were allocated to the more cost-effective programs and the populations most likely to acquire and transmit the infection.

Estimated HIV incidence in the United States, 2006-2009.

Directory of Open Access Journals (Sweden)

Joseph Prejean

Full Text Available BACKGROUND: The estimated number of new HIV infections in the United States reflects the leading edge of the epidemic. Previously, CDC estimated HIV incidence in the United States in 2006 as 56,300 (95% CI: 48,200-64,500. We updated the 2006 estimate and calculated incidence for 2007-2009 using improved methodology. METHODOLOGY: We estimated incidence using incidence surveillance data from 16 states and 2 cities and a modification of our previously described stratified extrapolation method based on a sample survey approach with multiple imputation, stratification, and extrapolation to account for missing data and heterogeneity of HIV testing behavior among population groups. PRINCIPAL FINDINGS: Estimated HIV incidence among persons aged 13 years and older was 48,600 (95% CI: 42,400-54,700 in 2006, 56,000 (95% CI: 49,100-62,900 in 2007, 47,800 (95% CI: 41,800-53,800 in 2008 and 48,100 (95% CI: 42,200-54,000 in 2009. From 2006 to 2009 incidence did not change significantly overall or among specific race/ethnicity or risk groups. However, there was a 21% (95% CI:1.9%-39.8%; p = 0.017 increase in incidence for people aged 13-29 years, driven by a 34% (95% CI: 8.4%-60.4% increase in young men who have sex with men (MSM. There was a 48% increase among young black/African American MSM (12.3%-83.0%; p<0.001. Among people aged 13-29, only MSM experienced significant increases in incidence, and among 13-29 year-old MSM, incidence increased significantly among young, black/African American MSM. In 2009, MSM accounted for 61% of new infections, heterosexual contact 27%, injection drug use (IDU 9%, and MSM/IDU 3%. CONCLUSIONS/SIGNIFICANCE: Overall, HIV incidence in the United States was relatively stable 2006-2009; however, among young MSM, particularly black/African American MSM, incidence increased. HIV continues to be a major public health burden, disproportionately affecting several populations in the United States, especially MSM and racial and

Estimating inpatient hospital prices from state administrative data and hospital financial reports.

Science.gov (United States)

Levit, Katharine R; Friedman, Bernard; Wong, Herbert S

2013-10-01

To develop a tool for estimating hospital-specific inpatient prices for major payers. AHRQ Healthcare Cost and Utilization Project State Inpatient Databases and complete hospital financial reporting of revenues mandated in 10 states for 2006. Hospital discharge records and hospital financial information were merged to estimate revenue per stay by payer. Estimated prices were validated against other data sources. Hospital prices can be reasonably estimated for 10 geographically diverse states. All-payer price-to-charge ratios, an intermediate step in estimating prices, compare favorably to cost-to-charge ratios. Estimated prices also compare well with Medicare, MarketScan private insurance, and the Medical Expenditure Panel Survey prices for major payers, given limitations of each dataset. Public reporting of prices is a consumer resource in making decisions about health care treatment; for self-pay patients, they can provide leverage in negotiating discounts off of charges. Researchers can also use prices to increase understanding of the level and causes of price differentials among geographic areas. Prices by payer expand investigational tools available to study the interaction of inpatient hospital price setting among public and private payers--an important asset as the payer mix changes with the implementation of the Affordable Care Act. © Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Mathematical model of transmission network static state estimation

Directory of Open Access Journals (Sweden)

Ivanov Aleksandar

2012-01-01

Full Text Available In this paper the characteristics and capabilities of the power transmission network static state estimator are presented. The solving process of the mathematical model containing the measurement errors and their processing is developed. To evaluate difference between the general model of state estimation and the fast decoupled state estimation model, the both models are applied to an example, and so derived results are compared.

Linear Covariance Analysis and Epoch State Estimators

Science.gov (United States)

Markley, F. Landis; Carpenter, J. Russell

2014-01-01

This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.

State energy data report 1996: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-02-01

The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.

State energy data report 1996: Consumption estimates

International Nuclear Information System (INIS)

1999-02-01

The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA's energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs

New developments in state estimation for Nonlinear Systems

DEFF Research Database (Denmark)

Nørgård, Peter Magnus; Poulsen, Niels Kjølstad; Ravn, Ole

2000-01-01

Based on an interpolation formula, accurate state estimators for nonlinear systems can be derived. The estimators do not require derivative information which makes them simple to implement.; State estimators for nonlinear systems are derived based on polynomial approximations obtained with a mult......-known estimators, such as the extended Kalman filter (EKF) and its higher-order relatives, in most practical applications....

Power distribution, the environment, and public health. A state-level analysis

International Nuclear Information System (INIS)

Boyce, James K.; Klemer, Andrew R.; Templet, Paul H.; Willis, Cleve E.

1999-01-01

This paper examines relationships among power distribution, the environment, and public health by means of a cross-sectional analysis of the 50 US states. A measure of inter-state variations in power distribution is derived from data on voter participation, tax fairness, Medicaid access, and educational attainment. We develop and estimate a recursive model linking the distribution of power to environmental policy, environmental stress, and public health. The results support the hypothesis that greater power inequality leads to weaker environmental policies, which in turn lead to greater environmental degradation and to adverse public health outcomes

Power distribution, the environment, and public health. A state-level analysis

Energy Technology Data Exchange (ETDEWEB)

Boyce, James K. [Department of Economics, University of Massachusetts, Amherst, MA 01003 (United States); Klemer, Andrew R. [Department of Biology, University of Minnesota, Duluth, MN (United States); Templet, Paul H. [Institute of Environmental Studies, Louisiana State University, Baton Rouge, LA (United States); Willis, Cleve E. [Department of Resource Economics, University of Massachusetts, Amherst, MA 01003 (United States)

1999-04-15

This paper examines relationships among power distribution, the environment, and public health by means of a cross-sectional analysis of the 50 US states. A measure of inter-state variations in power distribution is derived from data on voter participation, tax fairness, Medicaid access, and educational attainment. We develop and estimate a recursive model linking the distribution of power to environmental policy, environmental stress, and public health. The results support the hypothesis that greater power inequality leads to weaker environmental policies, which in turn lead to greater environmental degradation and to adverse public health outcomes.

Power distribution, the environment, and public health. A state-level analysis

Energy Technology Data Exchange (ETDEWEB)

Boyce, James K. [Department of Economics, University of Massachusetts, Amherst, MA 01003 (United States); Klemer, Andrew R. [Department of Biology, University of Minnesota, Duluth, MN (United States); Templet, Paul H. [Institute of Environmental Studies, Louisiana State University, Baton Rouge, LA (United States); Willis, Cleve E. [Department of Resource Economics, University of Massachusetts, Amherst, MA 01003 (United States)

1999-04-15

This paper examines relationships among power distribution, the environment, and public health by means of a cross-sectional analysis of the 50 US states. A measure of inter-state variations in power distribution is derived from data on voter participation, tax fairness, Medicaid access, and educational attainment. We develop and estimate a recursive model linking the distribution of power to environmental policy, environmental stress, and public health. The results support the hypothesis that greater power inequality leads to weaker environmental policies, which in turn lead to greater environmental degradation and to adverse public health outcomes

Duplicate Health Insurance Coverage: Determinants of Variation Across States

OpenAIRE

Luft, Harold S.; Maerki, Susan C.

1982-01-01

Although it is recognized that many people have duplicate private health insurance coverage, either through separate purchase or as health benefits in multi-earner families, there has been little analysis of the factors determining duplicate coverage rates. A new data source, the Survey of Income and Education, offers a comparison with the only previous source of state level data, the estimates from the Health Insurance Association of America. The R2 between the two sets is only .3 and certai...

State-level marriage equality and the health of same-sex couples.

Science.gov (United States)

Kail, Ben Lennox; Acosta, Katie L; Wright, Eric R

2015-06-01

We assessed the association between the health of people in same-sex relationships and the degree and nature of the legal recognition of same-sex relationships offered in the states in which they resided. We conducted secondary data analyses on the 2010 to 2013 Current Population Survey and publicly available data from Freedom to Marry, Inc. We estimated ordered logistic regression models in a 4-level framework to assess the impact of states' legal stances toward same-sex marriage on self-assessed health. Our findings indicated, relative to states with antigay constitutional amendments, that same-sex couples living in states with legally sanctioned marriage reported higher levels of self-assessed health. Our findings suggested that full legal recognition of same-sex relationships through marriage might be an important legal and policy strategy for improving the health of same-sex couples.

Transition probabilities of health states for workers in Malaysia using a Markov chain model

Science.gov (United States)

Samsuddin, Shamshimah; Ismail, Noriszura

2017-04-01

The aim of our study is to estimate the transition probabilities of health states for workers in Malaysia who contribute to the Employment Injury Scheme under the Social Security Organization Malaysia using the Markov chain model. Our study uses four states of health (active, temporary disability, permanent disability and death) based on the data collected from the longitudinal studies of workers in Malaysia for 5 years. The transition probabilities vary by health state, age and gender. The results show that men employees are more likely to have higher transition probabilities to any health state compared to women employees. The transition probabilities can be used to predict the future health of workers in terms of a function of current age, gender and health state.

On state estimation in electric drives

International Nuclear Information System (INIS)

Leon, A.E.; Solsona, J.A.

2010-01-01

This paper deals with state estimation in electric drives. On one hand a nonlinear observer is designed, whereas on the other hand the speed state is estimated by using the dirty derivative from the position measured. The dirty derivative is an approximate version of the perfect derivative which introduces an estimation error few times analyzed in drive applications. For this reason, our proposal in this work consists in illustrating several aspects on the performance of the dirty derivator in presence of both model uncertainties and noisy measurements. To this end, a case study is introduced. The case study considers rotor speed estimation in a permanent magnet stepper motor, by assuming that rotor position and electrical variables are measured. In addition, this paper presents comments about the connection between dirty derivators and observers, and advantages and disadvantages of both techniques are also remarked.

State-Level Estimates of Cancer-Related Absenteeism Costs

Science.gov (United States)

Tangka, Florence K.; Trogdon, Justin G.; Nwaise, Isaac; Ekwueme, Donatus U.; Guy, Gery P.; Orenstein, Diane

2016-01-01

Background Cancer is one of the top five most costly diseases in the United States and leads to substantial work loss. Nevertheless, limited state-level estimates of cancer absenteeism costs have been published. Methods In analyses of data from the 2004–2008 Medical Expenditure Panel Survey, the 2004 National Nursing Home Survey, the U.S. Census Bureau for 2008, and the 2009 Current Population Survey, we used regression modeling to estimate annual state-level absenteeism costs attributable to cancer from 2004 to 2008. Results We estimated that the state-level median number of days of absenteeism per year among employed cancer patients was 6.1 days and that annual state-level cancer absenteeism costs ranged from $14.9 million to $915.9 million (median = $115.9 million) across states in 2010 dollars. Absenteeism costs are approximately 6.5% of the costs of premature cancer mortality. Conclusions The results from this study suggest that lost productivity attributable to cancer is a substantial cost to employees and employers and contributes to estimates of the overall impact of cancer in a state population. PMID:23969498

The Association between State Policy Environments and Self-Rated Health Disparities for Sexual Minorities in the United States

Directory of Open Access Journals (Sweden)

Gilbert Gonzales

2018-06-01

Full Text Available A large body of research has documented disparities in health and access to care for lesbian, gay, and bisexual (LGB people in the United States. Less research has examined how the level of legal protection afforded to LGB people (the state policy environment affects health disparities for sexual minorities. This study used data on 14,687 sexual minority adults and 490,071 heterosexual adults from the 2014–2016 Behavioral Risk Factor Surveillance System to document differences in health. Unadjusted state-specific prevalence estimates and multivariable logistic regression models were used to compare poor/fair self-rated health by gender, sexual minority status, and state policy environments (comprehensive versus limited protections for LGB people. We found disparities in self-rated health between sexual minority adults and heterosexual adults in most states. On average, sexual minority men in states with limited protections and sexual minority women in states with either comprehensive or limited protections were more likely to report poor/fair self-rated health compared to their heterosexual counterparts. This study adds new findings on the association between state policy environments and self-rated health for sexual minorities and suggests differences in this relationship by gender. The associations and impacts of state-specific policies affecting LGB populations may vary by gender, as well as other intersectional identities.

Algorithm of the managing systems state estimation

Directory of Open Access Journals (Sweden)

Skubilin M. D.

2010-02-01

Full Text Available The possibility of an electronic estimation of automatic and automated managing systems state is analyzed. An estimation of a current state (functional readiness of technical equipment and person-operator as integrated system allows to take operatively adequate measures on an exception and-or minimisation of consequences of system’s transition in a supernumerary state. The offered method is universal enough and can be recommended for normalisation of situations on transport, mainly in aircraft.

Comparison of direct and indirect methods of estimating health state utilities for resource allocation: review and empirical analysis.

Science.gov (United States)

Arnold, David; Girling, Alan; Stevens, Andrew; Lilford, Richard

2009-07-22

Utilities (values representing preferences) for healthcare priority setting are typically obtained indirectly by asking patients to fill in a quality of life questionnaire and then converting the results to a utility using population values. We compared such utilities with those obtained directly from patients or the public. Review of studies providing both a direct and indirect utility estimate. Papers reporting comparisons of utilities obtained directly (standard gamble or time tradeoff) or indirectly (European quality of life 5D [EQ-5D], short form 6D [SF-6D], or health utilities index [HUI]) from the same patient. PubMed and Tufts database of utilities. Sign test for paired comparisons between direct and indirect utilities; least squares regression to describe average relations between the different methods. Mean utility scores (or median if means unavailable) for each method, and differences in mean (median) scores between direct and indirect methods. We found 32 studies yielding 83 instances where direct and indirect methods could be compared for health states experienced by adults. The direct methods used were standard gamble in 57 cases and time trade off in 60(34 used both); the indirect methods were EQ-5D (67 cases), SF-6D (13), HUI-2 (5), and HUI-3 (37). Mean utility values were 0.81 (standard gamble) and 0.77 (time tradeoff) for the direct methods; for the indirect methods: 0.59(EQ-5D), 0.63 (SF-6D), 0.75 (HUI-2) and 0.68 (HUI-3). Direct methods of estimating utilities tend to result in higher health ratings than the more widely used indirect methods, and the difference can be substantial.Use of indirect methods could have important implications for decisions about resource allocation: for example, non-lifesaving treatments are relatively more favoured in comparison with lifesaving interventions than when using direct methods.

Approximation to estimation of critical state

International Nuclear Information System (INIS)

Orso, Jose A.; Rosario, Universidad Nacional

2011-01-01

The position of the control rod for the critical state of the nuclear reactor depends on several factors; including, but not limited to the temperature and configuration of the fuel elements inside the core. Therefore, the position can not be known in advance. In this paper theoretical estimations are developed to obtain an equation that allows calculating the position of the control rod for the critical state (approximation to critical) of the nuclear reactor RA-4; and will be used to create a software performing the estimation by entering the count rate of the reactor pulse channel and the length obtained from the control rod (in cm). For the final estimation of the approximation to critical state, a function obtained experimentally indicating control rods reactivity according to the function of their position is used, work is done mathematically to obtain a linear function, which gets the length of the control rod, which has to be removed to get the reactor in critical position. (author) [es

Health Parameter Estimation with Second-Order Sliding Mode Observer for a Turbofan Engine

Directory of Open Access Journals (Sweden)

Xiaodong Chang

2017-07-01

Full Text Available In this paper the problem of health parameter estimation in an aero-engine is investigated by using an unknown input observer-based methodology, implemented by a second-order sliding mode observer (SOSMO. Unlike the conventional state estimator-based schemes, such as Kalman filters (KF and sliding mode observers (SMO, the proposed scheme uses a “reconstruction signal” to estimate health parameters modeled as artificial inputs, and is not only applicable to long-time health degradation, but reacts much quicker in handling abrupt fault cases. In view of the inevitable uncertainties in engine dynamics and modeling, a weighting matrix is created to minimize such effect on estimation by using the linear matrix inequalities (LMI. A big step toward uncertainty modeling is taken compared with our previous SMO-based work, in that uncertainties are considered in a more practical form. Moreover, to avoid chattering in sliding modes, the super-twisting algorithm (STA is employed in observer design. Various simulations are carried out, based on the comparisons between the KF-based scheme, the SMO-based scheme in our earlier research, and the proposed method. The results consistently demonstrate the capabilities and advantages of the proposed approach in health parameter estimation.

A quick on-line state of health estimation method for Li-ion battery with incremental capacity curves processed by Gaussian filter

Science.gov (United States)

Li, Yi; Abdel-Monem, Mohamed; Gopalakrishnan, Rahul; Berecibar, Maitane; Nanini-Maury, Elise; Omar, Noshin; van den Bossche, Peter; Van Mierlo, Joeri

2018-01-01

This paper proposes an advanced state of health (SoH) estimation method for high energy NMC lithium-ion batteries based on the incremental capacity (IC) analysis. IC curves are used due to their ability of detect and quantify battery degradation mechanism. A simple and robust smoothing method is proposed based on Gaussian filter to reduce the noise on IC curves, the signatures associated with battery ageing can therefore be accurately identified. A linear regression relationship is found between the battery capacity with the positions of features of interest (FOIs) on IC curves. Results show that the developed SoH estimation function from one single battery cell is able to evaluate the SoH of other batteries cycled under different cycling depth with less than 2.5% maximum errors, which proves the robustness of the proposed method on SoH estimation. With this technique, partial charging voltage curves can be used for SoH estimation and the testing time can be therefore largely reduced. This method shows great potential to be applied in reality, as it only requires static charging curves and can be easily implemented in battery management system (BMS).

A comparison of prevalence estimates for selected health indicators and chronic diseases or conditions from the Behavioral Risk Factor Surveillance System, the National Health Interview Survey, and the National Health and Nutrition Examination Survey, 2007-2008.

Science.gov (United States)

Li, Chaoyang; Balluz, Lina S; Ford, Earl S; Okoro, Catherine A; Zhao, Guixiang; Pierannunzi, Carol

2012-06-01

To compare the prevalence estimates of selected health indicators and chronic diseases or conditions among three national health surveys in the United States. Data from adults aged 18 years or older who participated in the Behavioral Risk Factor Surveillance System (BRFSS) in 2007 and 2008 (n=807,524), the National Health Interview Survey (NHIS) in 2007 and 2008 (n=44,262), and the National Health and Nutrition Examination Survey (NHANES) during 2007 and 2008 (n=5871) were analyzed. The prevalence estimates of current smoking, obesity, hypertension, and no health insurance were similar across the three surveys, with absolute differences ranging from 0.7% to 3.9% (relative differences: 2.3% to 20.2%). The prevalence estimate of poor or fair health from BRFSS was similar to that from NHANES, but higher than that from NHIS. The prevalence estimates of diabetes, coronary heart disease, and stroke were similar across the three surveys, with absolute differences ranging from 0.0% to 0.8% (relative differences: 0.2% to 17.1%). While the BRFSS continues to provide invaluable health information at state and local level, it is reassuring to observe consistency in the prevalence estimates of key health indicators of similar caliber between BRFSS and other national surveys. Published by Elsevier Inc.

Distributed Dynamic State Estimation with Extended Kalman Filter

Energy Technology Data Exchange (ETDEWEB)

Du, Pengwei; Huang, Zhenyu; Sun, Yannan; Diao, Ruisheng; Kalsi, Karanjit; Anderson, Kevin K.; Li, Yulan; Lee, Barry

2011-08-04

Increasing complexity associated with large-scale renewable resources and novel smart-grid technologies necessitates real-time monitoring and control. Our previous work applied the extended Kalman filter (EKF) with the use of phasor measurement data (PMU) for dynamic state estimation. However, high computation complexity creates significant challenges for real-time applications. In this paper, the problem of distributed dynamic state estimation is investigated. One domain decomposition method is proposed to utilize decentralized computing resources. The performance of distributed dynamic state estimation is tested on a 16-machine, 68-bus test system.

Lithium-ion battery state of function estimation based on fuzzy logic algorithm with associated variables

Science.gov (United States)

Gan, L.; Yang, F.; Shi, Y. F.; He, H. L.

2017-11-01

Many occasions related to batteries demand to know how much continuous and instantaneous power can batteries provide such as the rapidly developing electric vehicles. As the large-scale applications of lithium-ion batteries, lithium-ion batteries are used to be our research object. Many experiments are designed to get the lithium-ion battery parameters to ensure the relevance and reliability of the estimation. To evaluate the continuous and instantaneous load capability of a battery called state-of-function (SOF), this paper proposes a fuzzy logic algorithm based on battery state-of-charge(SOC), state-of-health(SOH) and C-rate parameters. Simulation and experimental results indicate that the proposed approach is suitable for battery SOF estimation.

Traffic State Estimation Using Connected Vehicles and Stationary Detectors

Directory of Open Access Journals (Sweden)

Ellen F. Grumert

2018-01-01

Full Text Available Real-time traffic state estimation is of importance for efficient traffic management. This is especially the case for traffic management systems that require fast detection of changes in the traffic conditions in order to apply an effective control measure. In this paper, we propose a method for estimating the traffic state and speed and density, by using connected vehicles combined with stationary detectors. The aim is to allow fast and accurate estimation of changes in the traffic conditions. The proposed method does only require information about the speed and the position of connected vehicles and can make use of sparsely located stationary detectors to limit the dependence on the infrastructure equipment. An evaluation of the proposed method is carried out by microscopic traffic simulation. The traffic state estimated using the proposed method is compared to the true simulated traffic state. Further, the density estimates are compared to density estimates from one detector-based method, one combined method, and one connected-vehicle-based method. The results of the study show that the proposed method is a promising alternative for estimating the traffic state in traffic management applications.

Estimated Human and Economic Burden of Four Major Adult Vaccine-Preventable Diseases in the United States, 2013

OpenAIRE

McLaughlin, John M.; McGinnis, Justin J.; Tan, Litjen; Mercatante, Annette; Fortuna, Joseph

2015-01-01

Low uptake of routinely recommended adult immunizations is a public health concern. Using data from the peer-reviewed literature, government disease-surveillance programs, and the US Census, we developed a customizable model to estimate human and economic burden caused by four major adult vaccine-preventable diseases (VPD) in 2013 in the United States, and for each US state individually. To estimate the number of cases for each adult VPD for a given population, we multiplied age-specific inci...

State Estimation-based Transmission line parameter identification

Directory of Open Access Journals (Sweden)

Fredy Andrés Olarte Dussán

2010-01-01

Full Text Available This article presents two state-estimation-based algorithms for identifying transmission line parameters. The identification technique used simultaneous state-parameter estimation on an artificial power system composed of several copies of the same transmission line, using measurements at different points in time. The first algorithm used active and reactive power measurements at both ends of the line. The second method used synchronised phasor voltage and current measurements at both ends. The algorithms were tested in simulated conditions on the 30-node IEEE test system. All line parameters for this system were estimated with errors below 1%.

U.S. Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States

Data.gov (United States)

U.S. Department of Health & Human Services — 2010-2015. U.S. Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates are based on the 2010 Census...

Multistage optimal PMU placement for hybrid state estimation

DEFF Research Database (Denmark)

Hazra, J.; Das, Kaushik; Roy, B. K. S.

2017-01-01

placed by the proposed method are used in developing a hybrid state estimator (HSE). The HSE estimates the voltage phasor at all the buses of a power system with a limited numbers of PMUs in steady state as well as in the presence of disturbances even in that part of network which is unobservable through...... PMUs. Performance of the proposed phased installation scheme for HSE is evaluated on the number of standard test system and the simulation results shows an improvement in the accuracy of the estimated states as compared to the existing methods in the literature....

Transitions in state public health law: comparative analysis of state public health law reform following the Turning Point Model State Public Health Act.

Science.gov (United States)

Meier, Benjamin Mason; Hodge, James G; Gebbie, Kristine M

2009-03-01

Given the public health importance of law modernization, we undertook a comparative analysis of policy efforts in 4 states (Alaska, South Carolina, Wisconsin, and Nebraska) that have considered public health law reform based on the Turning Point Model State Public Health Act. Through national legislative tracking and state case studies, we investigated how the Turning Point Act's model legal language has been considered for incorporation into state law and analyzed key facilitating and inhibiting factors for public health law reform. Our findings provide the practice community with a research base to facilitate further law reform and inform future scholarship on the role of law as a determinant of the public's health.

Effect of Smart Meter Measurements Data On Distribution State Estimation

DEFF Research Database (Denmark)

Pokhrel, Basanta Raj; Nainar, Karthikeyan; Bak-Jensen, Birgitte

2018-01-01

Smart distribution grids with renewable energy based generators and demand response resources (DRR) requires accurate state estimators for real time control. Distribution grid state estimators are normally based on accumulated smart meter measurements. However, increase of measurements in the phy......Smart distribution grids with renewable energy based generators and demand response resources (DRR) requires accurate state estimators for real time control. Distribution grid state estimators are normally based on accumulated smart meter measurements. However, increase of measurements...... in the physical grid can enforce significant stress not only on the communication infrastructure but also in the control algorithms. This paper aims to propose a methodology to analyze needed real time smart meter data from low voltage distribution grids and their applicability in distribution state estimation...

Optimal state estimation theory applied to safeguards accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.

1977-01-01

This paper presents a unified theory for the application of modern state estimation techniques to nuclear material accountability. First a summary of the current MUF/LEMUF approach is detailed. It is shown that when inventory measurement error is large in comparison to transfer measurement error, improved estimates of the losses can be achieved using the cumulative summation technique. However, the optimal estimator is shown to be the Kalman filter. An enhancement of the retrospective estimation of losses can be achieved using linear smoothing. State space models are developed for a mixed oxide fuel fabrication facility and examples are presented

Differences Between Individual and Societal Health State Valuations

Science.gov (United States)

Chapman, Benjamin P.; Franks, Peter; Duberstein, Paul R.; Jerant, Anthony

2009-01-01

Objective The concept of “adaptation” has been proposed to account for differences between individual and societal valuations of specific health states in patients with chronic diseases. Little is known about psychological indices of adaptational capacity, which may predict differences in individual and societal valuations of health states. We investigated whether such differences were partially explained by personality traits in chronic disease patients. Research Design Analysis of baseline data of randomized controlled trial. Subjects Three hundred seventy patients with chronic disease. Measures The NEO-five factor inventory measure of personality, EuroQoL-5D (EQ-5D) societal-based, and the EQ visual analogue scale individually-based measures of health valuation. Results Regression analyses modeled Dev, a measure of difference between the EQ-Visual Analogue Scale and EQ-5D, as a function of personality traits, sociodemographic factors, and chronic diseases. Individual valuations were significantly and clinically higher than societal valuations among patients in the second and third quartile of conscientiousness (Dev = 0.08, P = 0.01); among covariates, only depression (Dev = -0.04, P = 0.046) was also associated with Dev. Conclusion Compared with societal valuations of a given health state, persons at higher quartiles of conscientiousness report less disutility associated with poor health. The effect is roughly twice that of some estimates of minimally important clinical differences on the EQ-5D and of depression. Although useful at the aggregate level, societal preference measures may systematically undervalue the health states of more conscientious individuals. Future work should examine the impact this has on individual patient outcome evaluation in clinical studies. PMID:19543121

Mapping to Estimate Health-State Utility from Non-Preference-Based Outcome Measures: An ISPOR Good Practices for Outcomes Research Task Force Report.

Science.gov (United States)

Wailoo, Allan J; Hernandez-Alava, Monica; Manca, Andrea; Mejia, Aurelio; Ray, Joshua; Crawford, Bruce; Botteman, Marc; Busschbach, Jan

2017-01-01

Economic evaluation conducted in terms of cost per quality-adjusted life-year (QALY) provides information that decision makers find useful in many parts of the world. Ideally, clinical studies designed to assess the effectiveness of health technologies would include outcome measures that are directly linked to health utility to calculate QALYs. Often this does not happen, and even when it does, clinical studies may be insufficient for a cost-utility assessment. Mapping can solve this problem. It uses an additional data set to estimate the relationship between outcomes measured in clinical studies and health utility. This bridges the evidence gap between available evidence on the effect of a health technology in one metric and the requirement for decision makers to express it in a different one (QALYs). In 2014, ISPOR established a Good Practices for Outcome Research Task Force for mapping studies. This task force report provides recommendations to analysts undertaking mapping studies, those that use the results in cost-utility analysis, and those that need to critically review such studies. The recommendations cover all areas of mapping practice: the selection of data sets for the mapping estimation, model selection and performance assessment, reporting standards, and the use of results including the appropriate reflection of variability and uncertainty. This report is unique because it takes an international perspective, is comprehensive in its coverage of the aspects of mapping practice, and reflects the current state of the art. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A wedge-based approach to estimating health co-benefits of climate change mitigation activities in the United States

Energy Technology Data Exchange (ETDEWEB)

Balbus, John M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Greenblatt, Jeffery B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chari, Ramya [Rand Corporation, Santa Monica, CA (United States); Millstein, Dev [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ebi, Kristie L. [ClimAdapt, Inc., Los Altos, CA (United States)

2015-02-01

While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM2.5) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO₂) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM2.5 would yield economic benefits in the range of $6 to $14 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $93 per metric ton of CO₂ in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.

Dynamic state estimation assisted power system monitoring and protection

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Cui, Yinan

The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the

Minimax estimation of qubit states with Bures risk

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Acharya, Anirudh; Guţă, Mădălin

2018-04-01

The central problem of quantum statistics is to devise measurement schemes for the estimation of an unknown state, given an ensemble of n independent identically prepared systems. For locally quadratic loss functions, the risk of standard procedures has the usual scaling of 1/n. However, it has been noticed that for fidelity based metrics such as the Bures distance, the risk of conventional (non-adaptive) qubit tomography schemes scales as 1/\\sqrt{n} for states close to the boundary of the Bloch sphere. Several proposed estimators appear to improve this scaling, and our goal is to analyse the problem from the perspective of the maximum risk over all states. We propose qubit estimation strategies based on separate adaptive measurements, and collective measurements, that achieve 1/n scalings for the maximum Bures risk. The estimator involving local measurements uses a fixed fraction of the available resource n to estimate the Bloch vector direction; the length of the Bloch vector is then estimated from the remaining copies by measuring in the estimator eigenbasis. The estimator based on collective measurements uses local asymptotic normality techniques which allows us to derive upper and lower bounds to its maximum Bures risk. We also discuss how to construct a minimax optimal estimator in this setup. Finally, we consider quantum relative entropy and show that the risk of the estimator based on collective measurements achieves a rate O(n-1log n) under this loss function. Furthermore, we show that no estimator can achieve faster rates, in particular the ‘standard’ rate n ‑1.

Estimating the cost to U.S. health departments to conduct HIV surveillance.

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Shrestha, Ram K; Sansom, Stephanie L; Laffoon, Benjamin T; Farnham, Paul G; Shouse, R Luke; MacMaster, Karen; Hall, H Irene

2014-01-01

HIV case surveillance is a primary source of information for monitoring HIV burden in the United States and guiding the allocation of prevention and treatment funds. While the number of people living with HIV and the need for surveillance data have increased, little is known about the cost of surveillance. We estimated the economic cost to health departments of conducting high-quality HIV case surveillance. We collected primary data on the unit cost and quantity of resources used to operate the HIV case surveillance program in Michigan, where HIV burden (i.e., the number of HIV cases) is moderate to high (n=14,864 cases). Based on Michigan's data, we projected the expected annual HIV surveillance cost for U.S., state, local, and territorial health departments. We based our cost projection on the variation in the number of new and established cases, area-specific wages, and potential economies of scale. We estimated the annual total HIV surveillance cost to the Michigan health department to be $1,286,524 ($87/case), the annual total cost of new cases to be $108,657 ($133/case), and the annual total cost of established cases to be $1,177,867 ($84/case). Our projected median annual HIV surveillance cost per health department ranged from $210,600 in low-HIV burden sites to $1,835,000 in high-HIV burden sites. Our analysis shows that a systematic approach to costing HIV surveillance at the health department level is feasible. For HIV surveillance, a substantial portion of total surveillance costs is attributable to maintaining established cases.

Fuzzy filter for state estimation of a glucoregulatory system.

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Trajanoski, Z; Wach, P

1996-08-01

A filter based on fuzzy logic for state estimation of a glucoregulatory system is presented. A published non-linear model for the dynamics of glucose and its hormonal control including a single glucose compartment, five insulin compartments and a glucagon compartment was used for simulation. The simulated data were corrupted by an additive white noise with zero mean and a coefficient of variation (CV) of between 2 and 20% and then submitted to the state estimation procedure using a fuzzy filter (FF). The performance of the FF was compared with an extended Kalman filter (EKF) for state estimation. Both the FF and the EKF were evaluated in the following cases: (a) five state variables are measurable; three plasma variables are measurable; only plasma glucose is measurable; (b) for different measurement noise levels (CV of 2-20%); and (c) a mismatch between the glucoregulatory system and the given mathematical model (uncertain or approximate model). In contrast to the FF, in the case of approximate model of the glucose system, the EKF failed to achieve useful state estimation. Moreover, the performance of the FF was independent of the noise level. In conclusion, the FF approach is a viable alternative for state estimation in a noisy environment and with an uncertain mathematical model of the glucoregulatory system.

Estimation methods for nonlinear state-space models in ecology

DEFF Research Database (Denmark)

Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

2011-01-01

The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

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Xiaoxue Feng

2014-11-01

Full Text Available Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS, which gets better filtering performance than NILS without constraint.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

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Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-01-01

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

Constrained state estimation for individual localization in wireless body sensor networks.

Science.gov (United States)

Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-11-10

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint.

Inconsistencies Exist in National Estimates of Eye Care Services Utilization in the United States

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Fernando A. Wilson

2015-01-01

Full Text Available Background. There are limited research and substantial uncertainty about the level of eye care utilization in the United States. Objectives. Our study estimated eye care utilization using, to our knowledge, every known nationally representative, publicly available database with information on office-based optometry or ophthalmology services. Research Design. We analyzed the following national databases to estimate eye care utilization: the Medical Expenditure Panel Survey (MEPS, National Health Interview Survey (NHIS, Joint Canada/US Survey of Health (JCUSH, Behavioral Risk Factor Surveillance System (BRFSS, and the National Ambulatory Medical Care Survey (NAMCS. Subjects. US adults aged 18 and older. Measures. Self-reported utilization of eye care services. Results. The weighted number of adults seeing or talking with any eye doctor ranges from 87.9 million to 99.5 million, and the number of visits annually ranges from 72.9 million to 142.6 million. There were an estimated 17.2 million optometry visits and 55.8 million ophthalmology visits. Conclusions. The definitions and estimates of eye care services vary widely across national databases, leading to substantial differences in national estimates of eye care utilization.

Vehicle State Information Estimation with the Unscented Kalman Filter

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Hongbin Ren

2014-01-01

Full Text Available The vehicle state information plays an important role in the vehicle active safety systems; this paper proposed a new concept to estimate the instantaneous vehicle speed, yaw rate, tire forces, and tire kinemics information in real time. The estimator is based on the 3DoF vehicle model combined with the piecewise linear tire model. The estimator is realized using the unscented Kalman filter (UKF, since it is based on the unscented transfer technique and considers high order terms during the measurement and update stage. The numerical simulations are carried out to further investigate the performance of the estimator under high friction and low friction road conditions in the MATLAB/Simulink combined with the Carsim environment. The simulation results are compared with the numerical results from Carsim software, which indicate that UKF can estimate the vehicle state information accurately and in real time; the proposed estimation will provide the necessary and reliable state information to the vehicle controller in the future.

Exponentially convergent state estimation for delayed switched recurrent neural networks.

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Ahn, Choon Ki

2011-11-01

This paper deals with the delay-dependent exponentially convergent state estimation problem for delayed switched neural networks. A set of delay-dependent criteria is derived under which the resulting estimation error system is exponentially stable. It is shown that the gain matrix of the proposed state estimator is characterised in terms of the solution to a set of linear matrix inequalities (LMIs), which can be checked readily by using some standard numerical packages. An illustrative example is given to demonstrate the effectiveness of the proposed state estimator.

Information geometry of density matrices and state estimation

International Nuclear Information System (INIS)

Brody, Dorje C

2011-01-01

Given a pure state vector |x) and a density matrix ρ-hat, the function p(x|ρ-hat)= defines a probability density on the space of pure states parameterised by density matrices. The associated Fisher-Rao information measure is used to define a unitary invariant Riemannian metric on the space of density matrices. An alternative derivation of the metric, based on square-root density matrices and trace norms, is provided. This is applied to the problem of quantum-state estimation. In the simplest case of unitary parameter estimation, new higher-order corrections to the uncertainty relations, applicable to general mixed states, are derived. (fast track communication)

Criteria of estimation of positive health level in the long-term process of the health training of women of senior age.

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Prusik Katerina

2011-09-01

Full Text Available In the article materials of the three-year looking are utillized after the state of positive health of group of women in age 50-80 years. The method of statistical ground of adequate control indexes is shown for the estimation of bodily condition of inspected. The use of high-quality criteria is offered for the estimation of efficiency of physical exercises on the Norwegian method of walking with sticks.

Estimating annualized earthquake losses for the conterminous United States

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Jaiswal, Kishor S.; Bausch, Douglas; Chen, Rui; Bouabid, Jawhar; Seligson, Hope

2015-01-01

We make use of the most recent National Seismic Hazard Maps (the years 2008 and 2014 cycles), updated census data on population, and economic exposure estimates of general building stock to quantify annualized earthquake loss (AEL) for the conterminous United States. The AEL analyses were performed using the Federal Emergency Management Agency's (FEMA) Hazus software, which facilitated a systematic comparison of the influence of the 2014 National Seismic Hazard Maps in terms of annualized loss estimates in different parts of the country. The losses from an individual earthquake could easily exceed many tens of billions of dollars, and the long-term averaged value of losses from all earthquakes within the conterminous U.S. has been estimated to be a few billion dollars per year. This study estimated nationwide losses to be approximately $4.5 billion per year (in 2012$), roughly 80% of which can be attributed to the States of California, Oregon and Washington. We document the change in estimated AELs arising solely from the change in the assumed hazard map. The change from the 2008 map to the 2014 map results in a 10 to 20% reduction in AELs for the highly seismic States of the Western United States, whereas the reduction is even more significant for Central and Eastern United States.

Diabetes prevalence and diagnosis in US states: analysis of health surveys

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Oza Shefali

2009-09-01

Full Text Available Abstract Background Current US surveillance data provide estimates of diabetes using laboratory tests at the national level as well as self-reported data at the state level. Self-reported diabetes prevalence may be biased because respondents may not be aware of their risk status. Our objective was to estimate the prevalence of diagnosed and undiagnosed diabetes by state. Methods We estimated undiagnosed diabetes prevalence as a function of a set of health system and sociodemographic variables using a logistic regression in the National Health and Nutrition Examination Survey (2003-2006. We applied this relationship to identical variables from the Behavioral Risk Factor Surveillance System (2003-2007 to estimate state-level prevalence of undiagnosed diabetes by age group and sex. We assumed that those who report being diagnosed with diabetes in both surveys are truly diabetic. Results The prevalence of diabetes in the U.S. was 13.7% among men and 11.7% among women ≥ 30 years. Age-standardized diabetes prevalence was highest in Mississippi, West Virginia, Louisiana, Texas, South Carolina, Alabama, and Georgia (15.8 to 16.6% for men and 12.4 to 14.8% for women. Vermont, Minnesota, Montana, and Colorado had the lowest prevalence (11.0 to 12.2% for men and 7.3 to 8.4% for women. Men in all states had higher diabetes prevalence than women. The absolute prevalence of undiagnosed diabetes, as a percent of total population, was highest in New Mexico, Texas, Florida, and California (3.5 to 3.7 percentage points and lowest in Montana, Oklahoma, Oregon, Alaska, Vermont, Utah, Washington, and Hawaii (2.1 to 3 percentage points. Among those with no established diabetes diagnosis, being obese, being Hispanic, not having insurance and being ≥ 60 years old were significantly associated with a higher risk of having undiagnosed diabetes. Conclusion Diabetes prevalence is highest in the Southern and Appalachian states and lowest in the Midwest and the Northeast

Steady-state evoked potentials possibilities for mental-state estimation

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Junker, Andrew M.; Schnurer, John H.; Ingle, David F.; Downey, Craig W.

1988-01-01

The use of the human steady-state evoked potential (SSEP) as a possible measure of mental-state estimation is explored. A method for evoking a visual response to a sum-of-ten sine waves is presented. This approach provides simultaneous multiple frequency measurements of the human EEG to the evoking stimulus in terms of describing functions (gain and phase) and remnant spectra. Ways in which these quantities vary with the addition of performance tasks (manual tracking, grammatical reasoning, and decision making) are presented. Models of the describing function measures can be formulated using systems engineering technology. Relationships between model parameters and performance scores during manual tracking are discussed. Problems of unresponsiveness and lack of repeatability of subject responses are addressed in terms of a need for loop closure of the SSEP. A technique to achieve loop closure using a lock-in amplifier approach is presented. Results of a study designed to test the effectiveness of using feedback to consciously connect humans to their evoked response are presented. Findings indicate that conscious control of EEG is possible. Implications of these results in terms of secondary tasks for mental-state estimation and brain actuated control are addressed.

Artificial Neural Network Based State Estimators Integrated into Kalmtool

DEFF Research Database (Denmark)

Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad

2012-01-01

In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation as...

Health, United States, 2012: Men's Health

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... Mailing List Previous Reports Suggested Citation Related Sites Purchase Health, United States Behavioral Health Report Children’s ... with Internet Explorer may experience difficulties in directly accessing links to Excel files ...

Stated Preference Survey Estimating the Willingness to Pay ...

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A national stated preference survey designed to elicit household willingness to pay for reductions in impinged and entrained fish at cooling water intake structures. To improve estimation of environmental benefits estimation

Power system dynamic state estimation using prediction based evolutionary technique

International Nuclear Information System (INIS)

Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

2016-01-01

In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

Health effects estimation for contaminated properties

International Nuclear Information System (INIS)

Marks, S.; Denham, D.H.; Cross, F.T.; Kennedy, W.E. Jr.

1984-05-01

As part of an overall remedial action program to evaluate the need for and institute actions designed to minimize health hazards from inactive tailings piles and from displaced tailings, methods for estimating health effects from tailings were developed and applied to the Salt Lake City area. 2 references, 2 tables

State estimation for wave energy converters

Energy Technology Data Exchange (ETDEWEB)

Bacelli, Giorgio; Coe, Ryan Geoffrey

2017-04-01

This report gives a brief discussion and examples on the topic of state estimation for wave energy converters (WECs). These methods are intended for use to enable real-time closed loop control of WECs.

Efficiency of health care system at the sub-state level in Madhya Pradesh, India.

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Purohit, Brijesh C

2010-01-01

This paper attempts a sub-state-level analysis of health system for a low-income Indian state, namely, Madhya Pradesh. The objective of our study is to establish efficiency parameters that may help health policy makers to improve district-level and thus state-level health system performance. It provides an idealized yardstick to evaluate the performance of the health sector by using stochastic frontier technique. The study was carried out in two stages of estimation, and our results suggest that life expectancy in the Indian state could be enhanced considerably by correcting the factors that are adversely influencing sub-state-level health system efficiency. Our results indicate that main factors within the health system for discrepancy in interdistrict performance are inequitable distribution of supplies, availability of skilled attention at birth, and inadequate staffing relative to patient load of rural population at primary health centers. Overcoming these factors through additional resources in the deficient districts, mobilized partly from grants in aid and partly from patient welfare societies, may help the state to improve life expectancy speedily and more equitably. Besides the direct inputs from the health sector, a more conducive environment for gender development, reducing inequality in opportunities for women in health, education and other rights may provide the necessary impetus towards reducing maternal morbidity and mortality and add to overall life expectancy in the state.

Joint estimation over multiple individuals improves behavioural state inference from animal movement data.

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Jonsen, Ian

2016-02-08

State-space models provide a powerful way to scale up inference of movement behaviours from individuals to populations when the inference is made across multiple individuals. Here, I show how a joint estimation approach that assumes individuals share identical movement parameters can lead to improved inference of behavioural states associated with different movement processes. I use simulated movement paths with known behavioural states to compare estimation error between nonhierarchical and joint estimation formulations of an otherwise identical state-space model. Behavioural state estimation error was strongly affected by the degree of similarity between movement patterns characterising the behavioural states, with less error when movements were strongly dissimilar between states. The joint estimation model improved behavioural state estimation relative to the nonhierarchical model for simulated data with heavy-tailed Argos location errors. When applied to Argos telemetry datasets from 10 Weddell seals, the nonhierarchical model estimated highly uncertain behavioural state switching probabilities for most individuals whereas the joint estimation model yielded substantially less uncertainty. The joint estimation model better resolved the behavioural state sequences across all seals. Hierarchical or joint estimation models should be the preferred choice for estimating behavioural states from animal movement data, especially when location data are error-prone.

Deaths Attributable to Diabetes in the United States: Comparison of Data Sources and Estimation Approaches.

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Stokes, Andrew; Preston, Samuel H

2017-01-01

The goal of this research was to identify the fraction of deaths attributable to diabetes in the United States. We estimated population attributable fractions (PAF) for cohorts aged 30-84 who were surveyed in the National Health Interview Survey (NHIS) between 1997 and 2009 (N = 282,322) and in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2010 (N = 21,814). Cohort members were followed prospectively for mortality through 2011. We identified diabetes status using self-reported diagnoses in both NHIS and NHANES and using HbA1c in NHANES. Hazard ratios associated with diabetes were estimated using Cox model adjusted for age, sex, race/ethnicity, educational attainment, and smoking status. We found a high degree of consistency between data sets and definitions of diabetes in the hazard ratios, estimates of diabetes prevalence, and estimates of the proportion of deaths attributable to diabetes. The proportion of deaths attributable to diabetes was estimated to be 11.5% using self-reports in NHIS, 11.7% using self-reports in NHANES, and 11.8% using HbA1c in NHANES. Among the sub-groups that we examined, the PAF was highest among obese persons at 19.4%. The proportion of deaths in which diabetes was assigned as the underlying cause of death (3.3-3.7%) severely understated the contribution of diabetes to mortality in the United States. Diabetes may represent a more prominent factor in American mortality than is commonly appreciated, reinforcing the need for robust population-level interventions aimed at diabetes prevention and care.

Deaths Attributable to Diabetes in the United States: Comparison of Data Sources and Estimation Approaches.

Directory of Open Access Journals (Sweden)

Andrew Stokes

Full Text Available The goal of this research was to identify the fraction of deaths attributable to diabetes in the United States.We estimated population attributable fractions (PAF for cohorts aged 30-84 who were surveyed in the National Health Interview Survey (NHIS between 1997 and 2009 (N = 282,322 and in the National Health and Nutrition Examination Survey (NHANES between 1999 and 2010 (N = 21,814. Cohort members were followed prospectively for mortality through 2011. We identified diabetes status using self-reported diagnoses in both NHIS and NHANES and using HbA1c in NHANES. Hazard ratios associated with diabetes were estimated using Cox model adjusted for age, sex, race/ethnicity, educational attainment, and smoking status.We found a high degree of consistency between data sets and definitions of diabetes in the hazard ratios, estimates of diabetes prevalence, and estimates of the proportion of deaths attributable to diabetes. The proportion of deaths attributable to diabetes was estimated to be 11.5% using self-reports in NHIS, 11.7% using self-reports in NHANES, and 11.8% using HbA1c in NHANES. Among the sub-groups that we examined, the PAF was highest among obese persons at 19.4%. The proportion of deaths in which diabetes was assigned as the underlying cause of death (3.3-3.7% severely understated the contribution of diabetes to mortality in the United States.Diabetes may represent a more prominent factor in American mortality than is commonly appreciated, reinforcing the need for robust population-level interventions aimed at diabetes prevention and care.

Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

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Campbell, D A; Chkrebtii, O

2013-12-01

Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

Air quality and human health impacts of grasslands and shrublands in the United States

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Gopalakrishnan, Varsha; Hirabayashi, Satoshi; Ziv, Guy; Bakshi, Bhavik R.

2018-06-01

Vegetation including canopy, grasslands, and shrublands can directly sequester pollutants onto the plant surface, resulting in an improvement in air quality. Until now, several studies have estimated the pollution removal capacity of canopy cover at the level of a county, but no such work exists for grasslands and shrublands. This work quantifies the air pollution removal capacity of grasslands and shrublands at the county-level in the United States and estimates the human health benefits associated with pollution removal using the i-Tree Eco model. Sequestration of pollutants is estimated based on the Leaf Area Index (LAI) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) derived dataset estimates of LAI and the percentage land cover obtained from the National Land Cover Database (NLCD) for the year 2010. Calculation of pollution removal capacity using local environmental data indicates that grasslands and shrublands remove a total of 6.42 million tonnes of air pollutants in the United States and the associated monetary benefits total 268 million. Human health impacts and associated monetary value due to pollution removal was observed to be significantly high in urban areas indicating that grasslands and shrublands are equally critical as canopy in improving air quality and human health in urban regions.

Female Genital Mutilation/Cutting in the United States: Updated Estimates of Women and Girls at Risk, 2012.

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Goldberg, Howard; Stupp, Paul; Okoroh, Ekwutosi; Besera, Ghenet; Goodman, David; Danel, Isabella

2016-01-01

In 1996, the U.S. Congress passed legislation making female genital mutilation/cutting (FGM/C) illegal in the United States. CDC published the first estimates of the number of women and girls at risk for FGM/C in 1997. Since 2012, various constituencies have again raised concerns about the practice in the United States. We updated an earlier estimate of the number of women and girls in the United States who were at risk for FGM/C or its consequences. We estimated the number of women and girls who were at risk for undergoing FGM/C or its consequences in 2012 by applying country-specific prevalence of FGM/C to the estimated number of women and girls living in the United States who were born in that country or who lived with a parent born in that country. Approximately 513,000 women and girls in the United States were at risk for FGM/C or its consequences in 2012, which was more than three times higher than the earlier estimate, based on 1990 data. The increase in the number of women and girls younger than 18 years of age at risk for FGM/C was more than four times that of previous estimates. The estimated increase was wholly a result of rapid growth in the number of immigrants from FGM/C-practicing countries living in the United States and not from increases in FGM/C prevalence in those countries. Scientifically valid information regarding whether women or their daughters have actually undergone FGM/C and related information that can contribute to efforts to prevent the practice in the United States and provide needed health services to women who have undergone FGM/C are needed.

Event-Based $H_\\infty $ State Estimation for Time-Varying Stochastic Dynamical Networks With State- and Disturbance-Dependent Noises.

Science.gov (United States)

Sheng, Li; Wang, Zidong; Zou, Lei; Alsaadi, Fuad E

2017-10-01

In this paper, the event-based finite-horizon H ∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with state- and disturbance-dependent noises [also called (x,v) -dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted only when certain conditions are satisfied. The purpose of the problem addressed is to design a time-varying state estimator in order to estimate the network states through available output measurements. By employing the completing-the-square technique and the stochastic analysis approach, sufficient conditions are established to ensure that the error dynamics of the state estimation satisfies a prescribed H ∞ performance constraint over a finite horizon. The desired estimator parameters can be designed via solving coupled backward recursive Riccati difference equations. Finally, a numerical example is exploited to demonstrate the effectiveness of the developed state estimation scheme.

The State Public Health Laboratory System.

Science.gov (United States)

Inhorn, Stanley L; Astles, J Rex; Gradus, Stephen; Malmberg, Veronica; Snippes, Paula M; Wilcke, Burton W; White, Vanessa A

2010-01-01

This article describes the development since 2000 of the State Public Health Laboratory System in the United States. These state systems collectively are related to several other recent public health laboratory (PHL) initiatives. The first is the Core Functions and Capabilities of State Public Health Laboratories, a white paper that defined the basic responsibilities of the state PHL. Another is the Centers for Disease Control and Prevention National Laboratory System (NLS) initiative, the goal of which is to promote public-private collaboration to assure quality laboratory services and public health surveillance. To enhance the realization of the NLS, the Association of Public Health Laboratories (APHL) launched in 2004 a State Public Health Laboratory System Improvement Program. In the same year, APHL developed a Comprehensive Laboratory Services Survey, a tool to measure improvement through the decade to assure that essential PHL services are provided.

Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery

International Nuclear Information System (INIS)

Deng, Zhongwei; Yang, Lin; Cai, Yishan; Deng, Hao; Sun, Liu

2016-01-01

The key technology of a battery management system is to online estimate the battery states accurately and robustly. For lithium iron phosphate battery, the relationship between state of charge and open circuit voltage has a plateau region which limits the estimation accuracy of voltage-based algorithms. The open circuit voltage hysteresis requires advanced online identification algorithms to cope with the strong nonlinear battery model. The available capacity, as a crucial parameter, contributes to the state of charge and state of health estimation of battery, but it is difficult to predict due to comprehensive influence by temperature, aging and current rates. Aim at above problems, the ampere-hour counting with current correction and the dual adaptive extended Kalman filter algorithms are combined to estimate model parameters and state of charge. This combination presents the advantages of less computation burden and more robustness. Considering the influence of temperature and degradation, the data-driven algorithm namely least squares support vector machine is implemented to predict the available capacity. The state estimation and capacity prediction methods are coupled to improve the estimation accuracy at different temperatures among the lifetime of battery. The experiment results verify the proposed methods have excellent state and available capacity estimation accuracy. - Highlights: • A dual adaptive extended Kalman filter is used to estimate parameters and states. • A correction term is introduced to consider the effect of current rates. • The least square support vector machine is used to predict the available capacity. • The experiment results verify the proposed state and capacity prediction methods.

Health Utilization and Cost Impact of Childhood Constipation in the United States

NARCIS (Netherlands)

Liem, Olivia; Harman, Jeffrey; Benninga, Marc; Kelleher, Kelly; Mousa, Hayat; Di Lorenzo, Carlo

2009-01-01

Objective To estimate the total health care utilization and costs for children with constipation in the United States. Study design We analyzed data from 2 consecutive years (2003 and 2004) of the Medical Expenditure Panel Survey (MEPS), a nationally representative household survey. We identified

Estimating the mental health costs of racial discrimination

Directory of Open Access Journals (Sweden)

Amanuel Elias

2016-11-01

Full Text Available Abstract Background Racial discrimination is a pervasive social problem in several advanced countries such as the U.S., U.K., and Australia. Public health research also indicates a range of associations between exposure to racial discrimination and negative health, particularly, mental health including depression, anxiety, and post-traumatic stress disorder (PTSD. However, the direct negative health impact of racial discrimination has not been costed so far although economists have previously estimated indirect non-health related productivity costs. In this study, we estimate the burden of disease due to exposure to racial discrimination and measure the cost of this exposure. Methods Using prevalence surveys and data on the association of racial discrimination with health outcomes from a global meta-analysis, we apply a cost of illness method to measure the impact of racial discrimination. This estimate indicates the direct health cost attributable to racial discrimination and we convert the estimates to monetary values based on conventional parameters. Results Racial discrimination costs the Australian economy 235,452 in disability adjusted life years lost, equivalent to $37.9 billion per annum, roughly 3.02% of annual gross domestic product (GDP over 2001–11, indicating a sizeable loss for the economy. Conclusion Substantial cost is incurred due to increased prevalence of racial discrimination as a result of its association with negative health outcomes (e.g. depression, anxiety and PTSD. This implies that potentially significant cost savings can be made through measures that target racial discrimination. Our research contributes to the debate on the social impact of racial discrimination, with implications for policies and efforts addressing it.

Vision Aided State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders

2007-01-01

This paper presents the design and verification of a state estimator for a helicopter based slung load system. The estimator is designed to augment the IMU driven estimator found in many helicopter UAV s and uses vision based updates only. The process model used for the estimator is a simple 4...

WTP for a QALY and health states: More money for severer health states?

Science.gov (United States)

Shiroiwa, Takeru; Igarashi, Ataru; Fukuda, Takashi; Ikeda, Shunya

2013-01-01

In economic evaluation, cost per quality-adjusted life year (QALY) is generally used as an indicator for cost-effectiveness. Although JPY 5 million to 6 million (USD 60, 000 to 75,000) per QALY is frequently referred to as a threshold in Japan, do all QALYs have the same monetary value? To examine the relationship between severity of health status and monetary value of a QALY, we obtained willingness to pay (WTP) values for one additional QALY in eight patterns of health states. We randomly sampled approximately 2,400 respondents from an online panel. To avoid misunderstanding, we randomly allocated respondents to one of 16 questionnaires, with 250 responses expected for each pattern. After respondents were asked whether they wanted to purchase the treatment, double-bounded dichotomous choice method was used to obtain WTP values. The results clearly show that the WTP per QALY is higher for worse health states than for better health states. The slope was about JPY -1 million per 0.1 utility score increase. The mean and median WTP values per QALY for 16 health states were JPY 5 million, consistent with our previous survey. For respondents who wanted to purchase the treatment, WTP values were significantly correlated with household income. This survey shows that QALY based on the EQ-5D does not necessarily have the same monetary value. The WTP per QALY should range from JPY 2 million (USD 20,000) to JPY 8 million (USD 80,000), corresponding to the severity of health states.

Estimation of pump operational state with model-based methods

International Nuclear Information System (INIS)

Ahonen, Tero; Tamminen, Jussi; Ahola, Jero; Viholainen, Juha; Aranto, Niina; Kestilae, Juha

2010-01-01

Pumps are widely used in industry, and they account for 20% of the industrial electricity consumption. Since the speed variation is often the most energy-efficient method to control the head and flow rate of a centrifugal pump, frequency converters are used with induction motor-driven pumps. Although a frequency converter can estimate the operational state of an induction motor without external measurements, the state of a centrifugal pump or other load machine is not typically considered. The pump is, however, usually controlled on the basis of the required flow rate or output pressure. As the pump operational state can be estimated with a general model having adjustable parameters, external flow rate or pressure measurements are not necessary to determine the pump flow rate or output pressure. Hence, external measurements could be replaced with an adjustable model for the pump that uses estimates of the motor operational state. Besides control purposes, modelling the pump operation can provide useful information for energy auditing and optimization purposes. In this paper, two model-based methods for pump operation estimation are presented. Factors affecting the accuracy of the estimation methods are analyzed. The applicability of the methods is verified by laboratory measurements and tests in two pilot installations. Test results indicate that the estimation methods can be applied to the analysis and control of pump operation. The accuracy of the methods is sufficient for auditing purposes, and the methods can inform the user if the pump is driven inefficiently.

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. Parameter and state estimation

Science.gov (United States)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-09-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online parameter identification technique based on a weighted recursive least quadratic squares parameter estimator to determine the parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.

Community preferences for health states associated with intimate partner violence.

Science.gov (United States)

Wittenberg, Eve; Lichter, Erika L; Ganz, Michael L; McCloskey, Laura A

2006-08-01

One in 4 women is affected by intimate partner violence in her lifetime. This article reports on a cross-sectional survey to estimate community preferences for health states resulting from intimate partner violence. A secondary analysis was conducted of data from a convenience sample of 93 abused and 138 nonabused women (231 total) recruited for in-person interviews from hospital outpatient department waiting rooms in metropolitan Boston, Massachusetts. SF-12 data were converted to utilities to describe community-perspective preferences for health states associated with intimate partner violence. Linear regression analysis was used to explore the association between violence and utility while controlling for other health and demographic factors. Median utility for intimate partner violence was between 0.58 and 0.63 on a scale of 0 (equivalent to death) to 1.0 (equivalent to optimal health), with a range from 0.64 to 0.66 for less severe violence to 0.53 to 0.62 for more severe violence. The data do not reveal whether violence itself is responsible for lower utility or whether a constellation of factors contributes to disutility experienced by women victims of abuse. The utility of health states experienced by women exposed to intimate partner violence is substantially diminished compared with optimal health and even other health conditions. These values quantify the substantial negative health impact of the experience of intimate partner violence in terms that allow comparison across diseases. They can be used in cost-effectiveness analyses to identify the benefits and potential returns from resources allocated to violence prevention and intervention efforts.

Distributed state estimation for multi-agent based active distribution networks

NARCIS (Netherlands)

Nguyen, H.P.; Kling, W.L.

2010-01-01

Along with the large-scale implementation of distributed generators, the current distribution networks have changed gradually from passive to active operation. State estimation plays a vital role to facilitate this transition. In this paper, a suitable state estimation method for the active network

Refining estimates of public health spending as measured in national health expenditure accounts: the Canadian experience.

Science.gov (United States)

Ballinger, Geoff

2007-01-01

The recent focus on public health stemming from, among other things, severe acute respiratory syndrome and avian flu has created an imperative to refine health-spending estimates in the Canadian Health Accounts. This article presents the Canadian experience in attempting to address the challenges associated with developing the needed taxonomies for systematically capturing, measuring, and analyzing the national investment in the Canadian public health system. The first phase of this process was completed in 2005, which was a 2-year project to estimate public health spending based on a more classic definition by removing the administration component of the previously combined public health and administration category. Comparing the refined public health estimate with recent data from the Organization for Economic Cooperation and Development still positions Canada with the highest share of total health expenditure devoted to public health than any other country reporting. The article also provides an analysis of the comparability of public health estimates across jurisdictions within Canada as well as a discussion of the recommendations for ongoing improvement of public health spending estimates. The Canadian Institute for Health Information is an independent, not-for-profit organization that provides Canadians with essential statistics and analysis on the performance of the Canadian health system, the delivery of healthcare, and the health status of Canadians. The Canadian Institute for Health Information administers more than 20 databases and registries, including Canada's Health Accounts, which tracks historically 40 categories of health spending by 5 sources of finance for 13 provincial and territorial jurisdictions. Until 2005, expenditure on public health services in the Canadian Health Accounts included measures to prevent the spread of communicable disease, food and drug safety, health inspections, health promotion, community mental health programs, public

Value of Public Health Funding in Preventing Hospital Bloodstream Infections in the United States.

Science.gov (United States)

Whittington, Melanie D; Bradley, Cathy J; Atherly, Adam J; Campbell, Jonathan D; Lindrooth, Richard C

2017-11-01

To estimate the association of 1 activity of the Prevention and Public Health Fund with hospital bloodstream infections and calculate the return on investment (ROI). The activity was funded for 1 year (2013). A difference-in-differences specification evaluated hospital standardized infection ratios (SIRs) before funding allocation (years 2011 and 2012) and after funding allocation (years 2013 and 2014) in the 15 US states that received the funding compared with hospital SIRs in states that did not receive the funding. We estimated the association of the funded public health activity with SIRs for bloodstream infections. We calculated the ROI by dividing cost offsets from infections averted by the amount invested. The funding was associated with a 33% (P < .05) reduction in SIRs and an ROI of $1.10 to $11.20 per $1 invested in the year of funding allocation (2013). In 2014, after the funding stopped, significant reductions were no longer evident. This activity was associated with a reduction in bloodstream infections large enough to recoup the investment. Public health funding of carefully targeted areas may improve health and reduce health care costs.

Alternative medicine, worker health, and absenteeism in the United States.

Science.gov (United States)

Rybczynski, Kate

2017-06-01

Health related absenteeism costs an estimated $153 billion annually in the United States (Witters and Agrawal, 2011). 1 Chronic conditions (major contributors to absenteeism) are often successfully managed by Complementary and Alternative Medicine (CAM). As CAM becomes an increasingly visible component of healthcare, firms may wish to consider whether CAM therapies can help reduce illness-related absenteeism. This paper aims to extend the literature on healthcare utilization and absenteeism by exploring whether CAM treatment is associated with fewer workdays missed due to illness. Using the 2007 National Health Interview Survey (NHIS) and propensity score matching (PSM), this study estimates the relationship between visits to CAM practitioners, health, and illness-related absenteeism. In a sample of 8820 workers, the average annual number of workdays lost due to illness is 3.69. Visiting an acupuncturist correlates with lower absenteeism among men (1.182 fewer workdays missed, pabsenteeism, and many correlate with improved health. Two limitations of this study are worth noting. First, a small proportion of the sample uses CAM, limiting the generalizability of results. Second, if health conscious individuals are more likely to use CAM, then health attitudes may be contributing to lower absenteeism among the treated. Further research is needed to identify a causal relationship between CAM treatment, health, and absenteeism. Copyright © 2016 Elsevier Ltd. All rights reserved.

Online Synchrophasor-Based Dynamic State Estimation using Real-Time Digital Simulator

DEFF Research Database (Denmark)

Khazraj, Hesam; Adewole, Adeyemi Charles; Udaya, Annakkage

2018-01-01

Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real-...... using the RTDS (real-time digital simulator). The dynamic state variables of multi-machine systems are monitored and measured for the study on the transient behavior of power systems.......Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real......-time digital simulator (RTDS). The dynamic state variables of the system are the rotor angle and speed of the generators. The performance of the UKF method is tested with PMU measurements as inputs using the IEEE 14-bus test system. This test system was modeled in the RSCAD software and tested in real time...

Loving and Leaving Public Health: Predictors of Intentions to Quit Among State Health Agency Workers.

Science.gov (United States)

Liss-Levinson, Rivka; Bharthapudi, Kiran; Leider, Jonathon P; Sellers, Katie

2015-01-01

State health agencies play a critical role in protecting and promoting the health and well-being of the people they serve. To be effective, they must maintain a highly skilled, diverse workforce of sufficient size and with proper training. The goal of this study was to examine demographics, job and workplace environment characteristics, job satisfaction, and reasons for initially joining the public health workforce as predictors of an employee's intentions to leave an organization within the next year. This study used a cross-sectional design. Respondents were selected on the basis of a stratified sampling approach, with 5 geographic (paired Health and Human Services [HHS] regions) as the primary strata. Balanced repeated replication was used as a resampling method for variance estimation. A logistic regression model was used to examine the correlates of intentions to leave one's organization within the next year. The independent variables included several measures of satisfaction, perceptions about the workplace environment, initial reasons for joining public health, gender, age, education, salary, supervisory status, program area, and paired HHS region. The sample for this study consisted of 10,246 permanently employed state health agency central office employees who responded to the Public Health Workforce Interests and Needs Survey (PH WINS). Considering leaving one's organization within the next year. Being a person of color, living in the West (HHS regions 9 and 10), and shorter tenure in one's current position were all associated with higher odds of intentions to leave an organization within the next year. Conversely, greater employee engagement, organizational support, job satisfaction, organization satisfaction, and pay satisfaction were all significant predictors of lower intentions to leave one's organization within the next year. Results from this study suggest several variables related to demographics, job characteristics, workplace environment, and

Geometry of perturbed Gaussian states and quantum estimation

International Nuclear Information System (INIS)

Genoni, Marco G; Giorda, Paolo; Paris, Matteo G A

2011-01-01

We address the non-Gaussianity (nG) of states obtained by weakly perturbing a Gaussian state and investigate the relationships with quantum estimation. For classical perturbations, i.e. perturbations to eigenvalues, we found that the nG of the perturbed state may be written as the quantum Fisher information (QFI) distance minus a term depending on the infinitesimal energy change, i.e. it provides a lower bound to statistical distinguishability. Upon moving on isoenergetic surfaces in a neighbourhood of a Gaussian state, nG thus coincides with a proper distance in the Hilbert space and exactly quantifies the statistical distinguishability of the perturbations. On the other hand, for perturbations leaving the covariance matrix unperturbed, we show that nG provides an upper bound to the QFI. Our results show that the geometry of non-Gaussian states in the neighbourhood of a Gaussian state is definitely not trivial and cannot be subsumed by a differential structure. Nevertheless, the analysis of perturbations to a Gaussian state reveals that nG may be a resource for quantum estimation. The nG of specific families of perturbed Gaussian states is analysed in some detail with the aim of finding the maximally non-Gaussian state obtainable from a given Gaussian one. (fast track communication)

Fidelity estimation between two finite ensembles of unknown pure equatorial qubit states

Energy Technology Data Exchange (ETDEWEB)

Siomau, Michael, E-mail: siomau@physi.uni-heidelberg.de [Physikalisches Institut, Heidelberg Universitaet, D-69120 Heidelberg (Germany); Department of Theoretical Physics, Belarussian State University, 220030 Minsk (Belarus)

2011-09-05

Suppose, we are given two finite ensembles of pure qubit states, so that the qubits in each ensemble are prepared in identical (but unknown for us) states lying on the equator of the Bloch sphere. What is the best strategy to estimate fidelity between these two finite ensembles of qubit states? We discuss three possible strategies for the fidelity estimation. We show that the best strategy includes two stages: a specific unitary transformation on two ensembles and state estimation of the output states of this transformation. -- Highlights: → We search for the best strategy for the fidelity estimation. → A measurement-based, a cloning-based and a unified strategies are considered. → The last strategy includes a specific unitary transformation and state estimation. → The unified strategy is shown to be the best among the three.

Transitions among Health States Using 12 Measures of Successful Aging in Men and Women: Results from the Cardiovascular Health Study

Directory of Open Access Journals (Sweden)

Stephen Thielke

2012-01-01

Full Text Available Introduction. Successful aging has many dimensions, which may manifest differently in men and women at different ages. Methods. We characterized one-year transitions among health states in 12 measures of successful aging among adults in the Cardiovascular Health Study. The measures included self-rated health, ADLs, IADLs, depression, cognition, timed walk, number of days spent in bed, number of blocks walked, extremity strength, recent hospitalizations, feelings about life as a whole, and life satisfaction. We dichotomized variables into “healthy” or “sick,” states, and estimated the prevalence of the healthy state and the probability of transitioning from one state to another, or dying, during yearly intervals. We compared men and women and three age groups (65–74, 75–84, and 85–94. Findings. Measures of successful aging showed similar results by gender. Most participants remained healthy even into advanced ages, although health declined for all measures. Recuperation, although less common with age, still occurred frequently. Men had a higher death rate than women regardless of health status, and were also more likely to remain in the healthy state. Discussion. The results suggest a qualitatively different experience of successful aging between men and women. Men did not simply “age faster” than women.

Guidelines for preparation of State water-use estimates for 2015

Science.gov (United States)

Bradley, Michael W.

2017-05-01

The U.S. Geological Survey (USGS) has estimated the use of water in the United States at 5-year intervals since 1950. This report describes the water-use categories and data elements used for the national water-use compilation conducted as part of the USGS National Water-Use Science Project. The report identifies sources of water-use information, provides standard methods and techniques for estimating water use at the county level, and outlines steps for preparing documentation for the United States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.As part of this USGS program to document water use on a national scale, estimates of water withdrawals for the categories of public supply, self-supplied domestic, industrial, irrigation, and thermoelectric power are prepared for each county in each State, District, or territory by using the guidelines in this report. County estimates of water withdrawals for aquaculture, livestock, and mining are prepared for each State by using a county-based national model, although water-use programs in each State or Water Science Center have the option of producing independent county estimates of water withdrawals for these categories. Estimates of water withdrawals and consumptive use for thermoelectric power will be aggregated to the county level for each State by the national project; additionally, irrigation consumptive use at the county level will also be provided, although study chiefs in each State have the option of producing independent county estimates of water withdrawals and consumptive use for these categories.Estimates of deliveries of water from public supplies for domestic use by county also will be prepared for each State. As a result, total domestic water use can be determined for each State by combining self-supplied domestic withdrawals and public-supplied domestic deliveries. Fresh groundwater and surface-water estimates will be prepared for all categories of use, and saline groundwater and

State and parameter estimation in biotechnical batch reactors

NARCIS (Netherlands)

Keesman, K.J.

2000-01-01

In this paper the problem of state and parameter estimation in biotechnical batch reactors is considered. Models describing the biotechnical process behaviour are usually nonlinear with time-varying parameters. Hence, the resulting large dimensions of the augmented state vector, roughly > 7, in

An open source framework for tracking and state estimation ('Stone Soup')

Science.gov (United States)

Thomas, Paul A.; Barr, Jordi; Balaji, Bhashyam; White, Kruger

2017-05-01

The ability to detect and unambiguously follow all moving entities in a state-space is important in multiple domains both in defence (e.g. air surveillance, maritime situational awareness, ground moving target indication) and the civil sphere (e.g. astronomy, biology, epidemiology, dispersion modelling). However, tracking and state estimation researchers and practitioners have difficulties recreating state-of-the-art algorithms in order to benchmark their own work. Furthermore, system developers need to assess which algorithms meet operational requirements objectively and exhaustively rather than intuitively or driven by personal favourites. We have therefore commenced the development of a collaborative initiative to create an open source framework for production, demonstration and evaluation of Tracking and State Estimation algorithms. The initiative will develop a (MIT-licensed) software platform for researchers and practitioners to test, verify and benchmark a variety of multi-sensor and multi-object state estimation algorithms. The initiative is supported by four defence laboratories, who will contribute to the development effort for the framework. The tracking and state estimation community will derive significant benefits from this work, including: access to repositories of verified and validated tracking and state estimation algorithms, a framework for the evaluation of multiple algorithms, standardisation of interfaces and access to challenging data sets. Keywords: Tracking,

Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems.

Science.gov (United States)

Chen, Tengpeng; Foo, Yi Shyh Eddy; Ling, K V; Chen, Xuebing

2017-10-11

In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is proposed for the large-scale power system state estimation. The proposed method partitions the power systems into several local areas with non-overlapping states. Unlike the centralized approach where all measurements are sent to a processing center, the proposed method distributes the state estimation task to the local processing centers where local measurements are collected. Inspired by the partitioned moving horizon estimation (PMHE) algorithm, each local area solves a smaller optimization problem to estimate its own local states by using local measurements and estimated results from its neighboring areas. In contrast with PMHE, the error from the process model is ignored in our method. The proposed modified PMHE (mPMHE) approach can also take constraints on states into account during the optimization process such that the influence of the outliers can be further mitigated. Simulation results on the IEEE 14-bus and 118-bus systems verify that our method achieves comparable state estimation accuracy but with a significant reduction in the overall computation load.

Metric Indices for Performance Evaluation of a Mixed Measurement based State Estimator

Directory of Open Access Journals (Sweden)

Paula Sofia Vide

2013-01-01

Full Text Available With the development of synchronized phasor measurement technology in recent years, it gains great interest the use of PMU measurements to improve state estimation performances due to their synchronized characteristics and high data transmission speed. The ability of the Phasor Measurement Units (PMU to directly measure the system state is a key over SCADA measurement system. PMU measurements are superior to the conventional SCADA measurements in terms of resolution and accuracy. Since the majority of measurements in existing estimators are from conventional SCADA measurement system, it is hard to be fully replaced by PMUs in the near future so state estimators including both phasor and conventional SCADA measurements are being considered. In this paper, a mixed measurement (SCADA and PMU measurements state estimator is proposed. Several useful measures for evaluating various aspects of the performance of the mixed measurement state estimator are proposed and explained. State Estimator validity, performance and characteristics of the results on IEEE 14 bus test system and IEEE 30 bus test system are presented.

The effect of non-response on estimates of health care utilisation

DEFF Research Database (Denmark)

Gundgaard, Jens; Ekholm, Orla; Hansen, Ebba Holme

2008-01-01

BACKGROUND: Non-response in health surveys may lead to bias in estimates of health care utilisation. The magnitude, direction and composition of the bias are usually not well known. When data from health surveys are merged with data from registers at the individual level, analyses can reveal non......-response bias. Our aim was to estimate the composition, direction and magnitude of non-response bias in the estimation of health care costs in two types of health interview surveys. METHODS: The surveys were (1) a national personal interview survey of 22 484 Danes (2) a telephone interview survey of 5000 Danes...... living in Funen County. Data were linked with register information on health care utilisation in hospitals and primary care. Health care utilisation was estimated for respondents and non-respondents, and the difference was explained by a decomposition method of bias components. RESULTS: The surveys...

3 CFR - State Children's Health Insurance Program

Science.gov (United States)

2010-01-01

... 3 The President 1 2010-01-01 2010-01-01 false State Children's Health Insurance Program... Insurance Program Memorandum for the Secretary of Health and Human Services The State Children's Health Insurance Program (SCHIP) encourages States to provide health coverage for uninsured children in families...

Estimating state of charge and health of lithium-ion batteries with guided waves using built-in piezoelectric sensors/actuators

Science.gov (United States)

Ladpli, Purim; Kopsaftopoulos, Fotis; Chang, Fu-Kuo

2018-04-01

This work presents the feasibility of monitoring state of charge (SoC) and state of health (SoH) of lithium-ion pouch batteries with acousto-ultrasonic guided waves. The guided waves are propagated and sensed using low-profile, built-in piezoelectric disc transducers that can be retrofitted onto off-the-shelf batteries. Both experimental and analytical studies are performed to understand the relationship between guided waves generated in a pitch-catch mode and battery SoC/SoH. The preliminary experiments on representative pouch cells show that the changes in time of flight (ToF) and signal amplitude (SA) resulting from shifts in the guided wave signals correlate strongly with the electrochemical charge-discharge cycling and aging. An analytical acoustic model is developed to simulate the variations in electrode moduli and densities during cycling, which correctly validates the absolute values and range of experimental ToF. It is further illustrated via a statistical study that ToF and SA can be used in a prediction model to accurately estimate SoC/SoH. Additionally, by using multiple sensors in a network configuration on the same battery, a significantly more reliable and accurate SoC/SoH prediction is achieved. The indicative results from this study can be extended to develop a unified guided-wave-based framework for SoC/SoH monitoring of many lithium-ion battery applications.

Integrating national surveys to estimate small area variations in poor health and limiting long-term illness in Great Britain.

Science.gov (United States)

Moon, Graham; Aitken, Grant; Taylor, Joanna; Twigg, Liz

2017-08-28

This study aims to address, for the first time, the challenges of constructing small area estimates of health status using linked national surveys. The study also seeks to assess the concordance of these small area estimates with data from national censuses. Population level health status in England, Scotland and Wales. A linked integrated dataset of 23 374 survey respondents (16+ years) from the 2011 waves of the Health Survey for England (n=8603), the Scottish Health Survey (n=7537) and the Welsh Health Survey (n=7234). Population prevalence of poorer self-rated health and limiting long-term illness. A multilevel small area estimation modelling approach was used to estimate prevalence of these outcomes for middle super output areas in England and Wales and intermediate zones in Scotland. The estimates were then compared with matched measures from the contemporaneous 2011 UK Census. There was a strong positive association between the small area estimates and matched census measures for all three countries for both poorer self-rated health (r=0.828, 95% CI 0.821 to 0.834) and limiting long-term illness (r=0.831, 95% CI 0.824 to 0.837), although systematic differences were evident, and small area estimation tended to indicate higher prevalences than census data. Despite strong concordance, variations in the small area prevalences of poorer self-rated health and limiting long-term illness evident in census data cannot be replicated perfectly using small area estimation with linked national surveys. This reflects a lack of harmonisation between surveys over question wording and design. The nature of small area estimates as 'expected values' also needs to be better understood. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Application of radial basis neural network for state estimation of ...

African Journals Online (AJOL)

An original application of radial basis function (RBF) neural network for power system state estimation is proposed in this paper. The property of massive parallelism of neural networks is employed for this. The application of RBF neural network for state estimation is investigated by testing its applicability on a IEEE 14 bus ...

Introduction to State Estimation of High-Rate System Dynamics.

Science.gov (United States)

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

Tracking Psychosocial Health in Adults with Epilepsy—Estimates from the 2010 National Health Interview Survey

Science.gov (United States)

Kobau, R; Cui, W; Kadima, N; Zack, MM; Sajatovic, M; Kaiboriboon, K; Jobst, B

2015-01-01

Objective This study provides population-based estimates of psychosocial health among U.S. adults with epilepsy from the 2010 National Health Interview Survey. Methods Multinomial logistic regression was used to estimate the prevalence of the following measures of psychosocial health among adults with and those without epilepsy: 1) the Kessler-6 scale of Serious Psychological Distress; 2) cognitive limitation; the extent of impairments associated with psychological problems; and work limitation; 3) Social participation; and 4) the Patient Reported Outcome Measurement Information System Global Health scale. Results Compared with adults without epilepsy, adults with epilepsy, especially those with active epilepsy, reported significantly worse psychological health, more cognitive impairment, difficulty in participating in some social activities, and reduced health-related quality of life (HRQOL). Conclusions These disparities in psychosocial health in U.S. adults with epilepsy serve as baseline national estimates of their HRQOL, consistent with Healthy People 2020 national objectives on HRQOL. PMID:25305435

State health policy for terrorism preparedness.

Science.gov (United States)

Ziskin, Leah Z; Harris, Drew A

2007-09-01

State health policy for terrorism preparedness began before the terrorist attacks on September 11, 2001, but was accelerated after that day. In a crisis atmosphere after September 11, the states found their policies changing rapidly, greatly influenced by federal policies and federal dollars. In the 5 years since September 11, these state health policies have been refined. This refinement has included a restatement of the goals and objectives of state programs, the modernization of emergency powers statutes, the education and training of the public health workforce, and a preparation of the health care system to better care for victims of disasters, including acts of terrorism.

Standard error of measurement of 5 health utility indexes across the range of health for use in estimating reliability and responsiveness.

Science.gov (United States)

Palta, Mari; Chen, Han-Yang; Kaplan, Robert M; Feeny, David; Cherepanov, Dasha; Fryback, Dennis G

2011-01-01

Standard errors of measurement (SEMs) of health-related quality of life (HRQoL) indexes are not well characterized. SEM is needed to estimate responsiveness statistics, and is a component of reliability. To estimate the SEM of 5 HRQoL indexes. The National Health Measurement Study (NHMS) was a population-based survey. The Clinical Outcomes and Measurement of Health Study (COMHS) provided repeated measures. A total of 3844 randomly selected adults from the noninstitutionalized population aged 35 to 89 y in the contiguous United States and 265 cataract patients. The SF6-36v2™, QWB-SA, EQ-5D, HUI2, and HUI3 were included. An item-response theory approach captured joint variation in indexes into a composite construct of health (theta). The authors estimated 1) the test-retest standard deviation (SEM-TR) from COMHS, 2) the structural standard deviation (SEM-S) around theta from NHMS, and 3) reliability coefficients. SEM-TR was 0.068 (SF-6D), 0.087 (QWB-SA), 0.093 (EQ-5D), 0.100 (HUI2), and 0.134 (HUI3), whereas SEM-S was 0.071, 0.094, 0.084, 0.074, and 0.117, respectively. These yield reliability coefficients 0.66 (COMHS) and 0.71 (NHMS) for SF-6D, 0.59 and 0.64 for QWB-SA, 0.61 and 0.70 for EQ-5D, 0.64 and 0.80 for HUI2, and 0.75 and 0.77 for HUI3, respectively. The SEM varied across levels of health, especially for HUI2, HUI3, and EQ-5D, and was influenced by ceiling effects. Limitations. Repeated measures were 5 mo apart, and estimated theta contained measurement error. The 2 types of SEM are similar and substantial for all the indexes and vary across health.

Power system static state estimation using Kalman filter algorithm

Directory of Open Access Journals (Sweden)

Saikia Anupam

2016-01-01

Full Text Available State estimation of power system is an important tool for operation, analysis and forecasting of electric power system. In this paper, a Kalman filter algorithm is presented for static estimation of power system state variables. IEEE 14 bus system is employed to check the accuracy of this method. Newton Raphson load flow study is first carried out on our test system and a set of data from the output of load flow program is taken as measurement input. Measurement inputs are simulated by adding Gaussian noise of zero mean. The results of Kalman estimation are compared with traditional Weight Least Square (WLS method and it is observed that Kalman filter algorithm is numerically more efficient than traditional WLS method. Estimation accuracy is also tested for presence of parametric error in the system. In addition, numerical stability of Kalman filter algorithm is tested by considering inclusion of zero mean errors in the initial estimates.

State energy data report 1992: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

1994-05-01

This is a report of energy consumption by state for the years 1960 to 1992. The report contains summaries of energy consumption for the US and by state, consumption by source, comparisons to other energy use reports, consumption by energy use sector, and describes the estimation methodologies used in the preparation of the report. Some years are not listed specifically although they are included in the summary of data.

Estimating the impact of newly arrived foreign-born persons on tuberculosis in the United States.

Directory of Open Access Journals (Sweden)

Yecai Liu

Full Text Available Among approximately 163.5 million foreign-born persons admitted to the United States annually, only 500,000 immigrants and refugees are required to undergo overseas tuberculosis (TB screening. It is unclear what extent of the unscreened nonimmigrant visitors contributes to the burden of foreign-born TB in the United States.We defined foreign-born persons within 1 year after arrival in the United States as "newly arrived", and utilized data from U.S. Department of Homeland Security, U.S. Centers for Disease Control and Prevention, and World Health Organization to estimate the incidence of TB among newly arrived foreign-born persons in the United States. During 2001 through 2008, 11,500 TB incident cases, including 291 multidrug-resistant TB incident cases, were estimated to occur among 20,989,738 person-years for the 1,479,542,654 newly arrived foreign-born persons in the United States. Of the 11,500 estimated TB incident cases, 41.6% (4,783 occurred among immigrants and refugees, 36.6% (4,211 among students/exchange visitors and temporary workers, 13.8% (1,589 among tourists and business travelers, and 7.3% (834 among Canadian and Mexican nonimmigrant visitors without an I-94 form (e.g., arrival-departure record. The top 3 newly arrived foreign-born populations with the largest estimated TB incident cases per 100,000 admissions were immigrants and refugees from high-incidence countries (e.g., 2008 WHO-estimated TB incidence rate of ≥100 cases/100,000 population/year; 235.8 cases/100,000 admissions, 95% confidence interval [CI], 228.3 to 243.3, students/exchange visitors and temporary workers from high-incidence countries (60.9 cases/100,000 admissions, 95% CI, 58.5 to 63.3, and immigrants and refugees from medium-incidence countries (e.g., 2008 WHO-estimated TB incidence rate of 15-99 cases/100,000 population/year; 55.2 cases/100,000 admissions, 95% CI, 51.6 to 58.8.Newly arrived nonimmigrant visitors contribute substantially to the burden of

Estimating the impact of newly arrived foreign-born persons on tuberculosis in the United States.

Science.gov (United States)

Liu, Yecai; Painter, John A; Posey, Drew L; Cain, Kevin P; Weinberg, Michelle S; Maloney, Susan A; Ortega, Luis S; Cetron, Martin S

2012-01-01

Among approximately 163.5 million foreign-born persons admitted to the United States annually, only 500,000 immigrants and refugees are required to undergo overseas tuberculosis (TB) screening. It is unclear what extent of the unscreened nonimmigrant visitors contributes to the burden of foreign-born TB in the United States. We defined foreign-born persons within 1 year after arrival in the United States as "newly arrived", and utilized data from U.S. Department of Homeland Security, U.S. Centers for Disease Control and Prevention, and World Health Organization to estimate the incidence of TB among newly arrived foreign-born persons in the United States. During 2001 through 2008, 11,500 TB incident cases, including 291 multidrug-resistant TB incident cases, were estimated to occur among 20,989,738 person-years for the 1,479,542,654 newly arrived foreign-born persons in the United States. Of the 11,500 estimated TB incident cases, 41.6% (4,783) occurred among immigrants and refugees, 36.6% (4,211) among students/exchange visitors and temporary workers, 13.8% (1,589) among tourists and business travelers, and 7.3% (834) among Canadian and Mexican nonimmigrant visitors without an I-94 form (e.g., arrival-departure record). The top 3 newly arrived foreign-born populations with the largest estimated TB incident cases per 100,000 admissions were immigrants and refugees from high-incidence countries (e.g., 2008 WHO-estimated TB incidence rate of ≥100 cases/100,000 population/year; 235.8 cases/100,000 admissions, 95% confidence interval [CI], 228.3 to 243.3), students/exchange visitors and temporary workers from high-incidence countries (60.9 cases/100,000 admissions, 95% CI, 58.5 to 63.3), and immigrants and refugees from medium-incidence countries (e.g., 2008 WHO-estimated TB incidence rate of 15-99 cases/100,000 population/year; 55.2 cases/100,000 admissions, 95% CI, 51.6 to 58.8). Newly arrived nonimmigrant visitors contribute substantially to the burden of foreign

An Australian discrete choice experiment to value eq-5d health states.

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Viney, Rosalie; Norman, Richard; Brazier, John; Cronin, Paula; King, Madeleine T; Ratcliffe, Julie; Street, Deborah

2014-06-01

Conventionally, generic quality-of-life health states, defined within multi-attribute utility instruments, have been valued using a Standard Gamble or a Time Trade-Off. Both are grounded in expected utility theory but impose strong assumptions about the form of the utility function. Preference elicitation tasks for both are complicated, limiting the number of health states that each respondent can value and, therefore, that can be valued overall. The usual approach has been to value a set of the possible health states and impute values for the remainder. Discrete Choice Experiments (DCEs) offer an attractive alternative, allowing investigation of more flexible specifications of the utility function and greater coverage of the response surface. We designed a DCE to obtain values for EQ-5D health states and implemented it in an Australia-representative online panel (n = 1,031). A range of specifications investigating non-linear preferences with respect to time and interactions between EQ-5D levels were estimated using a random-effects probit model. The results provide empirical support for a flexible utility function, including at least some two-factor interactions. We then constructed a preference index such that full health and death were valued at 1 and 0, respectively, to provide a DCE-based algorithm for Australian cost-utility analyses. Copyright © 2013 John Wiley & Sons, Ltd.

Federally-Assisted Healthcare Coverage among Male State Prisoners with Chronic Health Problems.

Directory of Open Access Journals (Sweden)

David L Rosen

Full Text Available Prisoners have higher rates of chronic diseases such as substance dependence, mental health conditions and infectious disease, as compared to the general population. We projected the number of male state prisoners with a chronic health condition who at release would be eligible or ineligible for healthcare coverage under the Affordable Care Act (ACA. We used ACA income guidelines in conjunction with reported pre-arrest social security benefits and income from a nationally representative sample of prisoners to estimate the number eligible for healthcare coverage at release. There were 643,290 US male prisoners aged 18-64 with a chronic health condition. At release, 73% in Medicaid-expansion states would qualify for Medicaid or tax credits. In non-expansion states, 54% would qualify for tax credits, but 22% (n = 69,827 had incomes of ≤ 100% the federal poverty limit and thus would be ineligible for ACA-mediated healthcare coverage. These prisoners comprise 11% of all male prisoners with a chronic condition. The ACA was projected to provide coverage to most male state prisoners with a chronic health condition; however, roughly 70,000 fall in the "coverage gap" and may require non-routine care at emergency departments. Mechanisms are needed to secure coverage for this at risk group and address barriers to routine utilization of health services.

Federally-Assisted Healthcare Coverage among Male State Prisoners with Chronic Health Problems.

Science.gov (United States)

Rosen, David L; Grodensky, Catherine A; Holley, Tara K

2016-01-01

Prisoners have higher rates of chronic diseases such as substance dependence, mental health conditions and infectious disease, as compared to the general population. We projected the number of male state prisoners with a chronic health condition who at release would be eligible or ineligible for healthcare coverage under the Affordable Care Act (ACA). We used ACA income guidelines in conjunction with reported pre-arrest social security benefits and income from a nationally representative sample of prisoners to estimate the number eligible for healthcare coverage at release. There were 643,290 US male prisoners aged 18-64 with a chronic health condition. At release, 73% in Medicaid-expansion states would qualify for Medicaid or tax credits. In non-expansion states, 54% would qualify for tax credits, but 22% (n = 69,827) had incomes of ≤ 100% the federal poverty limit and thus would be ineligible for ACA-mediated healthcare coverage. These prisoners comprise 11% of all male prisoners with a chronic condition. The ACA was projected to provide coverage to most male state prisoners with a chronic health condition; however, roughly 70,000 fall in the "coverage gap" and may require non-routine care at emergency departments. Mechanisms are needed to secure coverage for this at risk group and address barriers to routine utilization of health services.

Tracking development assistance for health to fragile states: 2005-2011.

Science.gov (United States)

Graves, Casey M; Haakenstad, Annie; Dieleman, Joseph L

2015-03-19

Development assistance for health (DAH) has grown substantially, totaling more than $31.3 billion in 2013. However, the degree that countries with high concentrations of armed conflict, ethnic violence, inequality, debt, and corruption have received this health aid and how that assistance might be different from the funding provided to other countries has not been assessed. We combine DAH estimates and a multidimensional fragile states index for 2005 through 2011. We disaggregate and compare total DAH disbursed for fragile states versus stable states. Between 2005 and 2011, DAH per person in fragile countries increased at an annualized rate of 5.4%. In 2011 DAH to fragile countries totaled $6.2 billion, which is $5.05 per person. This is 43% of total DAH that is traced to a country. Comparing low-income countries, funding channeled to fragile countries was $7.22 per person while stable countries received $11.15 per person. Relative to stable countries, donors preferred to provide more funding to low-income fragile countries that have refugees or ongoing external intervention but tended to avoid providing funding to countries with political gridlock, flawed elections, or economic decline. In 2011, Ethiopia received the most health aid of all fragile countries, while the United States provided the most funds to fragile countries. In 2011, 1.2 billion people lived in fragile countries. DAH can bolster health systems and might be especially valuable in providing long-term stability in fragile environments. While external health funding to these countries has increased since 2005, it is, in per person terms, almost half as much as the DAH provided to stable countries of comparable income levels.

Utility Values for Advanced Soft Tissue Sarcoma Health States from the General Public in the United Kingdom

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Julian F. Guest

2013-01-01

Full Text Available Soft tissue sarcomas are a rare type of cancer generally treated with palliative chemotherapy when in the advanced stage. There is a lack of published health utility data for locally advanced “inoperable”/metastatic disease (ASTS, essential for calculating the cost-effectiveness of current and future treatments. This study estimated time trade-off (TTO and standard gamble (SG preference values associated with four ASTS health states (progressive disease, stable disease, partial response, complete response among members of the general public in the UK (n=207. The four health states were associated with decreases in preference values from full health. Complete response was the most preferred health state (mean utility of 0.60 using TTO. The second most preferred health state was partial response followed by stable disease (mean utilities were 0.51 and 0.43, respectively, using TTO. The least preferred health state was progressive disease (mean utility of 0.30 using TTO. The utility value for each state was significantly different from one another (P<0.001. This study demonstrated and quantified the impact that different treatment responses may have on the health-related quality of life of patients with ASTS.

Geographic Variations in Arthritis Prevalence, Health-Related Characteristics, and Management - United States, 2015.

Science.gov (United States)

Barbour, Kamil E; Moss, Susan; Croft, Janet B; Helmick, Charles G; Theis, Kristina A; Brady, Teresa J; Murphy, Louise B; Hootman, Jennifer M; Greenlund, Kurt J; Lu, Hua; Wang, Yan

2018-03-16

Doctor-diagnosed arthritis is a common chronic condition affecting an estimated 23% (54 million) of adults in the United States, greatly influencing quality of life and costing approximately $300 billion annually. The geographic variations in arthritis prevalence, health-related characteristics, and management among states and territories are unknown. Therefore, public health professionals need to understand arthritis in their areas to target dissemination of evidence-based interventions that reduce arthritis morbidity. 2015. The Behavioral Risk Factor Surveillance System is an annual, random-digit-dialed landline and cellular telephone survey of noninstitutionalized adults aged ≥18 years residing in the United States. Self-reported data are collected from the 50 states, the District of Columbia, Guam, and Puerto Rico. Unadjusted and age-standardized prevalences of arthritis, arthritis health-related characteristics, and arthritis management were calculated. County-level estimates were calculated using a validated statistical modeling method. In 2015, in the 50 states and the District of Columbia, median age-standardized prevalence of arthritis was 23.0% (range: 17.2%-33.6%). Modeled prevalence of arthritis varied considerably by county (range: 11.2%-42.7%). In 13 states that administered the arthritis management module, among adults with arthritis, the age-standardized median percentage of participation in a self-management education course was 14.5% (range: 9.1%-19.0%), being told by a health care provider to engage in physical activity or exercise was 58.5% (range: 52.3%-61.9%), and being told to lose weight to manage arthritis symptoms (if overweight or obese) was 44.5% (range: 35.1%-53.2%). Respondents with arthritis who lived in the quartile of states with the highest prevalences of arthritis had the highest percentages of negative health-related characteristics (i.e., arthritis-attributable activity limitations, arthritis-attributable severe joint pain

National intelligence estimates and the Failed State Index.

Science.gov (United States)

Voracek, Martin

2013-10-01

Across 177 countries around the world, the Failed State Index, a measure of state vulnerability, was reliably negatively associated with the estimates of national intelligence. Psychometric analysis of the Failed State Index, compounded of 12 social, economic, and political indicators, suggested factorial unidimensionality of this index. The observed correspondence of higher national intelligence figures to lower state vulnerability might arise through these two macro-level variables possibly being proxies of even more pervasive historical and societal background variables that affect both.

On Estimating Marginal Tax Rates for U.S. States

OpenAIRE

Reed, W. Robert; Rogers, Cynthia L; Skidmore, Mark

2011-01-01

This paper presents a procedure for generating state-specific time-varying estimates of marginal tax rates (MTRs). Most estimates of MTRs follow a procedure developed by Koester and Kormendi (1989) (K&K). Unfortunately, the time-invariant nature of the K&K estimates precludes their use as explanatory variables in panel data studies with fixed effects. Furthermore, the associated MTR estimates are not explicitly linked to statutory tax parameters. Our approach addresses both shortcomings. Usin...

Global, regional and national levels and trends of preterm birth rates for 1990 to 2014: protocol for development of World Health Organization estimates.

Science.gov (United States)

Vogel, Joshua P; Chawanpaiboon, Saifon; Watananirun, Kanokwaroon; Lumbiganon, Pisake; Petzold, Max; Moller, Ann-Beth; Thinkhamrop, Jadsada; Laopaiboon, Malinee; Seuc, Armando H; Hogan, Daniel; Tunçalp, Ozge; Allanson, Emma; Betrán, Ana Pilar; Bonet, Mercedes; Oladapo, Olufemi T; Gülmezoglu, A Metin

2016-06-17

The official WHO estimates of preterm birth are an essential global resource for assessing the burden of preterm birth and developing public health programmes and policies. This protocol describes the methods that will be used to identify, critically appraise and analyse all eligible preterm birth data, in order to develop global, regional and national level estimates of levels and trends in preterm birth rates for the period 1990 - 2014. We will conduct a systematic review of civil registration and vital statistics (CRVS) data on preterm birth for all WHO Member States, via national Ministries of Health and Statistics Offices. For Member States with absent, limited or lower-quality CRVS data, a systematic review of surveys and/or research studies will be conducted. Modelling will be used to develop country, regional and global rates for 2014, with time trends for Member States where sufficient data are available. Member States will be invited to review the methodology and provide additional eligible data via a country consultation before final estimates are developed and disseminated. This research will be used to generate estimates on the burden of preterm birth globally for 1990 to 2014. We invite feedback on the methodology described, and call on the public health community to submit pertinent data for consideration. Registered at PROSPERO CRD42015027439 CONTACT: pretermbirth@who.int.

Parameter and State Estimation of Large-Scale Complex Systems Using Python Tools

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M. Anushka S. Perera

2015-07-01

Full Text Available This paper discusses the topics related to automating parameter, disturbance and state estimation analysis of large-scale complex nonlinear dynamic systems using free programming tools. For large-scale complex systems, before implementing any state estimator, the system should be analyzed for structural observability and the structural observability analysis can be automated using Modelica and Python. As a result of structural observability analysis, the system may be decomposed into subsystems where some of them may be observable --- with respect to parameter, disturbances, and states --- while some may not. The state estimation process is carried out for those observable subsystems and the optimum number of additional measurements are prescribed for unobservable subsystems to make them observable. In this paper, an industrial case study is considered: the copper production process at Glencore Nikkelverk, Kristiansand, Norway. The copper production process is a large-scale complex system. It is shown how to implement various state estimators, in Python, to estimate parameters and disturbances, in addition to states, based on available measurements.

Estimation of the number of wild pigs found in the United States

Energy Technology Data Exchange (ETDEWEB)

Mayer, J. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2014-08-01

Based on a compilation of three estimation approaches, the total nationwide population of wild pigs in the United States numbers approximately 6.3 million animals, with that total estimate ranging from 4.4 up to 11.3 million animals. The majority of these numbers (99 percent), which were encompassed by ten states (i.e., Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Oklahoma, South Carolina and Texas), were based on defined estimation methodologies (e.g., density estimates correlated to the total potential suitable wild pig habitat statewide, statewide harvest percentages, statewide agency surveys regarding wild pig distribution and numbers). In contrast to the pre-1990 estimates, none of these more recent efforts, collectively encompassing 99 percent of the total, were based solely on anecdotal information or speculation. To that end, one can defensibly state that the wild pigs found in the United States number in the millions of animals, with the nationwide population estimated to arguably vary from about four million up to about eleven million individuals.

Vehicle-Level Reasoning Systems: Integrating System-Wide Data to Estimate the Instantaneous Health State

Science.gov (United States)

Srivastava, Ashok N.; Mylaraswmay, Dinkar; Mah, Robert W.; Cooper, Eric G.

2011-01-01

At the aircraft level, a Vehicle-Level Reasoning System (VLRS) can be developed to provide aircraft with at least two significant capabilities: improvement of aircraft safety due to enhanced monitoring and reasoning about the aircrafts health state, and also potential cost savings by enabling Condition Based Maintenance (CBM). Along with the benefits of CBM, an important challenge facing aviation safety today is safeguarding against system and component failures and malfunctions. Faults can arise in one or more aircraft subsystem their effects in one system may propagate to other subsystems, and faults may interact.

Estimating the state of large spatio-temporally chaotic systems

International Nuclear Information System (INIS)

Ott, E.; Hunt, B.R.; Szunyogh, I.; Zimin, A.V.; Kostelich, E.J.; Corazza, M.; Kalnay, E.; Patil, D.J.; Yorke, J.A.

2004-01-01

We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

Science.gov (United States)

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-03-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

Science.gov (United States)

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models

KAUST Repository

Ting, Chee-Ming

2017-12-06

We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.

Battery state-of-charge estimation using approximate least squares

Science.gov (United States)

Unterrieder, C.; Zhang, C.; Lunglmayr, M.; Priewasser, R.; Marsili, S.; Huemer, M.

2015-03-01

In recent years, much effort has been spent to extend the runtime of battery-powered electronic applications. In order to improve the utilization of the available cell capacity, high precision estimation approaches for battery-specific parameters are needed. In this work, an approximate least squares estimation scheme is proposed for the estimation of the battery state-of-charge (SoC). The SoC is determined based on the prediction of the battery's electromotive force. The proposed approach allows for an improved re-initialization of the Coulomb counting (CC) based SoC estimation method. Experimental results for an implementation of the estimation scheme on a fuel gauge system on chip are illustrated. Implementation details and design guidelines are presented. The performance of the presented concept is evaluated for realistic operating conditions (temperature effects, aging, standby current, etc.). For the considered test case of a GSM/UMTS load current pattern of a mobile phone, the proposed method is able to re-initialize the CC-method with a high accuracy, while state-of-the-art methods fail to perform a re-initialization.

Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation

Directory of Open Access Journals (Sweden)

Xi Liu

2016-09-01

Full Text Available A new algorithm called maximum correntropy unscented Kalman filter (MCUKF is proposed and applied to relative state estimation in space communication networks. As is well known, the unscented Kalman filter (UKF provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises. Its performance may deteriorate substantially in the presence of non-Gaussian noises, especially when the measurements are disturbed by some heavy-tailed impulsive noises. By making use of the maximum correntropy criterion (MCC, the proposed algorithm can enhance the robustness of UKF against impulsive noises. In the MCUKF, the unscented transformation (UT is applied to obtain a predicted state estimation and covariance matrix, and a nonlinear regression method with the MCC cost is then used to reformulate the measurement information. Finally, the UT is adopted to the measurement equation to obtain the filter state and covariance matrix. Illustrative examples demonstrate the superior performance of the new algorithm.

A Novel Methodology for Estimating State-Of-Charge of Li-Ion Batteries Using Advanced Parameters Estimation

Directory of Open Access Journals (Sweden)

Ibrahim M. Safwat

2017-11-01

Full Text Available State-of-charge (SOC estimations of Li-ion batteries have been the focus of many research studies in previous years. Many articles discussed the dynamic model’s parameters estimation of the Li-ion battery, where the fixed forgetting factor recursive least square estimation methodology is employed. However, the change rate of each parameter to reach the true value is not taken into consideration, which may tend to poor estimation. This article discusses this issue, and proposes two solutions to solve it. The first solution is the usage of a variable forgetting factor instead of a fixed one, while the second solution is defining a vector of forgetting factors, which means one factor for each parameter. After parameters estimation, a new idea is proposed to estimate state-of-charge (SOC of the Li-ion battery based on Newton’s method. Also, the error percentage and computational cost are discussed and compared with that of nonlinear Kalman filters. This methodology is applied on a 36 V 30 A Li-ion pack to validate this idea.

Methods for Estimating Water Withdrawals for Mining in the United States, 2005

Science.gov (United States)

Lovelace, John K.

2009-01-01

The mining water-use category includes groundwater and surface water that is withdrawn and used for nonfuels and fuels mining. Nonfuels mining includes the extraction of ores, stone, sand, and gravel. Fuels mining includes the extraction of coal, petroleum, and natural gas. Water is used for mineral extraction, quarrying, milling, and other operations directly associated with mining activities. For petroleum and natural gas extraction, water often is injected for secondary oil or gas recovery. Estimates of water withdrawals for mining are needed for water planning and management. This report documents methods used to estimate withdrawals of fresh and saline groundwater and surface water for mining during 2005 for each county and county equivalent in the United States, Puerto Rico, and the U.S. Virgin Islands. Fresh and saline groundwater and surface-water withdrawals during 2005 for nonfuels- and coal-mining operations in each county or county equivalent in the United States, Puerto Rico, and the U.S. Virgin Islands were estimated. Fresh and saline groundwater withdrawals for oil and gas operations in counties of six states also were estimated. Water withdrawals for nonfuels and coal mining were estimated by using mine-production data and water-use coefficients. Production data for nonfuels mining included the mine location and weight (in metric tons) of crude ore, rock, or mineral produced at each mine in the United States, Puerto Rico, and the U.S. Virgin Islands during 2004. Production data for coal mining included the weight, in metric tons, of coal produced in each county or county equivalent during 2004. Water-use coefficients for mined commodities were compiled from various sources including published reports and written communications from U.S. Geological Survey National Water-use Information Program (NWUIP) personnel in several states. Water withdrawals for oil and gas extraction were estimated for six States including California, Colorado, Louisiana, New

Spin State Estimation of Tumbling Small Bodies

Science.gov (United States)

Olson, Corwin; Russell, Ryan P.; Bhaskaran, Shyam

2016-06-01

It is expected that a non-trivial percentage of small bodies that future missions may visit are in non-principal axis rotation (i.e. "tumbling"). The primary contribution of this paper is the application of the Extended Kalman Filter (EKF) Simultaneous Localization and Mapping (SLAM) method to estimate the small body spin state, mass, and moments of inertia; the spacecraft position and velocity; and the surface landmark locations. The method uses optical landmark measurements, and an example scenario based on the Rosetta mission is used. The SLAM method proves effective, with order of magnitude decreases in the spacecraft and small body spin state errors after less than a quarter of the comet characterization phase. The SLAM method converges nicely for initial small body angular velocity errors several times larger than the true rates (effectively having no a priori knowledge of the angular velocity). Surface landmark generation and identification are not treated in this work, but significant errors in the initial body-fixed landmark positions are effectively estimated. The algorithm remains effective for a range of different truth spin states, masses, and center of mass offsets that correspond to expected tumbling small bodies throughout the solar system.

Distributed Dynamic State Estimator, Generator Parameter Estimation and Stability Monitoring Demonstration

Energy Technology Data Exchange (ETDEWEB)

Meliopoulos, Sakis [Georgia Inst. of Technology, Atlanta, GA (United States); Cokkinides, George [Georgia Inst. of Technology, Atlanta, GA (United States); Fardanesh, Bruce [New York Power Authority, NY (United States); Hedrington, Clinton [U.S. Virgin Islands Water and Power Authority (WAPA), St. Croix (U.S. Virgin Islands)

2013-12-31

This is the final report for this project that was performed in the period: October1, 2009 to June 30, 2013. In this project, a fully distributed high-fidelity dynamic state estimator (DSE) that continuously tracks the real time dynamic model of a wide area system with update rates better than 60 times per second is achieved. The proposed technology is based on GPS-synchronized measurements but also utilizes data from all available Intelligent Electronic Devices in the system (numerical relays, digital fault recorders, digital meters, etc.). The distributed state estimator provides the real time model of the system not only the voltage phasors. The proposed system provides the infrastructure for a variety of applications and two very important applications (a) a high fidelity generating unit parameters estimation and (b) an energy function based transient stability monitoring of a wide area electric power system with predictive capability. Also the dynamic distributed state estimation results are stored (the storage scheme includes data and coincidental model) enabling an automatic reconstruction and “play back” of a system wide disturbance. This approach enables complete play back capability with fidelity equal to that of real time with the advantage of “playing back” at a user selected speed. The proposed technologies were developed and tested in the lab during the first 18 months of the project and then demonstrated on two actual systems, the USVI Water and Power Administration system and the New York Power Authority’s Blenheim-Gilboa pumped hydro plant in the last 18 months of the project. The four main thrusts of this project, mentioned above, are extremely important to the industry. The DSE with the achieved update rates (more than 60 times per second) provides a superior solution to the “grid visibility” question. The generator parameter identification method fills an important and practical need of the industry. The “energy function” based

Public health insurance under a nonbenevolent state.

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Lemieux, Pierre

2008-10-01

This paper explores the consequences of the oft ignored fact that public health insurance must actually be supplied by the state. Depending how the state is modeled, different health insurance outcomes are expected. The benevolent model of the state does not account for many actual features of public health insurance systems. One alternative is to use a standard public choice model, where state action is determined by interaction between self-interested actors. Another alternative--related to a strand in public choice theory--is to model the state as Leviathan. Interestingly, some proponents of public health insurance use an implicit Leviathan model, but not consistently. The Leviathan model of the state explains many features of public health insurance: its uncontrolled growth, its tendency toward monopoly, its capacity to buy trust and loyalty from the common people, its surveillance ability, its controlling nature, and even the persistence of its inefficiencies and waiting lines.

Differences between individual and societal health state valuations: any link with personality?

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Chapman, Benjamin P; Franks, Peter; Duberstein, Paul R; Jerant, Anthony

2009-08-01

The concept of "adaptation" has been proposed to account for differences between individual and societal valuations of specific health states in patients with chronic diseases. Little is known about psychological indices of adaptational capacity, which may predict differences in individual and societal valuations of health states. We investigated whether such differences were partially explained by personality traits in chronic disease patients. Analysis of baseline data of randomized controlled trial. Three hundred seventy patients with chronic disease. The NEO-five factor inventory measure of personality, EuroQoL-5D (EQ-5D) societal-based, and the EQ visual analogue scale individually-based measures of health valuation. Regression analyses modeled Dev, a measure of difference between the EQ-Visual Analogue Scale and EQ-5D, as a function of personality traits, sociodemographic factors, and chronic diseases. Individual valuations were significantly and clinically higher than societal valuations among patients in the second and third quartile of conscientiousness (Dev = 0.08, P = 0.01); among covariates, only depression (Dev = -0.04, P = 0.046) was also associated with Dev. Compared with societal valuations of a given health state, persons at higher quartiles of conscientiousness report less disutility associated with poor health. The effect is roughly twice that of some estimates of minimally important clinical differences on the EQ-5D and of depression. Although useful at the aggregate level, societal preference measures may systematically undervalue the health states of more conscientious individuals. Future work should examine the impact this has on individual patient outcome evaluation in clinical studies.

National Estimates of Marijuana Use and Related Indicators - National Survey on Drug Use and Health, United States, 2002-2014.

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Azofeifa, Alejandro; Mattson, Margaret E; Schauer, Gillian; McAfee, Tim; Grant, Althea; Lyerla, Rob

2016-09-02

In the United States, marijuana is the most commonly used illicit drug. In 2013, 7.5% (19.8 million) of the U.S. population aged ≥12 years reported using marijuana during the preceding month. Because of certain state-level policies that have legalized marijuana for medical or recreational use, population-based data on marijuana use and other related indicators are needed to help monitor behavioral health changes in the United States. 2002-2014. The National Survey on Drug Use and Health (NSDUH) is a national- and state-level survey of a representative sample of the civilian, noninstitutionalized U.S. population aged ≥12 years. NSDUH collects information about the use of illicit drugs, alcohol, and tobacco; initiation of substance use; frequency of substance use; substance dependence and abuse; perception of substance harm risk or no risk; and other related behavioral health indicators. This report describes national trends for selected marijuana use and related indicators, including prevalence of marijuana use; initiation; perception of harm risk, approval, and attitudes; perception of availability and mode of acquisition; dependence and abuse; and perception of legal penalty for marijuana possession. In 2014, a total of 2.5 million persons aged ≥12 years had used marijuana for the first time during the preceding 12 months, an average of approximately 7,000 new users each day. During 2002-2014, the prevalence of marijuana use during the past month, past year, and daily or almost daily increased among persons aged ≥18 years, but not among those aged 12-17 years. Among persons aged ≥12 years, the prevalence of perceived great risk from smoking marijuana once or twice a week and once a month decreased and the prevalence of perceived no risk increased. The prevalence of past year marijuana dependence and abuse decreased, except among persons aged ≥26 years. Among persons aged ≥12 years, the percentage reporting that marijuana was fairly easy or very easy

Canadian valuation of EQ-5D health states: preliminary value set and considerations for future valuation studies.

Directory of Open Access Journals (Sweden)

Nick Bansback

Full Text Available The EQ-5D is a preference based instrument which provides a description of a respondent's health status, and an empirically derived value for that health state often from a representative sample of the general population. It is commonly used to derive Quality Adjusted Life Year calculations (QALY in economic evaluations. However, values for health states have been found to differ between countries. The objective of this study was to develop a set of values for the EQ-5D health states for use in Canada.Values for 48 different EQ-5D health states were elicited using the Time Trade Off (TTO via a web survey in English. A random effect model was fitted to the data to estimate values for all 243 health states of the EQ-5D. Various model specifications were explored. Comparisons with EQ-5D values from the UK and US were made. Sensitivity analysis explored different transformations of values worse than dead, and exclusion criteria of subjects.The final model was estimated from the values of 1145 subjects with socio-demographics broadly representative of Canadian general population with the exception of Quebec. This yielded a good fit with observed TTO values, with an overall R2 of 0.403 and a mean absolute error of 0.044.A preference-weight algorithm for Canadian studies that include the EQ-5D is developed. The primary limitations regarded the representativeness of the final sample, given the language used (English only, the method of recruitment, and the difficulty in the task. Insights into potential issues for conducting valuation studies in countries as large and diverse as Canada are gained.

Estimating the Reference Incremental Cost-Effectiveness Ratio for the Australian Health System.

Science.gov (United States)

Edney, Laura Catherine; Haji Ali Afzali, Hossein; Cheng, Terence Chai; Karnon, Jonathan

2018-02-01

Spending on new healthcare technologies increases net population health when the benefits of a new technology are greater than their opportunity costs-the benefits of the best alternative use of the additional resources required to fund a new technology. The objective of this study was to estimate the expected incremental cost per quality-adjusted life-year (QALY) gained of increased government health expenditure as an empirical estimate of the average opportunity costs of decisions to fund new health technologies. The estimated incremental cost-effectiveness ratio (ICER) is proposed as a reference ICER to inform value-based decision making in Australia. Empirical top-down approaches were used to estimate the QALY effects of government health expenditure with respect to reduced mortality and morbidity. Instrumental variable two-stage least-squares regression was used to estimate the elasticity of mortality-related QALY losses to a marginal change in government health expenditure. Regression analysis of longitudinal survey data representative of the general population was used to isolate the effects of increased government health expenditure on morbidity-related, QALY gains. Clinical judgement informed the duration of health-related quality-of-life improvement from the annual increase in government health expenditure. The base-case reference ICER was estimated at AUD28,033 per QALY gained. Parametric uncertainty associated with the estimation of mortality- and morbidity-related QALYs generated a 95% confidence interval AUD20,758-37,667. Recent public summary documents suggest new technologies with ICERs above AUD40,000 per QALY gained are recommended for public funding. The empirical reference ICER reported in this article suggests more QALYs could be gained if resources were allocated to other forms of health spending.

Triangular and Trapezoidal Fuzzy State Estimation with Uncertainty on Measurements

Directory of Open Access Journals (Sweden)

Mohammad Sadeghi Sarcheshmah

2012-01-01

Full Text Available In this paper, a new method for uncertainty analysis in fuzzy state estimation is proposed. The uncertainty is expressed in measurements. Uncertainties in measurements are modelled with different fuzzy membership functions (triangular and trapezoidal. To find the fuzzy distribution of any state variable, the problem is formulated as a constrained linear programming (LP optimization. The viability of the proposed method would be verified with the ones obtained from the weighted least squares (WLS and the fuzzy state estimation (FSE in the 6-bus system and in the IEEE-14 and 30 bus system.

Uncertainty of feedback and state estimation determines the speed of motor adaptation

Directory of Open Access Journals (Sweden)

Kunlin Wei

2010-05-01

Full Text Available Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation.

State estimation for integrated vehicle dynamics control

NARCIS (Netherlands)

Zuurbier, J.; Bremmer, P.

2002-01-01

This paper discusses a vehicle controller and a state estimator that was implemented and tested in a vehicle equipped with a combined braking and chassis control system to improve handling. The vehicle dynamics controller consists of a feed forward body roll compensation and a feedback stability

The cost of universal health care in India: a model based estimate.

Science.gov (United States)

Prinja, Shankar; Bahuguna, Pankaj; Pinto, Andrew D; Sharma, Atul; Bharaj, Gursimer; Kumar, Vishal; Tripathy, Jaya Prasad; Kaur, Manmeet; Kumar, Rajesh

2012-01-01

As high out-of-pocket healthcare expenses pose heavy financial burden on the families, Government of India is considering a variety of financing and delivery options to universalize health care services. Hence, an estimate of the cost of delivering universal health care services is needed. We developed a model to estimate recurrent and annual costs for providing health services through a mix of public and private providers in Chandigarh located in northern India. Necessary health services required to deliver good quality care were defined by the Indian Public Health Standards. National Sample Survey data was utilized to estimate disease burden. In addition, morbidity and treatment data was collected from two secondary and two tertiary care hospitals. The unit cost of treatment was estimated from the published literature. For diseases where data on treatment cost was not available, we collected data on standard treatment protocols and cost of care from local health providers. We estimate that the cost of universal health care delivery through the existing mix of public and private health institutions would be INR 1713 (USD 38, 95%CI USD 18-73) per person per annum in India. This cost would be 24% higher, if branded drugs are used. Extrapolation of these costs to entire country indicates that Indian government needs to spend 3.8% (2.1%-6.8%) of the GDP for universalizing health care services. The cost of universal health care delivered through a combination of public and private providers is estimated to be INR 1713 per capita per year in India. Important issues such as delivery strategy for ensuring quality, reducing inequities in access, and managing the growth of health care demand need be explored.

Surveillance for Certain Health Behaviors, Chronic Diseases, and Conditions, Access to Health Care, and Use of Preventive Health Services Among States and Selected Local Areas
- Behavioral Risk Factor Surveillance System, United States, 2012.

Science.gov (United States)

Chowdhury, Pranesh P; Mawokomatanda, Tebitha; Xu, Fang; Gamble, Sonya; Flegel, David; Pierannunzi, Carol; Garvin, William; Town, Machell

2016-04-29

Chronic diseases (e.g., heart diseases, cancer, chronic lower respiratory disease, stroke, diabetes, and arthritis) and unintentional injuries are the leading causes of morbidity and mortality in the United States. Behavioral risk factors (e.g., tobacco use, poor diet, physical inactivity, excessive alcohol consumption, failure to use seat belts, and insufficient sleep) are linked to the leading causes of death. Modifying these behavioral risk factors and using preventive health services (e.g., cancer screenings and influenza and pneumococcal vaccination of adults aged ≥65 years) can substantially reduce morbidity and mortality in the U.S. Continuous monitoring of these health-risk behaviors, chronic conditions, and use of preventive services are essential to the development of health promotion strategies, intervention programs, and health policies at the state, city, and county level. January-December 2012. The Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit-dialed landline- and cellular-telephone survey of noninstitutionalized adults aged ≥18 years residing in the United States. BRFSS collects data on health-risk behaviors, chronic diseases and conditions, access to health care, and use of preventive health services related to the leading causes of death and disability. This report presents results for all 50 states, the District of Columbia, participating U.S. territories that include the Commonwealth of Puerto Rico (Puerto Rico) and Guam, 187 Metropolitan/Micropolitan Statistical Areas (MMSAs), and 210 counties (n = 475,687 survey respondents) for the year 2012. In 2012, the estimated prevalence of health-risk behaviors, chronic diseases or conditions, access to health care, and use of preventive health services substantially varied by state and territory, MMSA, and county. The following portion of the abstract lists a summary of results by selected BRFSS measures. Each set of proportions refers to the range of

State estimation of spatio-temporal phenomena

Science.gov (United States)

Yu, Dan

This dissertation addresses the state estimation problem of spatio-temporal phenomena which can be modeled by partial differential equations (PDEs), such as pollutant dispersion in the atmosphere. After discretizing the PDE, the dynamical system has a large number of degrees of freedom (DOF). State estimation using Kalman Filter (KF) is computationally intractable, and hence, a reduced order model (ROM) needs to be constructed first. Moreover, the nonlinear terms, external disturbances or unknown boundary conditions can be modeled as unknown inputs, which leads to an unknown input filtering problem. Furthermore, the performance of KF could be improved by placing sensors at feasible locations. Therefore, the sensor scheduling problem to place multiple mobile sensors is of interest. The first part of the dissertation focuses on model reduction for large scale systems with a large number of inputs/outputs. A commonly used model reduction algorithm, the balanced proper orthogonal decomposition (BPOD) algorithm, is not computationally tractable for large systems with a large number of inputs/outputs. Inspired by the BPOD and randomized algorithms, we propose a randomized proper orthogonal decomposition (RPOD) algorithm and a computationally optimal RPOD (RPOD*) algorithm, which construct an ROM to capture the input-output behaviour of the full order model, while reducing the computational cost of BPOD by orders of magnitude. It is demonstrated that the proposed RPOD* algorithm could construct the ROM in real-time, and the performance of the proposed algorithms on different advection-diffusion equations. Next, we consider the state estimation problem of linear discrete-time systems with unknown inputs which can be treated as a wide-sense stationary process with rational power spectral density, while no other prior information needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input

Standard error of measurement of five health utility indexes across the range of health for use in estimating reliability and responsiveness

Science.gov (United States)

Palta, Mari; Chen, Han-Yang; Kaplan, Robert M.; Feeny, David; Cherepanov, Dasha; Fryback, Dennis

2011-01-01

Background Standard errors of measurement (SEMs) of health related quality of life (HRQoL) indexes are not well characterized. SEM is needed to estimate responsiveness statistics and provides guidance on using indexes on the individual and group level. SEM is also a component of reliability. Purpose To estimate SEM of five HRQoL indexes. Design The National Health Measurement Study (NHMS) was a population based telephone survey. The Clinical Outcomes and Measurement of Health Study (COMHS) provided repeated measures 1 and 6 months post cataract surgery. Subjects 3844 randomly selected adults from the non-institutionalized population 35 to 89 years old in the contiguous United States and 265 cataract patients. Measurements The SF6-36v2™, QWB-SA, EQ-5D, HUI2 and HUI3 were included. An item-response theory (IRT) approach captured joint variation in indexes into a composite construct of health (theta). We estimated: (1) the test-retest standard deviation (SEM-TR) from COMHS, (2) the structural standard deviation (SEM-S) around the composite construct from NHMS and (3) corresponding reliability coefficients. Results SEM-TR was 0.068 (SF-6D), 0.087 (QWB-SA), 0.093 (EQ-5D), 0.100 (HUI2) and 0.134 (HUI3), while SEM-S was 0.071, 0.094, 0.084, 0.074 and 0.117, respectively. These translate into reliability coefficients for SF-6D: 0.66 (COMHS) and 0.71 (NHMS), for QWB: 0.59 and 0.64, for EQ-5D: 0.61 and 0.70 for HUI2: 0.64 and 0.80, and for HUI3: 0.75 and 0.77, respectively. The SEM varied considerably across levels of health, especially for HUI2, HUI3 and EQ-5D, and was strongly influenced by ceiling effects. Limitations Repeated measures were five months apart and estimated theta contain measurement error. Conclusions The two types of SEM are similar and substantial for all the indexes, and vary across the range of health. PMID:20935280

The North Carolina State Health Plan for Teachers and State Employees: Strategies in Creating Financial Stability While Improving Member Health.

Science.gov (United States)

Jones, Dee; Horner, Beth

2018-01-01

The North Carolina State Health Plan provides health care coverage to more than 700,000 members, including teachers, state employees, retirees, current and former lawmakers, state university and community college personnel, and their dependents. The State Health Plan is a division of the North Carolina Department of State Treasurer, self-insured, and exempt from the Employee Retirement Income Security Act as a government-sponsored plan. With health care costs rising at rates greater than funding, the Plan must take measures to stem cost growth while ensuring access to quality health care. The Plan anticipates focusing on strategic initiatives that drive results and cost savings while improving member health to protect the Plan's financial future. ©2018 by the North Carolina Institute of Medicine and The Duke Endowment. All rights reserved.

Study of the Convergence in State Estimators for LTI Systems with Event Detection

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Juan C. Posada

2016-01-01

Full Text Available The methods frequently used to estimate the state of an LTI system require that the precise value of the output variable is known at all times, or at equidistant sampling times. In LTI systems, in which the output signal is measured through binary sensors (detectors, the traditional way of state observers design is not applicable even though the system has a complete observability matrix. This type of state observers design is known as passive. It is necessary, then, to introduce a new state estimation technique, which allows reckoning the state from the information of the variable’s crossing through a detector’s action threshold (switch. This paper seeks, therefore, to study the convergence in this type of estimators in finite time, allowing establishing, theoretically, whether some family of the proposed models can be estimated in a convergent way through the use of the estimation technique based on events.

Discrete-time state estimation for stochastic polynomial systems over polynomial observations

Science.gov (United States)

Hernandez-Gonzalez, M.; Basin, M.; Stepanov, O.

2018-07-01

This paper presents a solution to the mean-square state estimation problem for stochastic nonlinear polynomial systems over polynomial observations confused with additive white Gaussian noises. The solution is given in two steps: (a) computing the time-update equations and (b) computing the measurement-update equations for the state estimate and error covariance matrix. A closed form of this filter is obtained by expressing conditional expectations of polynomial terms as functions of the state estimate and error covariance. As a particular case, the mean-square filtering equations are derived for a third-degree polynomial system with second-degree polynomial measurements. Numerical simulations show effectiveness of the proposed filter compared to the extended Kalman filter.

Monitoring maternal, newborn, and child health interventions using lot quality assurance sampling in Sokoto State of northern Nigeria.

Science.gov (United States)

Abegunde, Dele; Orobaton, Nosa; Shoretire, Kamil; Ibrahim, Mohammed; Mohammed, Zainab; Abdulazeez, Jumare; Gwamzhi, Ringpon; Ganiyu, Akeem

2015-01-01

Maternal mortality ratio and infant mortality rate are as high as 1,576 per 100,000 live births and 78 per 1,000 live births, respectively, in Nigeria's northwestern region, where Sokoto State is located. Using applicable monitoring indicators for tracking progress in the UN/WHO framework on continuum of maternal, newborn, and child health care, this study evaluated the progress of Sokoto toward achieving the Millennium Development Goals (MDGs) 4 and 5 by December 2015. The changes in outcomes in 2012-2013 associated with maternal and child health interventions were assessed. We used baseline and follow-up lot quality assurance sampling (LQAS) data obtained in 2012 and 2013, respectively. In each of the surveys, data were obtained from 437 households sampled from 19 LQAS locations in each of the 23 local government areas (LGAs). The composite state-level coverage estimates of the respective indicators were aggregated from estimated LGA coverage estimates. None of the nine indicators associated with the continuum of maternal, neonatal, and child care satisfied the recommended 90% coverage target for achieving MDGs 4 and 5. Similarly, the average state coverage estimates were lower than national coverage estimates. Marginal improvements in coverage were obtained in the demand for family planning satisfied, antenatal care visits, postnatal care for mothers, and exclusive breast-feeding. Antibiotic treatment for acute pneumonia increased significantly by 12.8 percentage points. The majority of the LGAs were classifiable as low-performing, high-priority areas for intensified program intervention. Despite the limited time left in the countdown to December 2015, Sokoto State, Nigeria, is not on track to achieving the MDG 90% coverage of indicators tied to the continuum of maternal and child care, to reduce maternal and childhood mortality by a third by 2015. Targeted health system investments at the primary care level remain a priority, for intensive program scale-up to

Lithium-Ion Battery Online Rapid State-of-Power Estimation under Multiple Constraints

Directory of Open Access Journals (Sweden)

Shun Xiang

2018-01-01

Full Text Available The paper aims to realize a rapid online estimation of the state-of-power (SOP with multiple constraints of a lithium-ion battery. Firstly, based on the improved first-order resistance-capacitance (RC model with one-state hysteresis, a linear state-space battery model is built; then, using the dual extended Kalman filtering (DEKF method, the battery parameters and states, including open-circuit voltage (OCV, are estimated. Secondly, by employing the estimated OCV as the observed value to build the second dual Kalman filters, the battery SOC is estimated. Thirdly, a novel rapid-calculating peak power/SOP method with multiple constraints is proposed in which, according to the bisection judgment method, the battery’s peak state is determined; then, one or two instantaneous peak powers are used to determine the peak power during T seconds. In addition, in the battery operating process, the actual constraint that the battery is under is analyzed specifically. Finally, three simplified versions of the Federal Urban Driving Schedule (SFUDS with inserted pulse experiments are conducted to verify the effectiveness and accuracy of the proposed online SOP estimation method.

World Health Organization Member States and Open Health Data: An Observational Study

Directory of Open Access Journals (Sweden)

Charles J Greenberg

2016-09-01

Full Text Available Background Open health data has implications for clinical care, research, public health, and health policy at regional, national, and global levels. No published attempts have been made to determine, collectively, whether WHO member states and governments have embraced the promise and effort required to officially share open health data. The observational study will provide evidence that World Health Organization (WHO member states individually and collectively have adopted open data recommended principles, providing access to open health data. Methods Using the WHO list of member states (n=194, the researchers identified the presence of open health data or initiatives. With each country, the following types of official government web pages were recorded: a Ministry of Health web page; a conspicuous link on a government web page to open health data; additional government health web sites; national government-sponsored open data repositories; unique attributes of national health data web sites; and adherence to the principles of open government data for health. A supplemental PDF file provides a representation of data used for analysis and observations. Our complete data is available at: https://goo.gl/Kwj7mb Observations and Discussion Open health data is easily discoverable in less than one-third of the WHO member states. 13 nations demonstrate the principle to provide comprehensive open data. Only 16 nations distribute primary, non-aggregated health data. 24 % of the WHO observed member states are providing some health data in a non-proprietary formats such as comma-separated values. The sixth, seventh, and eighth open government data principles for health, representing universal access, non-proprietary formats, and non-patent protection, are observed in about one-third of the WHO member states. While there are examples of organized national open health data, no more than a one-third minority of the world’s nations have portals set up to

State health managers' perceptions of the Public Health Action Organizational Contract in the State of Ceará, Brazil.

Science.gov (United States)

Goya, Neusa; Andrade, Luiz Odorico Monteiro de; Pontes, Ricardo José Soares; Tajra, Fábio Solon; Barreto, Ivana Cristina de Holanda Cunha

2017-04-01

The Public Health Action Organizational Contract (COAP) / Decree 7.508/2011 aimed to seal health agreements made between federated entities to promote the cooperative governance and management of Health Regions. A qualitative study was carried out adopting a hermeneutic approach to understand state health managers' perceptions of the elaboration and effects of the COAP in the State of Ceará. Open-ended interviewees and documental analysis were conducted. It was observed that the COAP led to the strengthening of regionalization in the government sphere; institutional gains through the implementation of ombudsmen and the National System of Pharmaceutical Care Management; increased information about the state health system's workforce; and health budget transparency. The following problems were (re)visited: institutional weakness in the operation of the network; limited state capacity for regulation of care; and underfunding. Regional governance was restricted to the government sphere, coordinated by the state, and was characterized by a predominantly bureaucratic and hierarchical governance structure. The COAP inaugurated a contractual interfederative model of regionalization, but revealed the institutional weaknesses of the SUS and its lacks of capacity to fulfill its principles as the structural problems of the three-tiered model go unaddressed.

Dynamic state estimation techniques for large-scale electric power systems

International Nuclear Information System (INIS)

Rousseaux, P.; Pavella, M.

1991-01-01

This paper presents the use of dynamic type state estimators for energy management in electric power systems. Various dynamic type estimators have been developed, but have never been implemented. This is primarily because of dimensionality problems posed by the conjunction of an extended Kalman filter with a large scale power system. This paper precisely focuses on how to circumvent the high dimensionality, especially prohibitive in the filtering step, by using a decomposition-aggregation hierarchical scheme; to appropriately model the power system dynamics, the authors introduce new state variables in the prediction step and rely on a load forecasting method. The combination of these two techniques succeeds in solving the overall dynamic state estimation problem not only in a tractable and realistic way, but also in compliance with real-time computational requirements. Further improvements are also suggested, bound to the specifics of the high voltage electric transmission systems

Real-time measurements and their effects on state estimation of distribution power system

DEFF Research Database (Denmark)

Han, Xue; You, Shi; Thordarson, Fannar

2013-01-01

between the estimated values (voltage and injected power) and the measurements are applied to evaluate the accuracy of the estimated grid states. Eventually, some suggestions are provided for the distribution grid operators on placing the real-time meters in the distribution grid.......This paper aims at analyzing the potential value of using different real-time metering and measuring instruments applied in the low voltage distribution networks for state-estimation. An algorithm is presented to evaluate different combinations of metering data using a tailored state estimator....... It is followed by a case study based on the proposed algorithm. A real distribution grid feeder with different types of meters installed either in the cabinets or at the customer side is selected for simulation and analysis. Standard load templates are used to initiate the state estimation. The deviations...

Method for Estimating Water Withdrawals for Livestock in the United States, 2005

Science.gov (United States)

Lovelace, John K.

2009-01-01

Livestock water use includes ground water and surface water associated with livestock watering, feedlots, dairy operations, and other on-farm needs. The water may be used for drinking, cooling, sanitation, waste disposal, and other needs related to the animals. Estimates of water withdrawals for livestock are needed for water planning and management. This report documents a method used to estimate withdrawals of fresh ground water and surface water for livestock in 2005 for each county and county equivalent in the United States, Puerto Rico, and the U.S. Virgin Islands. Categories of livestock included dairy cattle, beef and other cattle, hogs and pigs, laying hens, broilers and other chickens, turkeys, sheep and lambs, all goats, and horses (including ponies, mules, burros, and donkeys). Use of the method described in this report could result in more consistent water-withdrawal estimates for livestock that can be used by water managers and planners to determine water needs and trends across the United States. Water withdrawals for livestock in 2005 were estimated by using water-use coefficients, in gallons per head per day for each animal type, and livestock-population data. Coefficients for various livestock for most States were obtained from U.S. Geological Survey water-use program personnel or U.S. Geological Survey water-use publications. When no coefficient was available for an animal type in a State, the median value of reported coefficients for that animal was used. Livestock-population data were provided by the National Agricultural Statistics Service. County estimates were further divided into ground-water and surface-water withdrawals for each county and county equivalent. County totals from 2005 were compared to county totals from 1995 and 2000. Large deviations from 1995 or 2000 livestock withdrawal estimates were investigated and generally were due to comparison with reported withdrawals, differences in estimation techniques, differences in livestock

The cost of universal health care in India: a model based estimate.

Directory of Open Access Journals (Sweden)

Shankar Prinja

Full Text Available INTRODUCTION: As high out-of-pocket healthcare expenses pose heavy financial burden on the families, Government of India is considering a variety of financing and delivery options to universalize health care services. Hence, an estimate of the cost of delivering universal health care services is needed. METHODS: We developed a model to estimate recurrent and annual costs for providing health services through a mix of public and private providers in Chandigarh located in northern India. Necessary health services required to deliver good quality care were defined by the Indian Public Health Standards. National Sample Survey data was utilized to estimate disease burden. In addition, morbidity and treatment data was collected from two secondary and two tertiary care hospitals. The unit cost of treatment was estimated from the published literature. For diseases where data on treatment cost was not available, we collected data on standard treatment protocols and cost of care from local health providers. RESULTS: We estimate that the cost of universal health care delivery through the existing mix of public and private health institutions would be INR 1713 (USD 38, 95%CI USD 18-73 per person per annum in India. This cost would be 24% higher, if branded drugs are used. Extrapolation of these costs to entire country indicates that Indian government needs to spend 3.8% (2.1%-6.8% of the GDP for universalizing health care services. CONCLUSION: The cost of universal health care delivered through a combination of public and private providers is estimated to be INR 1713 per capita per year in India. Important issues such as delivery strategy for ensuring quality, reducing inequities in access, and managing the growth of health care demand need be explored.

Income, Poverty, and Health Insurance Coverage in the United States: 2012. Current Population Reports P60-245

Science.gov (United States)

DeNavas-Walt, Carmen; Proctor, Bernadette D.; Smith, Jessica C.

2013-01-01

This report presents data on income, poverty, and health insurance coverage in the United States based on information collected in the 2013 and earlier Current Population Survey Annual Social and Economic Supplements (CPS ASEC) conducted by the U.S. Census Bureau. For most groups, the 2012 income, poverty, and health insurance estimates were not…

Health Service Areas (HSAs) - Small Area Estimates

Science.gov (United States)

Health Service Areas (HSAs) are a compromise between the 3000 counties and the 50 states. An HSA may be thought of as an area that is relatively self-contained with respect to hospital care and may cross over state boundries.

Assessing concentrations and health impacts of air quality management strategies: Framework for Rapid Emissions Scenario and Health impact ESTimation (FRESH-EST).

Science.gov (United States)

Milando, Chad W; Martenies, Sheena E; Batterman, Stuart A

2016-09-01

In air quality management, reducing emissions from pollutant sources often forms the primary response to attaining air quality standards and guidelines. Despite the broad success of air quality management in the US, challenges remain. As examples: allocating emissions reductions among multiple sources is complex and can require many rounds of negotiation; health impacts associated with emissions, the ultimate driver for the standards, are not explicitly assessed; and long dispersion model run-times, which result from the increasing size and complexity of model inputs, limit the number of scenarios that can be evaluated, thus increasing the likelihood of missing an optimal strategy. A new modeling framework, called the "Framework for Rapid Emissions Scenario and Health impact ESTimation" (FRESH-EST), is presented to respond to these challenges. FRESH-EST estimates concentrations and health impacts of alternative emissions scenarios at the urban scale, providing efficient computations from emissions to health impacts at the Census block or other desired spatial scale. In addition, FRESH-EST can optimize emission reductions to meet specified environmental and health constraints, and a convenient user interface and graphical displays are provided to facilitate scenario evaluation. The new framework is demonstrated in an SO2 non-attainment area in southeast Michigan with two optimization strategies: the first minimizes emission reductions needed to achieve a target concentration; the second minimizes concentrations while holding constant the cumulative emissions across local sources (e.g., an emissions floor). The optimized strategies match outcomes in the proposed SO2 State Implementation Plan without the proposed stack parameter modifications or shutdowns. In addition, the lower health impacts estimated for these strategies suggest that FRESH-EST could be used to identify potentially more desirable pollution control alternatives in air quality management planning

[The state and health insurance].

Science.gov (United States)

Lagrave, Michel

2003-01-01

The relationship between the State and the health insurance passes through an institutional and financial crisis, leading the government to decide a new governance of the health care system and of the health insurance. The onset of the institutional crisis is the consequence of the confusion of the roles played by the State and the social partners. The social democracy installed by the French plan in 1945 and the autonomy of management of the health insurance established by the 1967 ordinances have failed. The administration parity (union and MEDEF) flew into pieces. The State had to step in by failing. The light is put on the financial crisis by the evolution of ONDAM (National Objective of the Health Insurance Expenses) which appears in the yearly law financing Social Security. The drift of the real expenses as compared to the passed ONDAM bill is constant and worsening. The question of reform includes the link between social democracy to be restored (social partners) and political democracy (Parliament and Government) to establish a contractual democracy. The Government made the announcement of an ONDAM sincere and medically oriented, based on tools agreed upon by all parties. The region could become a regulating step involving a regional health council. An accounting magistrate would be needed to consider not only the legal aspect but to include economic fallouts of health insurance. The role and the missions of the Social Security Accounting Committee should be reinforced.

Assembling GHERG: Could "academic crowd-sourcing" address gaps in global health estimates?

Science.gov (United States)

Rudan, Igor; Campbell, Harry; Marušić, Ana; Sridhar, Devi; Nair, Harish; Adeloye, Davies; Theodoratou, Evropi; Chan, Kit Yee

2015-06-01

In recent months, the World Health Organization (WHO), independent academic researchers, the Lancet and PLoS Medicine journals worked together to improve reporting of population health estimates. The new guidelines for accurate and transparent health estimates reporting (likely to be named GATHER), which are eagerly awaited, represent a helpful move that should benefit the field of global health metrics. Building on this progress and drawing from a tradition of Child Health Epidemiology Reference Group (CHERG)'s successful work model, we would like to propose a new initiative - "Global Health Epidemiology Reference Group" (GHERG). We see GHERG as an informal and entirely voluntary international collaboration of academic groups who are willing to contribute to improving disease burden estimates and respect the principles of the new guidelines - a form of "academic crowd-sourcing". The main focus of GHERG will be to identify the "gap areas" where not much information is available and/or where there is a lot of uncertainty present about the accuracy of the existing estimates. This approach should serve to complement the existing WHO and IHME estimates and to represent added value to both efforts.

Comparing cancer screening estimates: Behavioral Risk Factor Surveillance System and National Health Interview Survey.

Science.gov (United States)

Sauer, Ann Goding; Liu, Benmei; Siegel, Rebecca L; Jemal, Ahmedin; Fedewa, Stacey A

2018-01-01

Cancer screening prevalence from the Behavioral Risk Factor Surveillance System (BRFSS), designed to provide state-level estimates, and the National Health Interview Survey (NHIS), designed to provide national estimates, are used to measure progress in cancer control. A detailed description of the extent to which recent cancer screening estimates vary by key demographic characteristics has not been previously described. We examined national prevalence estimates for recommended breast, cervical, and colorectal cancer screening using data from the 2012 and 2014 BRFSS and the 2010 and 2013 NHIS. Treating the NHIS estimates as the reference, direct differences (DD) were calculated by subtracting NHIS estimates from BRFSS estimates. Relative differences were computed by dividing the DD by the NHIS estimates. Two-sample t-tests (2-tails), were performed to test for statistically significant differences. BRFSS screening estimates were higher than those from NHIS for breast (78.4% versus 72.5%; DD=5.9%, pNHIS, each survey has a unique and important role in providing information to track cancer screening utilization among various populations. Awareness of these differences and their potential causes is important when comparing the surveys and determining the best application for each data source. Copyright © 2017 Elsevier Inc. All rights reserved.

Resting State Network Estimation in Individual Subjects

Science.gov (United States)

Hacker, Carl D.; Laumann, Timothy O.; Szrama, Nicholas P.; Baldassarre, Antonello; Snyder, Abraham Z.

2014-01-01

Resting-state functional magnetic resonance imaging (fMRI) has been used to study brain networks associated with both normal and pathological cognitive function. The objective of this work is to reliably compute resting state network (RSN) topography in single participants. We trained a supervised classifier (multi-layer perceptron; MLP) to associate blood oxygen level dependent (BOLD) correlation maps corresponding to pre-defined seeds with specific RSN identities. Hard classification of maps obtained from a priori seeds was highly reliable across new participants. Interestingly, continuous estimates of RSN membership retained substantial residual error. This result is consistent with the view that RSNs are hierarchically organized, and therefore not fully separable into spatially independent components. After training on a priori seed-based maps, we propagated voxel-wise correlation maps through the MLP to produce estimates of RSN membership throughout the brain. The MLP generated RSN topography estimates in individuals consistent with previous studies, even in brain regions not represented in the training data. This method could be used in future studies to relate RSN topography to other measures of functional brain organization (e.g., task-evoked responses, stimulation mapping, and deficits associated with lesions) in individuals. The multi-layer perceptron was directly compared to two alternative voxel classification procedures, specifically, dual regression and linear discriminant analysis; the perceptron generated more spatially specific RSN maps than either alternative. PMID:23735260

Estimating small area health-related characteristics of populations: a methodological review

Directory of Open Access Journals (Sweden)

Azizur Rahman

2017-05-01

Full Text Available Estimation of health-related characteristics at a fine local geographic level is vital for effective health promotion programmes, provision of better health services and population-specific health planning and management. Lack of a micro-dataset readily available for attributes of individuals at small areas negatively impacts the ability of local and national agencies to manage serious health issues and related risks in the community. A solution to this challenge would be to develop a method that simulates reliable small-area statistics. This paper provides a significant appraisal of the methodologies for estimating health-related characteristics of populations at geographical limited areas. Findings reveal that a range of methodologies are in use, which can be classified as three distinct set of approaches: i indirect standardisation and individual level modelling; ii multilevel statistical modelling; and iii micro-simulation modelling. Although each approach has its own strengths and weaknesses, it appears that microsimulation- based spatial models have significant robustness over the other methods and also represent a more precise means of estimating health-related population characteristics over small areas.

Estimating Air Pollution Removal Through an Analysis of Vegetation Communities in Government Canyon State Natural Area

Science.gov (United States)

Medrano, Nicolas W.

Ambient air pollution is a major issue in urban environments, causing negative health impacts and increasing costs for metropolitan economies. Vegetation has been shown to remove these pollutants at a substantial rate. This study utilizes the i-Tree Eco (UFORE) and i-Tree Canopy models to estimate air pollution removal services provided by trees in Government Canyon State Natural Area (GCSNA), an approximately 4,700 hectare area in San Antonio, Texas. For i-Tree Eco, a stratified project of the five prominent vegetation types was completed. A comparison of removal services provided by vegetation communities indicated there was no significant difference in removal rates. Total pollution removal of GCSNA was estimated to be 239.52 metric tons/year at a rate of 64.42 kg/ha of tree cover/year. By applying this value to the area within Bexar County, Texas belonging to the Balcones Canyonlands ecoregion, it was determined that for 2013 an estimated 2,598.45 metric tons/year of air pollution was removed at a health value to society of 19.4 million. This is a reduction in pollution removal services since 2003, in which 3,050.35 metric tons/year were removed at a health value of 22.8 million. These results suggest urban sprawl taking place in San Antonio is reducing air pollution removal services provided by trees.

State estimation and control for low-cost unmanned aerial vehicles

CERN Document Server

Hajiyev, Chingiz; Yenal Vural, Sıtkı

2015-01-01

This book discusses state estimation and control procedures for a low-cost unmanned aerial vehicle (UAV). The authors consider the use of robust adaptive Kalman filter algorithms and demonstrate their advantages over the optimal Kalman filter in the context of the difficult and varied environments in which UAVs may be employed. Fault detection and isolation (FDI) and data fusion for UAV air-data systems are also investigated, and control algorithms, including the classical, optimal, and fuzzy controllers, are given for the UAV. The performance of different control methods is investigated and the results compared. State Estimation and Control of Low-Cost Unmanned Aerial Vehicles covers all the important issues for designing a guidance, navigation and control (GNC) system of a low-cost UAV. It proposes significant new approaches that can be exploited by GNC system designers in the future and also reviews the current literature. The state estimation, control and FDI methods are illustrated by examples and MATLAB...

Health manpower development in Bayelsa State, Nigeria

Directory of Open Access Journals (Sweden)

McFubara KG

2012-11-01

Full Text Available Kalada G McFubara,1 Elizabeth R Edoni,2 Rose E Ezonbodor-Akwagbe21Department of Community Medicine, Faculty of Clinical Sciences, 2Department of Community Health Nursing, Niger Delta University, Wilberforce Island, NigeriaBackground: Health manpower is one of the critical factors in the development of a region. This is because health is an index of development. Bayelsa State has a low level of health manpower. Thus, in this study, we sought to identify factors necessary for effective development of health manpower.Methods: Three methods were used to gather information, ie, face-to-face interviews, postal surveys, and documentary analysis. Critical incidents were identified, and content and thematic analyses were conducted.Results: There is no full complement of a primary health care workforce in any of the health centers in the state. The three health manpower training institutions have the limitations of inadequate health care educators and other manpower training facilities, including lack of a teaching hospital.Conclusion: Accreditation of health manpower training institutions is a major factor for effective development of health manpower. Public officers can contribute to the accreditation process by subsuming their personal interest into the state's common interest. Bayelsa is a fast-growing state and needs a critical mass of health care personnel. To develop this workforce requires a conscious effort rich in common interests in the deployment of resources.Keywords: health manpower, development, health care education

Use estimates of in-feed antimicrobials in swine production in the United States.

Science.gov (United States)

Apley, Michael D; Bush, Eric J; Morrison, Robert B; Singer, Randall S; Snelson, Harry

2012-03-01

When considering the development of antimicrobial resistance in food animals, comparing gross use estimates of different antimicrobials is of little value due to differences in potencies, duration of activity, relative effect on target and commensal bacteria, and mechanisms of resistance. However, it may be valuable to understand quantities of different antimicrobials used in different ages of swine and for what applications. Therefore, the objective of this project was to construct an estimate of antimicrobial use through the feed in swine production in the United States. Estimates were based on data from the National Animal Health Monitoring System (NAHMS) Swine 2006 Study and from a 2009 survey of swine-exclusive practitioners. Inputs consisted of number of pigs in a production phase, feed intake per day, dose of the antimicrobial in the feed, and duration of administration. Calculations were performed for a total of 102 combinations of antimicrobials (n=17), production phases (n=2), and reasons for use (n=3). Calculations were first conducted on farm-level data, and then extrapolated to the U.S. swine population. Among the nursery phase estimates, chlortetracycline had the largest estimate of use, followed by oxytetracycline and tilmicosin. In the grower/finisher phase, chlortetracycline also had the largest use estimate, followed by tylosin and oxytetracycline. As an annual industry estimate for all phases, chlortetracycline had the highest estimated use at 533,973 kg. The second and third highest estimates were tylosin and oxytetracycline with estimated annual uses of 165,803 kg and 154,956 kg, respectively. The estimates presented here were constructed to accurately reflect available data related to production practices, and to provide an example of a scientific approach to estimating use of compounds in production animals.

Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering

KAUST Repository

El Gharamti, Mohamad

2013-10-01

Modeling the spread of subsurface contaminants requires coupling a groundwater flow model with a contaminant transport model. Such coupling may provide accurate estimates of future subsurface hydrologic states if essential flow and contaminant data are assimilated in the model. Assuming perfect flow, an ensemble Kalman filter (EnKF) can be used for direct data assimilation into the transport model. This is, however, a crude assumption as flow models can be subject to many sources of uncertainty. If the flow is not accurately simulated, contaminant predictions will likely be inaccurate even after successive Kalman updates of the contaminant model with the data. The problem is better handled when both flow and contaminant states are concurrently estimated using the traditional joint state augmentation approach. In this paper, we introduce a dual estimation strategy for data assimilation into a one-way coupled system by treating the flow and the contaminant models separately while intertwining a pair of distinct EnKFs, one for each model. The presented strategy only deals with the estimation of state variables but it can also be used for state and parameter estimation problems. This EnKF-based dual state-state estimation procedure presents a number of novel features: (i) it allows for simultaneous estimation of both flow and contaminant states in parallel; (ii) it provides a time consistent sequential updating scheme between the two models (first flow, then transport); (iii) it simplifies the implementation of the filtering system; and (iv) it yields more stable and accurate solutions than does the standard joint approach. We conducted synthetic numerical experiments based on various time stepping and observation strategies to evaluate the dual EnKF approach and compare its performance with the joint state augmentation approach. Experimental results show that on average, the dual strategy could reduce the estimation error of the coupled states by 15% compared with the

Support vector machines for nuclear reactor state estimation

Energy Technology Data Exchange (ETDEWEB)

Zavaljevski, N.; Gross, K. C.

2000-02-14

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformed into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear power reactors. In particular, they implemented and tested kernels developed at Argonne National Laboratory for the Multivariate State Estimation Technique (MSET), a nonlinear, nonparametric estimation technique with a wide range of applications in nuclear reactors. The methodology has been applied to three data sets from experimental and commercial nuclear power reactor applications. The results are promising. The combination of MSET kernels with the SVM method has better noise reduction and generalization properties than the standard MSET algorithm.

Support vector machines for nuclear reactor state estimation

International Nuclear Information System (INIS)

Zavaljevski, N.; Gross, K. C.

2000-01-01

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformed into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear power reactors. In particular, they implemented and tested kernels developed at Argonne National Laboratory for the Multivariate State Estimation Technique (MSET), a nonlinear, nonparametric estimation technique with a wide range of applications in nuclear reactors. The methodology has been applied to three data sets from experimental and commercial nuclear power reactor applications. The results are promising. The combination of MSET kernels with the SVM method has better noise reduction and generalization properties than the standard MSET algorithm

Hybrid fuzzy charged system search algorithm based state estimation in distribution networks

Directory of Open Access Journals (Sweden)

Sachidananda Prasad

2017-06-01

Full Text Available This paper proposes a new hybrid charged system search (CSS algorithm based state estimation in radial distribution networks in fuzzy framework. The objective of the optimization problem is to minimize the weighted square of the difference between the measured and the estimated quantity. The proposed method of state estimation considers bus voltage magnitude and phase angle as state variable along with some equality and inequality constraints for state estimation in distribution networks. A rule based fuzzy inference system has been designed to control the parameters of the CSS algorithm to achieve better balance between the exploration and exploitation capability of the algorithm. The efficiency of the proposed fuzzy adaptive charged system search (FACSS algorithm has been tested on standard IEEE 33-bus system and Indian 85-bus practical radial distribution system. The obtained results have been compared with the conventional CSS algorithm, weighted least square (WLS algorithm and particle swarm optimization (PSO for feasibility of the algorithm.

Modeling Per Capita State Health Expenditure Variat...

Data.gov (United States)

U.S. Department of Health & Human Services — Modeling Per Capita State Health Expenditure Variation State-Level Characteristics Matter, published in Volume 3, Issue 4, of the Medicare and Medicaid Research...

How School Healthy Is Your State? a State-by-State Comparison of School Health Practices Related to a Healthy School Environment and Health Education

Science.gov (United States)

Brener, Nancy D.; Wechsler, Howell; McManus, Tim

2013-01-01

Background: School Health Profiles (Profiles) results help states understand how they compare to each other on specific school health policies and practices. The purpose of this study was to develop composite measures of critical Profiles results and use them to rate each state on their overall performance. Methods: Using data from state Profiles…

A Best-Estimate Reactor Core Monitor Using State Feedback Strategies to Reduce Uncertainties

International Nuclear Information System (INIS)

Martin, Robert P.; Edwards, Robert M.

2000-01-01

The development and demonstration of a new algorithm to reduce modeling and state-estimation uncertainty in best-estimate simulation codes has been investigated. Demonstration is given by way of a prototype reactor core monitor. The architecture of this monitor integrates a control-theory-based, distributed-parameter estimation technique into a production-grade best-estimate simulation code. The Kalman Filter-Sequential Least-Squares (KFSLS) parameter estimation algorithm has been extended for application into the computational environment of the best-estimate simulation code RELAP5-3D. In control system terminology, this configuration can be thought of as a 'best-estimate' observer. The application to a distributed-parameter reactor system involves a unique modal model that approximates physical components, such as the reactor, by describing both states and parameters by an orthogonal expansion. The basic KFSLS parameter estimation is used to dynamically refine a spatially varying (distributed) parameter. The application of the distributed-parameter estimator is expected to complement a traditional nonlinear best-estimate simulation code by providing a mechanism for reducing both code input (modeling) and output (state-estimation) uncertainty in complex, distributed-parameter systems

The multiplier effect of the health education-risk reduction program in 28 states and 1 territory.

Science.gov (United States)

Kreuter, M W; Christensen, G M; Divincenzo, A

1982-01-01

The multiplier effect of the Health Education-Risk Reduction (HE-RR) Grants Program funded by the Public Health Service is examined to identify outcomes for the period 1978-81. Responses to a questionnaire from the directors of health education of 28 States and 1 Territory supplied the information concerning new health promotion activities generated by the program. The directors were asked to identify and give cost estimates of new activities that resulted from State-level and local intervention projects. A method for calculating the extent to which the HE-RR program influenced new health promotion activities that were funded by alternate sources was devised. The calculation, termed the new activity rate, was applied to the survey data. Rates calculated for the HE-RR program revealed that it generated nearly $4 million in new health promotion activities, most of them funded by the private and voluntary segments of society.

Response-based estimation of sea state parameters - Influence of filtering

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam

2007-01-01

Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The wave spectrum can be estimated from procedures based on measured ship responses. The paper deals with two procedures—Bayesian Modelling and Parametric Modelling...

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

2016-08-29

In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

Unknown author

2016-01-01

In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

U.S. Citizen Children of Undocumented Parents: The Link Between State Immigration Policy and the Health of Latino Children.

Science.gov (United States)

Vargas, Edward D; Ybarra, Vickie D

2017-08-01

We examine Latino citizen children in mixed-status families and how their physical health status compares to their U.S. citizen, co-ethnic counterparts. We also examine Latino parents' perceptions of state immigration policy and its implications for child health status. Using the 2015 Latino National Health and Immigration Survey (n = 1493), we estimate a series of multivariate ordered logistic regression models with mixed-status family and perceptions of state immigration policy as primary predictors. We find that mixed-status families report worse physical health for their children as compared to their U.S. citizen co-ethnics. We also find that parental perceptions of their states' immigration status further exacerbate health disparities between families. These findings have implications for scholars and policy makers interested in immigrant health, family wellbeing, and health disparities in complex family structures. They contribute to the scholarship on Latino child health and on the erosion of the Latino immigrant health advantage.

State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

Science.gov (United States)

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2016-04-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimates of the Resident Nonimmigrant Population in the United States: 2008

Data.gov (United States)

Department of Homeland Security — This report presents estimates on the size and characteristics of the resident nonimmigrant population in the United States in 2008.1 The estimates were based on...

Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

Science.gov (United States)

Lubey, D.; Scheeres, D.

Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal

[Potentials in the regionalization of health indicators using small-area estimation methods : Exemplary results based on the 2009, 2010 and 2012 GEDA studies].

Science.gov (United States)

Kroll, Lars Eric; Schumann, Maria; Müters, Stephan; Lampert, Thomas

2017-12-01

Nationwide health surveys can be used to estimate regional differences in health. Using traditional estimation techniques, the spatial depth for these estimates is limited due to the constrained sample size. So far - without special refreshment samples - results have only been available for larger populated federal states of Germany. An alternative is regression-based small-area estimation techniques. These models can generate smaller-scale data, but are also subject to greater statistical uncertainties because of the model assumptions. In the present article, exemplary regionalized results based on the studies "Gesundheit in Deutschland aktuell" (GEDA studies) 2009, 2010 and 2012, are compared to the self-rated health status of the respondents. The aim of the article is to analyze the range of regional estimates in order to assess the usefulness of the techniques for health reporting more adequately. The results show that the estimated prevalence is relatively stable when using different samples. Important determinants of the variation of the estimates are the achieved sample size on the district level and the type of the district (cities vs. rural regions). Overall, the present study shows that small-area modeling of prevalence is associated with additional uncertainties compared to conventional estimates, which should be taken into account when interpreting the corresponding findings.

Novel point estimation from a semiparametric ratio estimator (SPRE): long-term health outcomes from short-term linear data, with application to weight loss in obesity.

Science.gov (United States)

Weissman-Miller, Deborah

2013-11-02

Point estimation is particularly important in predicting weight loss in individuals or small groups. In this analysis, a new health response function is based on a model of human response over time to estimate long-term health outcomes from a change point in short-term linear regression. This important estimation capability is addressed for small groups and single-subject designs in pilot studies for clinical trials, medical and therapeutic clinical practice. These estimations are based on a change point given by parameters derived from short-term participant data in ordinary least squares (OLS) regression. The development of the change point in initial OLS data and the point estimations are given in a new semiparametric ratio estimator (SPRE) model. The new response function is taken as a ratio of two-parameter Weibull distributions times a prior outcome value that steps estimated outcomes forward in time, where the shape and scale parameters are estimated at the change point. The Weibull distributions used in this ratio are derived from a Kelvin model in mechanics taken here to represent human beings. A distinct feature of the SPRE model in this article is that initial treatment response for a small group or a single subject is reflected in long-term response to treatment. This model is applied to weight loss in obesity in a secondary analysis of data from a classic weight loss study, which has been selected due to the dramatic increase in obesity in the United States over the past 20 years. A very small relative error of estimated to test data is shown for obesity treatment with the weight loss medication phentermine or placebo for the test dataset. An application of SPRE in clinical medicine or occupational therapy is to estimate long-term weight loss for a single subject or a small group near the beginning of treatment.

Full State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

This paper presents the design of a state estimator system for a generic helicopter based slung load system. The estimator is designed to deliver full rigid body state information for both helicopter and load and is based on the unscented Kalman filter. Two different approaches are investigated......: One based on a parameter free kinematic model and one based on a full aerodynamic helicopter and slung load model. The kinematic model approach uses acceleration and rate information from two Inertial Measurement Units, one on the helicopter and one on the load, to drive a simple kinematic model....... A simple and effective virtual sensor method is developed to maintain the constraints imposed by the wires in the system. The full model based approach uses a complex aerodynamical model to describe the helicopter together with a generic rigid body model. This rigid body model is based on a redundant...

Full State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

2007-01-01

This paper presents the design of a state estimator system for a generic helicopter based slung load system. The estimator is designed to deliver full rigid body state information for both helicopter and load and is based on the unscented Kalman filter. Two different approaches are investigated......: One based on a parameter free kinematic model and one based on a full aerodynamic helicopter and slung load model. The kinematic model approach uses acceleration and rate information from two Inertial Measurement Units, one on the helicopter and one on the load, to drive a simple kinematic model....... A simple and effective virtual sensor method is developed to maintain the constraints imposed by the wires in the system. The full model based approach uses a complex aerodynamical model to describe the helicopter together with a generic rigid body model. This rigid body model is based on a redundant...

Automatic Regionalization Algorithm for Distributed State Estimation in Power Systems: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wang, Dexin; Yang, Liuqing; Florita, Anthony; Alam, S.M. Shafiul; Elgindy, Tarek; Hodge, Bri-Mathias

2016-08-01

The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.

Average State IQ, State Wealth and Racial Composition as Predictors of State Health Statistics: Partial Support for "g" as a Fundamental Cause of Health Disparities

Science.gov (United States)

Reeve, Charlie L.; Basalik, Debra

2010-01-01

This study examined the degree to which differences in average IQ across the 50 states was associated with differences in health statistics independent of differences in wealth, health care expenditures and racial composition. Results show that even after controlling for differences in state wealth and health care expenditures, average IQ had…

Dual extended Kalman filter for combined estimation of vehicle state and road friction

Science.gov (United States)

Zong, Changfu; Hu, Dan; Zheng, Hongyu

2013-03-01

Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, many estimation methods have been put forward to solve such problems, in which Kalman filter becomes one of the most popular techniques. Nevertheless, the use of complicated model always leads to poor real-time estimation while the role of road friction coefficient is often ignored. For the purpose of enhancing the real time performance of the algorithm and pursuing precise estimation of vehicle states, a model-based estimator is proposed to conduct combined estimation of vehicle states and road friction coefficients. The estimator is designed based on a three-DOF vehicle model coupled with the Highway Safety Research Institute(HSRI) tire model; the dual extended Kalman filter (DEKF) technique is employed, which can be regarded as two extended Kalman filters operating and communicating simultaneously. Effectiveness of the estimation is firstly examined by comparing the outputs of the estimator with the responses of the vehicle model in CarSim under three typical road adhesion conditions(high-friction, low-friction, and joint-friction). On this basis, driving simulator experiments are carried out to further investigate the practical application of the estimator. Numerical results from CarSim and driving simulator both demonstrate that the estimator designed is capable of estimating the vehicle states and road friction coefficient with reasonable accuracy. The DEKF-based estimator proposed provides the essential information for the vehicle active control system with low expense and decent precision, and offers the possibility of real car application in future.

State estimation of chemical engineering systems tending to multiple solutions

Directory of Open Access Journals (Sweden)

N. P. G. Salau

2014-09-01

Full Text Available A well-evaluated state covariance matrix avoids error propagation due to divergence issues and, thereby, it is crucial for a successful state estimator design. In this paper we investigate the performance of the state covariance matrices used in three unconstrained Extended Kalman Filter (EKF formulations and one constrained EKF formulation (CEKF. As benchmark case studies we have chosen: a a batch chemical reactor with reversible reactions whose system model and measurement are such that multiple states satisfy the equilibrium condition and b a CSTR with exothermic irreversible reactions and cooling jacket energy balance whose nonlinear behavior includes multiple steady-states and limit cycles. The results have shown that CEKF is in general the best choice of EKF formulations (even if they are constrained with an ad hoc clipping strategy which avoids undesired states for such case studies. Contrary to a clipped EKF formulation, CEKF incorporates constraints into an optimization problem, which minimizes the noise in a least square sense preventing a bad noise distribution. It is also shown that, although the Moving Horizon Estimation (MHE provides greater robustness to a poor guess of the initial state, converging in less steps to the actual states, it is not justified for our examples due to the high additional computational effort.

State estimation and synchronization of pendula systems over digital communication channels

Science.gov (United States)

Fradkov, A. L.; Andrievsky, B.; Ananyevskiy, M.

2014-04-01

The recent results on nonlinear systems synchronization and control under communication constraints are applied to the remote state estimation and synchronization for a class of exogenously excited nonlinear Lurie systems. State estimation of the chain of diffusively coupled pendulums over the digital communication channel with limited capacity is experimentally studied. Advantage of the adaptive coding procedure under the conditions of the plant model uncertainty and irregular disturbances is shown. Quality of the estimation is evaluated by means of the experiments with the multi-pendulum set-up. Experimental study of master-slave synchronization over network (local network, wireless network) for the system with two cart-pendulums is presented.

Estimated United States Transportation Energy Use 2005

Energy Technology Data Exchange (ETDEWEB)

Smith, C A; Simon, A J; Belles, R D

2011-11-09

A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.

Estimation of health effects due to elevated radiation exposure levels in structures

International Nuclear Information System (INIS)

Marks, S.; Cross, F.T.; Denham, D.H.; Kennedy, W.E. Jr.

1985-02-01

Uranium mill tailings were used as landfill for many years in the United States before the health risk associated with such use was recognized. Occupants of buildings erected on or adjacent to contaminated landfills may experience radiation exposures sufficient to warrant remedial action. Estimates of the cost-effectiveness of the remedial measures may be provided using a combination of occupancy data, appropriate risk coefficients and projected costs. This effort is in support of decisions by the US Department of Energy (DOE) to conduct remedial action at such locations. The methods used in this project, with examples of their application, will be presented in this paper

Monitoring maternal, newborn, and child health interventions using lot quality assurance sampling in Sokoto State of northern Nigeria

Directory of Open Access Journals (Sweden)

Dele Abegunde

2015-10-01

Full Text Available Background: Maternal mortality ratio and infant mortality rate are as high as 1,576 per 100,000 live births and 78 per 1,000 live births, respectively, in Nigeria's northwestern region, where Sokoto State is located. Using applicable monitoring indicators for tracking progress in the UN/WHO framework on continuum of maternal, newborn, and child health care, this study evaluated the progress of Sokoto toward achieving the Millennium Development Goals (MDGs 4 and 5 by December 2015. The changes in outcomes in 2012–2013 associated with maternal and child health interventions were assessed. Design: We used baseline and follow-up lot quality assurance sampling (LQAS data obtained in 2012 and 2013, respectively. In each of the surveys, data were obtained from 437 households sampled from 19 LQAS locations in each of the 23 local government areas (LGAs. The composite state-level coverage estimates of the respective indicators were aggregated from estimated LGA coverage estimates. Results: None of the nine indicators associated with the continuum of maternal, neonatal, and child care satisfied the recommended 90% coverage target for achieving MDGs 4 and 5. Similarly, the average state coverage estimates were lower than national coverage estimates. Marginal improvements in coverage were obtained in the demand for family planning satisfied, antenatal care visits, postnatal care for mothers, and exclusive breast-feeding. Antibiotic treatment for acute pneumonia increased significantly by 12.8 percentage points. The majority of the LGAs were classifiable as low-performing, high-priority areas for intensified program intervention. Conclusions: Despite the limited time left in the countdown to December 2015, Sokoto State, Nigeria, is not on track to achieving the MDG 90% coverage of indicators tied to the continuum of maternal and child care, to reduce maternal and childhood mortality by a third by 2015. Targeted health system investments at the primary care

State-Space Estimation of Soil Organic Carbon Stock

Science.gov (United States)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

Terrorism preparedness in state health departments--United States, 2001-2003.

Science.gov (United States)

2003-10-31

The anthrax attacks in fall 2001 highlighted the role of infectious disease (ID) epidemiologists in terrorism preparedness and response. Beginning in 2002, state health departments (SHDs) received approximately 1 billion dollars in new federal funding to prepare for and respond to terrorism, infectious disease outbreaks, and other public health threats and emergencies. This funding is being used in part to improve epidemiologic and surveillance capabilities. To determine how states have used a portion of their new funding to increase ID epidemiology capacity, the Iowa Department of Public Health's Center for Acute Disease Epidemiology and the Iowa State University Department of Microbiology conducted two surveys of U.S. state epidemiologists during September 2000-August 2001 and October 2002-June 2003. This report summarizes the results of these surveys, which determined that although the number of SHD epidemiology workers assigned to ID and terrorism preparedness increased by 132%, concerns remained regarding the ability of SHDs to hire qualified personnel. These findings underscore the need to develop additional and more diverse training venues for current and future ID epidemiologists.

Health spending by state of residence, 1991-2009.

Science.gov (United States)

Cuckler, Gigi; Martin, Anne; Whittle, Lekha; Heffler, Stephen; Sisko, Andrea; Lassman, Dave; Benson, Joseph

2011-12-06

Provide a detailed discussion of baseline health spending by state of residence (per capita personal health care spending, per enrollee Medicare spending, and per enrollee Medicaid spending) in 2009, over the last decade (1998-2009), as well as the differential regional and state impacts of the recent recession. State Health Expenditures by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. In 2009, the 10 states where per capita spending was highest ranged from 13 to 36 percent higher than the national average, and the 10 states where per capita spending was lowest ranged from 8 to 26 percent below the national average. States with the highest per capita spending tended to have older populations and the highest per capita incomes; states with the lowest per capita spending tended to have younger populations, lower per capita incomes, and higher rates of uninsured. Over the last decade, the New England and Mideast regions exhibited the highest per capita personal health care spending, while states in the Southwest and Rocky Mountain regions had the lowest per capita spending. Variation in per enrollee Medicaid spending, however, has consistently been greater than that of total per capita personal health care spending or per enrollee Medicare spending from 1998-2009. The Great Lakes, New England, and Far West regions experienced the largest slowdown in per person health spending growth during the recent recession, largely as a result of higher unemployment rates. Public Domain.

Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems

Directory of Open Access Journals (Sweden)

Feten Gannouni

2017-01-01

Full Text Available We consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF having an error variance with an optimized guaranteed upper bound for any allowed uncertainty is proposed to improve robust estimation of unknown time-varying faults and to improve robustness against uncertainties. In this study, the minimization problem of the upper bound of the estimation error variance is formulated as a convex optimization problem subject to linear matrix inequalities (LMI for all admissible uncertainties. The proportional and the integral gains are optimally chosen by solving the convex optimization problem. Simulation results are given in order to illustrate the performance of the proposed filter, in particular to solve the problem of joint fault and state estimation.

A Practical Circuit-based Model for State of Health Estimation of Li-ion Battery Cells in Electric Vehicles

Energy Technology Data Exchange (ETDEWEB)

Lam, Long

2011-08-23

In this thesis the development of the state of health of Li-ion battery cells under possible real-life operating conditions in electric cars has been characterised. Furthermore, a practical circuit-based model for Li-ion cells has been developed that is capable of modelling the cell voltage behaviour under various operating conditions. The Li-ion cell model can be implemented in simulation programs and be directly connected to a model of the rest of the electronic system in electric vehicles. Most existing battery models are impractical for electric vehicle system designers and require extensive background knowledge of electrochemistry to be implemented. Furthermore, many models do not take the effect of regenerative braking into account and are obtained from testing fully charged cells. However, in real-life applications electric vehicles are not always fully charged and utilise regenerative braking to save energy. To obtain a practical circuit model based on real operating conditions and to model the state of health of electric vehicle cells, numerous 18650 size LiFePO4 cells have been tested under possible operating conditions. Capacity fading was chosen as the state of health parameter, and the capacity fading of different cells was compared with the charge processed instead of cycles. Tests have shown that the capacity fading rate is dependent on temperature, charging C-rate, state of charge and depth of discharge. The obtained circuit model is capable of simulating the voltage behaviour under various temperatures and C-rates with a maximum error of 14mV. However, modelling the effect of different temperatures and C-rates increases the complexity of the model. The model is easily adjustable and the choice is given to the electric vehicle system designer to decide which operating conditions to take into account. By combining the test results for the capacity fading and the proposed circuit model, recommendations to optimise the battery lifetime are proposed.

An improved fuzzy Kalman filter for state estimation of nonlinear systems

International Nuclear Information System (INIS)

Zhou, Z-J; Hu, C-H; Chen, L; Zhang, B-C

2008-01-01

The extended fuzzy Kalman filter (EFKF) is developed recently and used for state estimation of the nonlinear systems with uncertainty. Based on extension of the orthogonality principle and the extended fuzzy Kalman filter, an improved fuzzy Kalman filters (IFKF) is proposed in this paper, which is more applicable and can deal with the state estimation of the nonlinear systems better than the EFKF. A simulation study is provided to verify the efficiency of the proposed method

Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter

DEFF Research Database (Denmark)

Mohd. Azam, Sazuan Nazrah

2017-01-01

In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing...... part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations....

Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration.

Science.gov (United States)

Uzunoglu, B.; Hussaini, Y.

2017-12-01

Implicit Particle Filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability by an implicit step . It optimizes a nonlinear cost function which can be inherited from legacy assimilation routines . Dynamic state estimation for almost real-time applications in power systems are becomingly increasingly more important with integration of variable wind and solar power generation. New advanced state estimation tools that will replace the old generation state estimation in addition to having a general framework of complexities should be able to address the legacy software and able to integrate the old software in a mathematical framework while allowing the power industry need for a cautious and evolutionary change in comparison to a complete revolutionary approach while addressing nonlinearity and non-normal behaviour. This work implements implicit particle filter as a state estimation tool for the estimation of the states of a power system and presents the first implicit particle filter application study on a power system state estimation. The implicit particle filter is introduced into power systems and the simulations are presented for a three-node benchmark power system . The performance of the filter on the presented problem is analyzed and the results are presented.

State Support: A Prerequisite for Global Health Network Effectiveness

Science.gov (United States)

Marten, Robert; Smith, Richard D.

2018-01-01

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks’ success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks’ effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. PMID:29524958

Diagnostic Inspection of Pipelines for Estimating the State of Stress in Them

Science.gov (United States)

Subbotin, V. A.; Kolotilov, Yu. V.; Smirnova, V. Yu.; Ivashko, S. K.

2017-12-01

The diagnostic inspection used to estimate the technical state of a pipeline is described. The problems of inspection works are listed, and a functional-structural scheme is developed to estimate the state of stress in a pipeline. Final conclusions regarding the actual loading of a pipeline section are drawn upon a cross analysis of the entire information obtained during pipeline inspection.

Premium Pricing In Health Insurance By Nelson- Aalen Estimator

OpenAIRE

Istikaanah, Najmah

2011-01-01

In this paper the using of Nelson Aalen estimators are presented to estimate transition probabilities of multistate model. Based on discrete time Markov, we will get transition matrices?é?á which the elements are transition probabilities from Nelson Aalen estimator. Because of the data that used in the construction of transition matrices are person?óÔé¼Ôäós health histories, then it can be seen as a morbidity value, which can be used to premium pricing.?é?á

Model-based state estimator for an intelligent tire

NARCIS (Netherlands)

Goos, J.; Teerhuis, A. P.; Schmeitz, A. J.C.; Besselink, I.; Nijmeijer, H.

2017-01-01

In this work a Tire State Estimator (TSE) is developed and validated using data from a tri-axial accelerometer, installed at the inner liner of the tire. The Flexible Ring Tire (FRT) model is proposed to calculate the tire deformation. For a rolling tire, this deformation is transformed into

Model-based State Estimator for an Intelligent Tire

NARCIS (Netherlands)

Goos, J.; Teerhuis, A.P.; Schmeitz, A.J.C.; Besselink, I.J.M.; Nijmeijer, H.

2016-01-01

In this work a Tire State Estimator (TSE) is developed and validated using data from a tri-axial accelerometer, installed at the inner liner of the tire. The Flexible Ring Tire (FRT) model is proposed to calculate the tire deformation. For a rolling tire, this deformation is transformed into

National health insurance reform in South Africa: estimating the implications for demand for private health insurance.

Science.gov (United States)

Okorafor, Okore Apia

2012-05-01

A recent health reform proposal in South Africa proposes universal access to a comprehensive package of healthcare services in the public sector, through the implementation of a national health insurance (NHI) scheme. Implementation of the scheme is likely to involve the introduction of a payroll tax. It is implied that the introduction of the payroll tax will significantly reduce the size of the private health insurance market. The objective of this study was to estimate the impact of an NHI payroll tax on the demand for private health insurance in South Africa, and to explore the broader implications for health policy. The study applies probit regression analysis on household survey data to estimate the change in demand for private health insurance as a result of income shocks arising from the proposed NHI. The introduction of payroll taxes for the proposed NHI was estimated to result in a reduction to private health insurance membership of 0.73%. This suggests inelasticity in the demand for private health insurance. In the literature on the subject, this inelasticity is usually due to quality differences between alternatives. In the South African context, there may be other factors at play. An NHI tax may have a very small impact on the demand for private health insurance. Although additional financial resources will be raised through a payroll tax under the proposed NHI reform, systemic problems within the South African health system can adversely affect the ability of the NHI to translate additional finances into better quality healthcare. If these systemic challenges are not adequately addressed, the introduction of a payroll tax could introduce inefficiencies within the South African health system.

Mixture estimation with state-space components and Markov model of switching

Czech Academy of Sciences Publication Activity Database

Nagy, Ivan; Suzdaleva, Evgenia

2013-01-01

Roč. 37, č. 24 (2013), s. 9970-9984 ISSN 0307-904X R&D Projects: GA TA ČR TA01030123 Institutional support: RVO:67985556 Keywords : probabilistic dynamic mixtures, * probability density function * state-space models * recursive mixture estimation * Bayesian dynamic decision making under uncertainty * Kerridge inaccuracy Subject RIV: BC - Control Systems Theory Impact factor: 2.158, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/nagy-mixture estimation with state-space components and markov model of switching.pdf

Health-Related Behaviors and Academic Achievement Among High School Students - United States, 2015.

Science.gov (United States)

Rasberry, Catherine N; Tiu, Georgianne F; Kann, Laura; McManus, Tim; Michael, Shannon L; Merlo, Caitlin L; Lee, Sarah M; Bohm, Michele K; Annor, Francis; Ethier, Kathleen A

2017-09-08

Studies have shown links between educational outcomes such as letter grades, test scores, or other measures of academic achievement, and health-related behaviors (1-4). However, as reported in a 2013 systematic review, many of these studies have used samples that are not nationally representative, and quite a few studies are now at least 2 decades old (1). To update the relevant data, CDC analyzed results from the 2015 national Youth Risk Behavior Survey (YRBS), a biennial, cross-sectional, school-based survey measuring health-related behaviors among U.S. students in grades 9-12. Analyses assessed relationships between academic achievement (i.e., self-reported letter grades in school) and 30 health-related behaviors (categorized as dietary behaviors, physical activity, sedentary behaviors, substance use, sexual risk behaviors, violence-related behaviors, and suicide-related behaviors) that contribute to leading causes of morbidity and mortality among adolescents in the United States (5). Logistic regression models controlling for sex, race/ethnicity, and grade in school found that students who earned mostly A's, mostly B's, or mostly C's had statistically significantly higher prevalence estimates for most protective health-related behaviors and significantly lower prevalence estimates for most health-related risk behaviors than did students with mostly D's/F's. These findings highlight the link between health-related behaviors and education outcomes, suggesting that education and public health professionals can find their respective education and health improvement goals to be mutually beneficial. Education and public health professionals might benefit from collaborating to achieve both improved education and health outcomes for youths.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

Science.gov (United States)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Monitoring the World Health Organization Global Target 2025 for Exclusive Breastfeeding: Experience From the United States.

Science.gov (United States)

Gupta, Priya M; Perrine, Cria G; Chen, Jian; Elam-Evans, Laurie D; Flores-Ayala, Rafael

2017-08-01

Exclusive breastfeeding under 6 months, calculated from a single 24-hour recall among mothers of children 0 to 5 months of age, is a World Health Organization (WHO) indicator used to monitor progress on the 2025 global breastfeeding target. Many upper-middle-income and high-income countries, including the United States, do not have estimates for this indicator. Research aim: To describe the prevalence of exclusive breastfeeding under 6 months in the United States. We used a single 24-hour dietary recall from the National Health and Nutrition Examination Survey 2009-2012 to calculate the prevalence of exclusive breastfeeding under 6 months. We discuss our results in the context of routine breastfeeding surveillance, which is reported from a national survey with different methodology. Among children younger than 6 months, 24.4%, 95% confidence interval [17.6, 31.1], were exclusively breastfed the previous day. To our knowledge, this is the first estimate of the WHO indicator of exclusive breastfeeding under 6 months for the United States. This study supports the global surveillance and data strategy for reporting to the WHO on the 2025 target for exclusive breastfeeding.

On state estimation and fusion with elliptical constraints

Energy Technology Data Exchange (ETDEWEB)

Rao, Nageswara S. [ORNL; Liu, Qiang [ORNL

2017-11-01

We consider tracking of a target with elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the known ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to the center, and (ii) shortest distance to the ellipse are discussed. A tracking example is used to illustrate the tracking performance using projection-based methods with various fusers in the lossy long-haul tracking environment.

State and Substate Estimates of Nonmedical Use of Prescription Pain Relievers

Science.gov (United States)

... with other local area data to enhance statistical power and analytic capability. 10 Delete Template National, Regional, and State Estimates In this section, estimates of past year nonmedical use of prescription pain relievers among people aged 12 or older are ...

System state estimation and optimal energy control framework for multicell lithium-ion battery system

International Nuclear Information System (INIS)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai; Kang, Yu

2017-01-01

Highlights: • Employed a dual-scale EKF based estimator for in-pack cells’ SOC values. • Proposed a two-stage hybrid state-feedback and output-feedback equalization algorithm. • A switchable balance current mode is designed in the equalization topology. • Verified the performance of proposed method under two conditions. - Abstract: Cell variations caused by the inevitable inconsistency during manufacture and use of battery cells have significant impacts on battery capacity, security and durability for battery energy storage systems. Thus, the battery equalization systems are essentially required to reduce variations of in-pack cells and increase battery pack capability. In order to protect all in-pack cells from damaging, estimate battery state and reduce variations, a system state estimation and energy optimal control framework for multicell lithium-ion battery system is proposed. The state-of-charge (SOC) values of all in-pack cells are firstly estimated using a dual-scale extended Kalman filtering (EKF) to improve estimation accuracy and reduce computation simultaneously. These estimated SOC values provide specific details of battery system, which cannot only be used to protect cells from over-charging/over-discharging, but also be employed to design state-feedback controller for battery equalization system. A two-stage hybrid state-feedback and output-feedback equalization algorithm is proposed. The state-feedback controller is firstly employed for coarse-grained adjustment to reduce equalization time cost with large current. However, due to the inevitable SOC estimation errors, the output-feedback controller is then used for fine-grained adjustment with trickle current. Experimental results show that the proposed framework can provide an effectively estimation and energy control for multicell battery systems. Finally, the implementation of the proposed method is further discussed for the real applications.

State Estimation for Landing Maneuver on High Performance Aircraft

Science.gov (United States)

Suresh, P. S.; Sura, Niranjan K.; Shankar, K.

2018-01-01

State estimation methods are popular means for validating aerodynamic database on aircraft flight maneuver performance characteristics. In this work, the state estimation method during landing maneuver is explored for the first of its kind, using upper diagonal adaptive extended Kalman filter (UD-AEKF) with fuzzy based adaptive tunning of process noise matrix. The mathematical model for symmetrical landing maneuver consists of non-linear flight mechanics equation representing Aircraft longitudinal dynamics. The UD-AEKF algorithm is implemented in MATLAB environment and the states with bias is considered to be the initial conditions just prior to the flare. The measurement data is obtained from a non-linear 6 DOF pilot in loop simulation using FORTRAN. These simulated measurement data is additively mixed with process and measurement noises, which are used as an input for UD-AEKF. Then, the governing states that dictate the landing loads at the instant of touch down are compared. The method is verified using flight data wherein, the vertical acceleration at the aircraft center of gravity (CG) is compared. Two possible outcome of purely relying on the aircraft measured data is highlighted. It is observed that, with the implementation of adaptive fuzzy logic based extended Kalman filter tuned to adapt for aircraft landing dynamics, the methodology improves the data quality of the states that are sourced from noisy measurements.

Learning to Estimate Dynamical State with Probabilistic Population Codes.

Directory of Open Access Journals (Sweden)

Joseph G Makin

2015-11-01

Full Text Available Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF, the parameters of which can be learned via latent-variable density estimation (the EM algorithm. The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states.

Contributions of national and global health estimates to monitoring health-related sustainable development goals.

Science.gov (United States)

Bundhamcharoen, Kanitta; Limwattananon, Supon; Kusreesakul, Khanitta; Tangcharoensathien, Viroj

2016-01-01

The millennium development goals triggered an increased demand for data on child and maternal mortalities for monitoring progress. With the advent of the sustainable development goals and growing evidence of an epidemiological transition toward non-communicable diseases, policymakers need data on mortality and disease trends and distribution to inform effective policies and support monitoring progress. Where there are limited capacities to produce national health estimates (NHEs), global health estimates (GHEs) can fill gaps for global monitoring and comparisons. This paper discusses lessons learned from Thailand's burden of disease (BOD) study on capacity development on NHEs and discusses the contributions and limitations of GHEs in informing policies at the country level. Through training and technical support by external partners, capacities are gradually strengthened and institutionalized to enable regular updates of BOD at national and subnational levels. Initially, the quality of cause-of-death reporting in death certificates was inadequate, especially for deaths occurring in the community. Verbal autopsies were conducted, using domestic resources, to determine probable causes of deaths occurring in the community. This method helped to improve the estimation of years of life lost. Since the achievement of universal health coverage in 2002, the quality of clinical data on morbidities has also considerably improved. There are significant discrepancies between the Global Burden of Disease 2010 study estimates for Thailand and the 1999 nationally generated BOD, especially for years of life lost due to HIV/AIDS, and the ranking of priority diseases. National ownership of NHEs and an effective interface between researchers and decision-makers contribute to enhanced country policy responses, whereas subnational data are intended to be used by various subnational partners. Although GHEs contribute to benchmarking country achievement compared with global health

System health monitoring using multiple-model adaptive estimation techniques

Science.gov (United States)

Sifford, Stanley Ryan

Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary

State Estimation of Permanent Magnet Synchronous Motor Using Improved Square Root UKF

Directory of Open Access Journals (Sweden)

Bo Xu

2016-06-01

Full Text Available This paper focuses on an improved square root unscented Kalman filter (SRUKF and its application for rotor speed and position estimation of permanent magnet synchronous motor (PMSM. The approach, which combines the SRUKF and strong tracking filter, uses the minimal skew simplex transformation to reduce the number of the sigma points, and utilizes the square root filtering to reduce computational errors. The time-varying fading factor and softening factor are introduced to self-adjust the gain matrices and the state forecast covariance square root matrix, which can realize the residuals orthogonality and force the SRUKF to track the real state rapidly. The theoretical analysis of the improved SRUKF and implementation details for PMSM state estimation are examined. The simulation results show that the improved SRUKF has higher nonlinear approximation accuracy, stronger numerical stability and computational efficiency, and it is an effective and powerful tool for PMSM state estimation under the conditions of step response or load disturbance.

A method for state of energy estimation of lithium-ion batteries based on neural network model

International Nuclear Information System (INIS)

Dong, Guangzhong; Zhang, Xu; Zhang, Chenbin; Chen, Zonghai

2015-01-01

The state-of-energy is an important evaluation index for energy optimization and management of power battery systems in electric vehicles. Unlike the state-of-charge which represents the residual energy of the battery in traditional applications, state-of-energy is integral result of battery power, which is the product of current and terminal voltage. On the other hand, like state-of-charge, the state-of-energy has an effect on terminal voltage. Therefore, it is hard to solve the nonlinear problems between state-of-energy and terminal voltage, which will complicate the estimation of a battery's state-of-energy. To address this issue, a method based on wavelet-neural-network-based battery model and particle filter estimator is presented for the state-of-energy estimation. The wavelet-neural-network based battery model is used to simulate the entire dynamic electrical characteristics of batteries. The temperature and discharge rate are also taken into account to improve model accuracy. Besides, in order to suppress the measurement noises of current and voltage, a particle filter estimator is applied to estimate cell state-of-energy. Experimental results on LiFePO_4 batteries indicate that the wavelet-neural-network based battery model simulates battery dynamics robustly with high accuracy and the estimation value based on the particle filter estimator converges to the real state-of-energy within an error of ±4%. - Highlights: • State-of-charge is replaced by state-of-energy to determine cells residual energy. • The battery state-space model is established based on a neural network. • Temperature and current influence are considered to improve the model accuracy. • The particle filter is used for state-of-energy estimation to improve accuracy. • The robustness of new method is validated under dynamic experimental conditions.

Implementation of a Simplified State Estimator for Wind Turbine Monitoring on an Embedded System

DEFF Research Database (Denmark)

Rasmussen, Theis Bo; Yang, Guangya; Nielsen, Arne Hejde

2017-01-01

system, including individual DER, is time consuming and numerically challenging. This paper presents the approach and results of implementing a simplified state estimator onto an embedded system for improving DER monitoring. The implemented state estimator is based on numerically robust orthogonal......The transition towards a cyber-physical energy system (CPES) entails an increased dependency on valid data. Simultaneously, an increasing implementation of renewable generation leads to possible control actions at individual distributed energy resources (DERs). A state estimation covering the whole...

Iterative Observer-based Estimation Algorithms for Steady-State Elliptic Partial Differential Equation Systems

KAUST Repository

Majeed, Muhammad Usman

2017-07-19

Steady-state elliptic partial differential equations (PDEs) are frequently used to model a diverse range of physical phenomena. The source and boundary data estimation problems for such PDE systems are of prime interest in various engineering disciplines including biomedical engineering, mechanics of materials and earth sciences. Almost all existing solution strategies for such problems can be broadly classified as optimization-based techniques, which are computationally heavy especially when the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time-like. In this regard, first, an iterative observer algorithm is developed that sweeps over regular-shaped domains and solves boundary estimation problems for steady-state Laplace equation. It is well-known that source and boundary estimation problems for the elliptic PDEs are highly sensitive to noise in the data. For this, an optimal iterative observer algorithm, which is a robust counterpart of the iterative observer, is presented to tackle the ill-posedness due to noise. The iterative observer algorithm and the optimal iterative algorithm are then used to solve source localization and estimation problems for Poisson equation for noise-free and noisy data cases respectively. Next, a divide and conquer approach is developed for three-dimensional domains with two congruent parallel surfaces to solve the boundary and the source data estimation problems for the steady-state Laplace and Poisson kind of systems respectively. Theoretical results are shown using a functional analysis framework, and consistent numerical simulation results are presented for several test cases using finite difference discretization schemes.

Practical global oceanic state estimation

Science.gov (United States)

Wunsch, Carl; Heimbach, Patrick

2007-06-01

The problem of oceanographic state estimation, by means of an ocean general circulation model (GCM) and a multitude of observations, is described and contrasted with the meteorological process of data assimilation. In practice, all such methods reduce, on the computer, to forms of least-squares. The global oceanographic problem is at the present time focussed primarily on smoothing, rather than forecasting, and the data types are unlike meteorological ones. As formulated in the consortium Estimating the Circulation and Climate of the Ocean (ECCO), an automatic differentiation tool is used to calculate the so-called adjoint code of the GCM, and the method of Lagrange multipliers used to render the problem one of unconstrained least-squares minimization. Major problems today lie less with the numerical algorithms (least-squares problems can be solved by many means) than with the issues of data and model error. Results of ongoing calculations covering the period of the World Ocean Circulation Experiment, and including among other data, satellite altimetry from TOPEX/POSEIDON, Jason-1, ERS- 1/2, ENVISAT, and GFO, a global array of profiling floats from the Argo program, and satellite gravity data from the GRACE mission, suggest that the solutions are now useful for scientific purposes. Both methodology and applications are developing in a number of different directions.

Food Insecurity and Health Care Expenditures in the United States, 2011-2013.

Science.gov (United States)

Berkowitz, Seth A; Basu, Sanjay; Meigs, James B; Seligman, Hilary K

2018-06-01

To determine whether food insecurity, limited or uncertain food access owing to cost, is associated with greater health care expenditures. Nationally representative sample of the civilian noninstitutionalized population of the United States (2011 National Health Interview Survey [NHIS] linked to 2012-2013 Medication Expenditure Panel Survey [MEPS]). Longitudinal retrospective cohort. A total of 16,663 individuals underwent assessment of food insecurity, using the 10-item adult 30-day food security module, in the 2011 NHIS. Their total health care expenditures in 2012 and 2013 were recorded in MEPS. Expenditure data were analyzed using zero-inflated negative binomial regression and adjusted for age, gender, race/ethnicity, education, income, insurance, and residence area. Fourteen percent of individuals reported food insecurity, representing 41,616,255 Americans. Mean annualized total expenditures were $4,113 (standard error $115); 9.2 percent of all individuals had no health care expenditures. In multivariable analyses, those with food insecurity had significantly greater estimated mean annualized health care expenditures ($6,072 vs. $4,208, p insecurity was associated with greater subsequent health care expenditures. Future studies should determine whether food insecurity interventions can improve health and reduce health care costs. © Health Research and Educational Trust.

Socioeconomic inequalities in oral health in different European welfare state regimes.

Science.gov (United States)

Guarnizo-Herreño, Carol C; Watt, Richard G; Pikhart, Hynek; Sheiham, Aubrey; Tsakos, Georgios

2013-09-01

There is very little information about the relationship between welfare regimes and oral health inequalities. We compared socioeconomic inequalities in adults' oral health in five European welfare-state regimes: Scandinavian, Anglo-Saxon, Bismarckian, Southern and Eastern. Using data from the oral health module of the Eurobarometer 72.3 survey, we assessed inequalities in two self-reported oral health measures: no functional dentition (less than 20 natural teeth) and edentulousness (no natural teeth). Occupational social class, education and subjective social status (SSS) were included as socioeconomic position indicators. We estimated age-standardised prevalence rates, ORs, the Relative Index of Inequality (RII) and the Slope Index of Inequality (SII). The Scandinavian regime showed the lowest prevalence rates of the two oral health measures while the Eastern showed the highest. In all welfare regimes there was a general pattern of social gradients by occupational social class and education. Relative educational inequalities in no functional dentition were largest in the Scandinavian welfare regime (RII=3.81; 95% CI 2.68 to 5.42). The Scandinavian and Southern regimes showed the largest relative inequalities in edentulousness by occupation and education, respectively. There were larger absolute inequalities in no functional dentition in the Eastern regime by occupation (SII=42.16; 95% CI 31.42 to 52.89) and in the Southern by SSS (SII=27.92; 95% CI 17.36 to 38.47). Oral health inequalities in adults exist in all welfare-state regimes, but contrary to what may be expected from theory, they are not smaller in the Scandinavian regime. Future work should examine the potential mechanisms linking welfare provision and oral health inequalities.

State Estimation for a Biological Phosphorus Removal Process using an Asymptotic Observer

DEFF Research Database (Denmark)

Larose, Claude Alain; Jørgensen, Sten Bay

2001-01-01

This study investigated the use of an asymptotic observer for state estimation in a continuous biological phosphorus removal process. The estimated states are the concentration of heterotrophic, autotrophic, and phosphorus accumulating organisms, polyphosphate, glycogen and PHA. The reaction scheme...... if the convergence, driven by the dilution rate, was slow (from 15 to 60 days). The propagation of the measurement noise and a bias in the estimation of glycogen and PHA could be the result of the high condition number of one of the matrices used in the algorithm of the asymptotic observer for the aerated tanks....

The economic costs of radiation-induced health effects: Estimation and simulation

International Nuclear Information System (INIS)

Nieves, L.A.; Tawil, J.J.

1988-08-01

This effort improves the quantitative information available for use in evaluating actions that alter health risks due to population exposure to ionizing radiation. To project the potential future costs of changes in health effects risks, Pacific Northwest Laboratory (PNL) constructed a probabilistic computer model, Health Effects Costs Model (HECOM), which utilizes the health effect incidence estimates from accident consequences models to calculate the discounted sum of the economic costs associated with population exposure to ionizing radiation. Application of HECOM to value-impact and environmental impact analyses should greatly increase the quality of the information available for regulatory decision making. Three major types of health effects present risks for any population sustaining a significant radiation exposure: acute radiation injuries (and fatalities), latent cancers, and impairments due to genetic effects. The literature pertaining to both incidence and treatment of these health effects was reviewed by PNL and provided the basis for developing economic cost estimates. The economic costs of health effects estimated by HECOM represent both the value of resources consumed in diagnosing, treating, and caring for the patient and the value of goods not produced because of illness or premature death due to the health effect. Additional costs to society, such as pain and suffering, are not included in the PNL economic cost measures since they do not divert resources from other uses, are difficult to quantify, and do not have a value observable in the marketplace. 83 refs., 3 figs., 19 tabs

The economic costs of radiation-induced health effects: Estimation and simulation

Energy Technology Data Exchange (ETDEWEB)

Nieves, L.A.; Tawil, J.J.

1988-08-01

This effort improves the quantitative information available for use in evaluating actions that alter health risks due to population exposure to ionizing radiation. To project the potential future costs of changes in health effects risks, Pacific Northwest Laboratory (PNL) constructed a probabilistic computer model, Health Effects Costs Model (HECOM), which utilizes the health effect incidence estimates from accident consequences models to calculate the discounted sum of the economic costs associated with population exposure to ionizing radiation. Application of HECOM to value-impact and environmental impact analyses should greatly increase the quality of the information available for regulatory decision making. Three major types of health effects present risks for any population sustaining a significant radiation exposure: acute radiation injuries (and fatalities), latent cancers, and impairments due to genetic effects. The literature pertaining to both incidence and treatment of these health effects was reviewed by PNL and provided the basis for developing economic cost estimates. The economic costs of health effects estimated by HECOM represent both the value of resources consumed in diagnosing, treating, and caring for the patient and the value of goods not produced because of illness or premature death due to the health effect. Additional costs to society, such as pain and suffering, are not included in the PNL economic cost measures since they do not divert resources from other uses, are difficult to quantify, and do not have a value observable in the marketplace. 83 refs., 3 figs., 19 tabs.

Optic Flow Based State Estimation for an Indoor Micro Air Vehicle

NARCIS (Netherlands)

Verveld, M.J.; Chu, Q.P.; De Wagter, C.; Mulder, J.A.

2010-01-01

This work addresses the problem of indoor state estimation for autonomous flying vehicles with an optic flow approach. The paper discusses a sensor configuration using six optic flow sensors of the computer mouse type augmented by a three-axis accelerometer to estimate velocity, rotation, attitude

National and state-specific health insurance disparities for adults in same-sex relationships.

Science.gov (United States)

Gonzales, Gilbert; Blewett, Lynn A

2014-02-01

We examined national and state-specific disparities in health insurance coverage, specifically employer-sponsored insurance (ESI) coverage, for adults in same-sex relationships. We used data from the American Community Survey to identify adults (aged 25-64 years) in same-sex relationships (n = 31,947), married opposite-sex relationships (n = 3,060,711), and unmarried opposite-sex relationships (n = 259,147). We estimated multinomial logistic regression models and state-specific relative differences in ESI coverage with predictive margins. Men and women in same-sex relationships were less likely to have ESI than were their married counterparts in opposite-sex relationships. We found ESI disparities among adults in same-sex relationships in every region, but we found the largest ESI gaps for men in the South and for women in the Midwest. ESI disparities were narrower in states that had extended legal same-sex marriage, civil unions, and broad domestic partnerships. Men and women in same-sex relationships experience disparities in health insurance coverage across the country, but residing in a state that recognizes legal same-sex marriage, civil unions, or broad domestic partnerships may improve access to ESI for same-sex spouses and domestic partners.

Estimates of Incidence and Prevalence of Visual Impairment, Low Vision, and Blindness in the United States.

Science.gov (United States)

Chan, Tiffany; Friedman, David S; Bradley, Chris; Massof, Robert

2018-01-01

Updated estimates of the prevalence and incidence rates of low vision and blindness are needed to inform policy makers and develop plans to meet the future demands for low vision rehabilitation services. To provide updated estimates of the incidence and prevalence of low vision and blindness in the United States. Visual acuity measurements as a function of age from the 2007-2008 National Health and Nutrition Examination Survey, with representation of racial and ethnic groups, were used to estimate the prevalence and incidence of visual impairments. Data from 6016 survey participants, ranging in age from younger than 18 years to older than 45 years, were obtained to estimate prevalence rates for different age groups. Incidence and prevalence rates of low vision (best-corrected visual acuity [BCVA] in the better-seeing eye of United States were estimated, using the 2010 US census data by age, from the rate models applied to the census projections for 2017, 2030, and 2050. Data were collected from November 1, 2007, to October 31, 2008. Data analysis took place from March 31, 2016, to March 19, 2017. Prevalence and incidence rates of low vision and blindness in the United States. Of the 6016 people in the study, 1714 (28.4%) were younger than 18 years of age, 2358 (39.1%) were 18 to 44 years of age, and 1944 (32.3%) were 45 years of age or older. There were 2888 male (48%) and 3128 female (52%) participants. The prevalence of low vision and blindness for older adults (≥45 years) in the United States in 2017 is estimated to be 3 894 406 persons (95% CI, 3 034 442-4 862 549 persons) with a BCVA less than 20/40, 1 483 703 persons (95% CI, 968 656-2 370 513 persons) with a BCVA less than 20/60, and 1 082 790 persons (95% CI, 637 771-1 741 864 persons) with a BCVA of 20/200 or less. The estimated 2017 annual incidence (projected from 2010 census data) of low vision and blindness among older adults (≥45 years) in the United States is 481�

Merging Psychophysical and Psychometric Theory to Estimate Global Visual State Measures from Forced-Choices

International Nuclear Information System (INIS)

Massof, Robert W; Schmidt, Karen M; Laby, Daniel M; Kirschen, David; Meadows, David

2013-01-01

Visual acuity, a forced-choice psychophysical measure of visual spatial resolution, is the sine qua non of clinical visual impairment testing in ophthalmology and optometry patients with visual system disorders ranging from refractive error to retinal, optic nerve, or central visual system pathology. Visual acuity measures are standardized against a norm, but it is well known that visual acuity depends on a variety of stimulus parameters, including contrast and exposure duration. This paper asks if it is possible to estimate a single global visual state measure from visual acuity measures as a function of stimulus parameters that can represent the patient's overall visual health state with a single variable. Psychophysical theory (at the sensory level) and psychometric theory (at the decision level) are merged to identify the conditions that must be satisfied to derive a global visual state measure from parameterised visual acuity measures. A global visual state measurement model is developed and tested with forced-choice visual acuity measures from 116 subjects with no visual impairments and 560 subjects with uncorrected refractive error. The results are in agreement with the expectations of the model

Real-Time Radar-Based Tracking and State Estimation of Multiple Non-Conformant Aircraft

Science.gov (United States)

Cook, Brandon; Arnett, Timothy; Macmann, Owen; Kumar, Manish

2017-01-01

In this study, a novel solution for automated tracking of multiple unknown aircraft is proposed. Many current methods use transponders to self-report state information and augment track identification. While conformant aircraft typically report transponder information to alert surrounding aircraft of its state, vehicles may exist in the airspace that are non-compliant and need to be accurately tracked using alternative methods. In this study, a multi-agent tracking solution is presented that solely utilizes primary surveillance radar data to estimate aircraft state information. Main research challenges include state estimation, track management, data association, and establishing persistent track validity. In an effort to realize these challenges, techniques such as Maximum a Posteriori estimation, Kalman filtering, degree of membership data association, and Nearest Neighbor Spanning Tree clustering are implemented for this application.

Estimated hospital costs associated with preventable health care-associated infections if health care antiseptic products were unavailable

Directory of Open Access Journals (Sweden)

Schmier JK

2016-05-01

Full Text Available Jordana K Schmier,1 Carolyn K Hulme-Lowe,1 Svetlana Semenova,2 Juergen A Klenk,3 Paul C DeLeo,4 Richard Sedlak,5 Pete A Carlson6 1Health Sciences, Exponent, Inc., Alexandria, VA, 2EcoSciences, Exponent, Inc., Maynard, MA, 3Health Sciences, Exponent, Inc., Alexandria, VA, 4Environmental Safety, 5Technical and International Affairs, American Cleaning Institute, Washington, DC, 6Regulatory Affairs, Ecolab, Saint Paul, MN, USA Objectives: Health care-associated infections (HAIs pose a significant health care and cost burden. This study estimates annual HAI hospital costs in the US avoided through use of health care antiseptics (health care personnel hand washes and rubs; surgical hand scrubs and rubs; patient preoperative and preinjection skin preparations. Methods: A spreadsheet model was developed with base case inputs derived from the published literature, supplemented with assumptions when data were insufficient. Five HAIs of interest were identified: catheter-associated urinary tract infections, central line-associated bloodstream infections, gastrointestinal infections caused by Clostridium difficile, hospital- or ventilator-associated pneumonia, and surgical site infections. A national estimate of the annual potential lost benefits from elimination of these products is calculated based on the number of HAIs, the proportion of HAIs that are preventable, the proportion of preventable HAIs associated with health care antiseptics, and HAI hospital costs. The model is designed to be user friendly and to allow assumptions about prevention across all infections to vary or stay the same. Sensitivity analyses provide low- and high-end estimates of costs avoided. Results: Low- and high-end estimates of national, annual HAIs in hospitals avoided through use of health care antiseptics are 12,100 and 223,000, respectively, with associated hospital costs avoided of US$142 million and US$4.25 billion, respectively. Conclusion: The model presents a novel

Health state utilities associated with attributes of weekly injection devices for treatment of type 2 diabetes

Directory of Open Access Journals (Sweden)

Louis S. Matza

2017-11-01

Full Text Available Abstract Background Glucagon-like peptide-1 (GLP-1 receptor agonists are often recommended as part of combination therapy for type 2 diabetes when oral medication does not result in sufficient glycemic control. Several GLP-1 receptor agonists are available as weekly injections. These medications vary in their injection delivery systems, and these differences could impact quality of life and treatment preference. The purpose of this study was to estimate utilities associated with attributes of injection delivery systems for weekly GLP-1 therapies. Methods Participants with type 2 diabetes in the UK valued health states in time trade-off interviews. The health states (drafted based on literature, device instructions for use, and clinician interviews had identical descriptions of type 2 diabetes, but differed in description of the treatment process. One health state described oral treatment, while six others described oral treatment plus a weekly injection. The injection health states varied in three aspects of the treatment administration process: requirements for reconstituting the medication (i.e., mixing the medication prior to the injection, waiting during medication preparation, and needle handling. Every participant valued all seven health states. Results A total of 209 participants completed interviews (57.4% male; mean age = 60.4y. The mean utility of the oral treatment health state was 0.89. All injection health states had significantly (p < 0.01 lower utilities ranging from 0.86 to 0.88. Differences among health state utilities suggest that each administration requirement had a small but measureable disutility: -0.004 (reconstitution, -0.004 (needle handling, -0.010 (reconstitution, needle handling, and -0.020 (reconstitution, waiting, needle handling. Conclusions Findings suggest it is feasible to use the TTO method to quantify preferences among injection treatment processes. It may be useful to incorporate these utility differences

State estimation for networked control systems using fixed data rates

Science.gov (United States)

Liu, Qing-Quan; Jin, Fang

2017-07-01

This paper investigates state estimation for linear time-invariant systems where sensors and controllers are geographically separated and connected via a bandwidth-limited and errorless communication channel with the fixed data rate. All plant states are quantised, coded and converted together into a codeword in our quantisation and coding scheme. We present necessary and sufficient conditions on the fixed data rate for observability of such systems, and further develop the data-rate theorem. It is shown in our results that there exists a quantisation and coding scheme to ensure observability of the system if the fixed data rate is larger than the lower bound given, which is less conservative than the one in the literature. Furthermore, we also examine the role that the disturbances have on the state estimation problem in the case with data-rate limitations. Illustrative examples are given to demonstrate the effectiveness of the proposed method.

A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model

International Nuclear Information System (INIS)

Wei, Zhongbao; Zhao, Jiyun; Ji, Dongxu; Tseng, King Jet

2017-01-01

Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.

Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

Directory of Open Access Journals (Sweden)

R. Manam

2017-12-01

Full Text Available In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

Series load induction heating inverter state estimator using Kalman filter

Directory of Open Access Journals (Sweden)

Szelitzky T.

2011-12-01

Full Text Available LQR and H2 controllers require access to the states of the controlled system. The method based on description function with Fourier series results in a model with immeasurable states. For this reason, we proposed a Kalman filter based state estimator, which not only filters the input signals, but also computes the unobservable states of the system. The algorithm of the filter was implemented in LabVIEW v8.6 and tested on recorded data obtained from a 10-40 kHz series load frequency controlled induction heating inverter.

Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

International Nuclear Information System (INIS)

Dhondt, Stijn; Beckx, Carolien; Degraeuwe, Bart; Lefebvre, Wouter; Kochan, Bruno; Bellemans, Tom; Int Panis, Luc; Macharis, Cathy; Putman, Koen

2012-01-01

In both ambient air pollution epidemiology and health impact assessment an accurate assessment of the population exposure is crucial. Although considerable advances have been made in assessing human exposure outdoors, the assessments often do not consider the impact of individual travel behavior on such exposures. Population-based exposures to NO 2 and O 3 using only home addresses were compared with models that integrate all time-activity patterns—including time in commute—for Flanders and Brussels. The exposure estimates were used to estimate the air pollution impact on years of life lost due to respiratory mortality. Health impact of NO 2 using an exposure that integrates time-activity information was on average 1.2% higher than when assuming that people are always at their home address. For ozone the overall estimated health impact was 0.8% lower. Local differences could be much larger, with estimates that differ up to 12% from the exposure using residential addresses only. Depending on age and gender, deviations from the population average were seen. Our results showed modest differences on a regional level. At the local level, however, time-activity patterns indicated larger differences in exposure and health impact estimates, mainly for people living in more rural areas. These results suggest that for local analyses the dynamic approach can contribute to an improved assessment of the health impact of various types of pollution and to the understanding of exposure differences between population groups. - Highlights: ► Exposure to ambient air pollution was assessed integrating population mobility. ► This dynamic exposure was integrated into a health impact assessment. ► Differences between the dynamic and residential exposure were quantified. ► Modest differences in health impact were found at a regional level. ► At municipal level larger differences were found, influenced by gender and age.

United States of America: health system review.

Science.gov (United States)

Rice, Thomas; Rosenau, Pauline; Unruh, Lynn Y; Barnes, Andrew J; Saltman, Richard B; van Ginneken, Ewout

2013-01-01

This analysis of the United States health system reviews the developments in organization and governance, health financing, health-care provision, health reforms and health system performance. The US health system has both considerable strengths and notable weaknesses. It has a large and well-trained health workforce, a wide range of high-quality medical specialists as well as secondary and tertiary institutions, a robust health sector research program and, for selected services, among the best medical outcomes in the world. But it also suffers from incomplete coverage of its citizenry, health expenditure levels per person far exceeding all other countries, poor measures on many objective and subjective measures of quality and outcomes, an unequal distribution of resources and outcomes across the country and among different population groups, and lagging efforts to introduce health information technology. It is difficult to determine the extent to which deficiencies are health-system related, though it seems that at least some of the problems are a result of poor access to care. Because of the adoption of the Affordable Care Act in 2010, the United States is facing a period of enormous potential change. Improving coverage is a central aim, envisaged through subsidies for the uninsured to purchase private insurance, expanded eligibility for Medicaid (in some states) and greater protection for insured persons. Furthermore, primary care and public health receive increased funding, and quality and expenditures are addressed through a range of measures. Whether the ACA will indeed be effective in addressing the challenges identified above can only be determined over time. World Health Organization 2013 (acting as the host organization for, and secretariat of, the European Observatory on Health Systems and Policies).

State funding for local public health: observations from six case studies.

Science.gov (United States)

Potter, Margaret A; Fitzpatrick, Tiffany

2007-01-01

The purpose of this study is to describe state funding of local public health within the context of state public health system types. These types are based on administrative relationships, legal structures, and relative proportion of state funding in local public health budgets. We selected six states representing various types and geographic regions. A case study for each state summarized available information and was validated by state public health officials. An analysis of the case studies reveals that the variability of state public health systems--even within a given type--is matched by variability in approaches to funding local public health. Nevertheless, some meaningful associations appear. For example, higher proportions of state funding occur along with higher levels of state oversight and the existence of local service mandates in state law. These associations suggest topics for future research on public health financing in relation to local accountability, local input to state priority-setting, mandated local services, and the absence of state funds for public health services in some local jurisdictions.

Optimal estimate of a pure qubit state from Uhlmann-Josza fidelity

Energy Technology Data Exchange (ETDEWEB)

Aoki, Manuel Avila, E-mail: manvlk@yahoo.com [Centro Universitario UAEM Valle de Chalco, UAEMex, Edo. de Mexico (Mexico)

2012-04-15

In the framework of collective measurements, efforts have been made to reconstruct one-qubit states. Such schemes find an obstacle in the no-cloning theorem, which prevents full reconstruction of a quantum state. Quantum Mechanics thus restricts to obtain estimates of the reconstruction of a pure qubit. We discuss the optimal estimate on the basis of the Uhlmann-Josza fidelity, respecting the limitations imposed by the no-cloning theorem. We derive a realistic optimal expression for the average fidelity. Our formalism also introduces an optimization parameter L. Values close to zero imply full reconstruction of the qubit (i. e., the classical limit), while larger L's represent good quantum optimization of the qubit estimate. The parameter L is interpreted as the degree of quantumness of the average fidelity associated with the reconstruction. (author)

Billing and insurance-related administrative costs in United States' health care: synthesis of micro-costing evidence.

Science.gov (United States)

Jiwani, Aliya; Himmelstein, David; Woolhandler, Steffie; Kahn, James G

2014-11-13

The United States' multiple-payer health care system requires substantial effort and costs for administration, with billing and insurance-related (BIR) activities comprising a large but incompletely characterized proportion. A number of studies have quantified BIR costs for specific health care sectors, using micro-costing techniques. However, variation in the types of payers, providers, and BIR activities across studies complicates estimation of system-wide costs. Using a consistent and comprehensive definition of BIR (including both public and private payers, all providers, and all types of BIR activities), we synthesized and updated available micro-costing evidence in order to estimate total and added BIR costs for the U.S. health care system in 2012. We reviewed BIR micro-costing studies across healthcare sectors. For physician practices, hospitals, and insurers, we estimated the % BIR using existing research and publicly reported data, re-calculated to a standard and comprehensive definition of BIR where necessary. We found no data on % BIR in other health services or supplies settings, so extrapolated from known sectors. We calculated total BIR costs in each sector as the product of 2012 U.S. national health expenditures and the percentage of revenue used for BIR. We estimated "added" BIR costs by comparing total BIR costs in each sector to those observed in existing, simplified financing systems (Canada's single payer system for providers, and U.S. Medicare for insurers). Due to uncertainty in inputs, we performed sensitivity analyses. BIR costs in the U.S. health care system totaled approximately $471 ($330 - $597) billion in 2012. This includes $70 ($54 - $76) billion in physician practices, $74 ($58 - $94) billion in hospitals, an estimated $94 ($47 - $141) billion in settings providing other health services and supplies, $198 ($154 - $233) billion in private insurers, and $35 ($17 - $52) billion in public insurers. Compared to simplified financing, $375

ASTDD Synopses of State Oral Health Programs - Selected indicators

Data.gov (United States)

U.S. Department of Health & Human Services — 2011-2017. The ASTDD Synopses of State Oral Health Programs contain information useful in tracking states’ efforts to improve oral health and contributions to...

Unauthorized Immigration to the United States: Annual Estimates and Components of Change, by State, 1990 to 2010

Science.gov (United States)

Warren, Robert; Warren, John Robert

2013-01-01

We describe a method for producing annual estimates of the unauthorized immigrant population in the United Sates and components of population change, for each state and D.C., for 1990 to 2010. We quantify a sharp drop in the number of unauthorized immigrants arriving since 2000, and we demonstrate the role of departures from the population (emigration, adjustment to legal status, removal by the Department of Homeland Security (DHS), and deaths) in reducing population growth from one million in 2000 to population losses in 2008 and 2009. The number arriving in the U.S. peaked at more than one million in 1999 to 2001, and then declined rapidly through 2009. We provide evidence that population growth stopped after 2007 primarily because entries declined and not because emigration increased during the economic crisis. Our estimates of the total unauthorized immigrant population in the U.S. and in the top ten states are comparable to those produced by DHS and the Pew Hispanic Center. For the remaining states and D.C., our data and methods produce estimates with smaller ranges of sampling error. PMID:23956482

Unauthorized Immigration to the United States: Annual Estimates and Components of Change, by State, 1990 to 2010.

Science.gov (United States)

Warren, Robert; Warren, John Robert

2013-06-01

We describe a method for producing annual estimates of the unauthorized immigrant population in the United Sates and components of population change, for each state and D.C., for 1990 to 2010. We quantify a sharp drop in the number of unauthorized immigrants arriving since 2000, and we demonstrate the role of departures from the population (emigration, adjustment to legal status, removal by the Department of Homeland Security (DHS), and deaths) in reducing population growth from one million in 2000 to population losses in 2008 and 2009. The number arriving in the U.S. peaked at more than one million in 1999 to 2001, and then declined rapidly through 2009. We provide evidence that population growth stopped after 2007 primarily because entries declined and not because emigration increased during the economic crisis. Our estimates of the total unauthorized immigrant population in the U.S. and in the top ten states are comparable to those produced by DHS and the Pew Hispanic Center. For the remaining states and D.C., our data and methods produce estimates with smaller ranges of sampling error.

H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.

Science.gov (United States)

Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir

2018-03-01

This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Simultaneous estimation of multiple phases in digital holographic interferometry using state space analysis

Science.gov (United States)

Kulkarni, Rishikesh; Rastogi, Pramod

2018-05-01

A new approach is proposed for the multiple phase estimation from a multicomponent exponential phase signal recorded in multi-beam digital holographic interferometry. It is capable of providing multidimensional measurements in a simultaneous manner from a single recording of the exponential phase signal encoding multiple phases. Each phase within a small window around each pixel is appproximated with a first order polynomial function of spatial coordinates. The problem of accurate estimation of polynomial coefficients, and in turn the unwrapped phases, is formulated as a state space analysis wherein the coefficients and signal amplitudes are set as the elements of a state vector. The state estimation is performed using the extended Kalman filter. An amplitude discrimination criterion is utilized in order to unambiguously estimate the coefficients associated with the individual signal components. The performance of proposed method is stable over a wide range of the ratio of signal amplitudes. The pixelwise phase estimation approach of the proposed method allows it to handle the fringe patterns that may contain invalid regions.

Drug use and AIDS: estimating injection prevalence in a rural state.

Science.gov (United States)

Leukefeld, Carl G; Logan, T K; Farabee, David; Clayton, Richard

2002-01-01

This paper presents approaches used in one rural U.S. state to describe the level of injecting drug use and to estimate the number of injectors not receiving drug-user treatment. The focus is on two broad areas of estimation that were used to present the prevalence of injecting drug use in Kentucky. The first estimation approach uses available data from secondary data sources. The second approach involves three small community studies.

Estimated Human and Economic Burden of Four Major Adult Vaccine-Preventable Diseases in the United States, 2013.

Science.gov (United States)

McLaughlin, John M; McGinnis, Justin J; Tan, Litjen; Mercatante, Annette; Fortuna, Joseph

2015-08-01

Low uptake of routinely recommended adult immunizations is a public health concern. Using data from the peer-reviewed literature, government disease-surveillance programs, and the US Census, we developed a customizable model to estimate human and economic burden caused by four major adult vaccine-preventable diseases (VPD) in 2013 in the United States, and for each US state individually. To estimate the number of cases for each adult VPD for a given population, we multiplied age-specific incidence rates obtained from the literature by age-specific 2013 Census population data. We then multiplied the estimated number of cases for a given population by age-specific, estimated medical and indirect (non-medical) costs per case. Adult VPDs examined were: (1) influenza, (2) pneumococcal disease (both invasive disease and pneumonia), (3) herpes zoster (shingles), and (4) pertussis (whooping cough). Sensitivity analyses simulated the impact of various epidemiological scenarios on the total estimated economic burden. Estimated US annual cost for the four adult VPDs was $26.5 billion (B) among adults aged 50 years and older, $15.3B (58 %) of which was attributable to those 65 and older. Among adults 50 and older, influenza, pneumococcal disease, herpes zoster, and pertussis made up $16.0B (60 %), $5.1B (19 %), $5.0B (19 %), and $0.4B (2 %) of the cost, respectively. Among those 65 and older, they made up $8.3B (54 %), $3.8B (25 %), $3.0B (20 %), and 0.2B (1 %) of the cost, respectively. Most (80-85 %) pneumococcal costs stemmed from nonbacteremic pneumococcal pneumonia (NPP). Cost attributable to adult VPD in the United States is substantial. Broadening adult immunization efforts beyond influenza only may help reduce the economic burden of adult VPD, and a pneumococcal vaccination effort, primarily focused on reducing NPP, may constitute a logical starting place. Sensitivity analyses revealed that a pandemic influenza season or change in size of the US elderly population

A game-theoretic framework for estimating a health purchaser's willingness-to-pay for health and for expansion.

Science.gov (United States)

Yaesoubi, Reza; Roberts, Stephen D

2010-12-01

A health purchaser's willingness-to-pay (WTP) for health is defined as the amount of money the health purchaser (e.g. a health maximizing public agency or a profit maximizing health insurer) is willing to spend for an additional unit of health. In this paper, we propose a game-theoretic framework for estimating a health purchaser's WTP for health in markets where the health purchaser offers a menu of medical interventions, and each individual in the population selects the intervention that maximizes her prospect. We discuss how the WTP for health can be employed to determine medical guidelines, and to price new medical technologies, such that the health purchaser is willing to implement them. The framework further introduces a measure for WTP for expansion, defined as the amount of money the health purchaser is willing to pay per person in the population served by the health provider to increase the consumption level of the intervention by one percent without changing the intervention price. This measure can be employed to find how much to invest in expanding a medical program through opening new facilities, advertising, etc. Applying the proposed framework to colorectal cancer screening tests, we estimate the WTP for health and the WTP for expansion of colorectal cancer screening tests for the 2005 US population.

Estimating irrigation water use in the humid eastern United States

Science.gov (United States)

Levin, Sara B.; Zarriello, Phillip J.

2013-01-01

Accurate accounting of irrigation water use is an important part of the U.S. Geological Survey National Water-Use Information Program and the WaterSMART initiative to help maintain sustainable water resources in the Nation. Irrigation water use in the humid eastern United States is not well characterized because of inadequate reporting and wide variability associated with climate, soils, crops, and farming practices. To better understand irrigation water use in the eastern United States, two types of predictive models were developed and compared by using metered irrigation water-use data for corn, cotton, peanut, and soybean crops in Georgia and turf farms in Rhode Island. Reliable metered irrigation data were limited to these areas. The first predictive model that was developed uses logistic regression to predict the occurrence of irrigation on the basis of antecedent climate conditions. Logistic regression equations were developed for corn, cotton, peanut, and soybean crops by using weekly irrigation water-use data from 36 metered sites in Georgia in 2009 and 2010 and turf farms in Rhode Island from 2000 to 2004. For the weeks when irrigation was predicted to take place, the irrigation water-use volume was estimated by multiplying the average metered irrigation application rate by the irrigated acreage for a given crop. The second predictive model that was developed is a crop-water-demand model that uses a daily soil water balance to estimate the water needs of a crop on a given day based on climate, soil, and plant properties. Crop-water-demand models were developed independently of reported irrigation water-use practices and relied on knowledge of plant properties that are available in the literature. Both modeling approaches require accurate accounting of irrigated area and crop type to estimate total irrigation water use. Water-use estimates from both modeling methods were compared to the metered irrigation data from Rhode Island and Georgia that were used to

Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles

International Nuclear Information System (INIS)

Sun, Fengchun; Hu, Xiaosong; Zou, Yuan; Li, Siguang

2011-01-01

An accurate battery State of Charge estimation is of great significance for battery electric vehicles and hybrid electric vehicles. This paper presents an adaptive unscented Kalman filtering method to estimate State of Charge of a lithium-ion battery for battery electric vehicles. The adaptive adjustment of the noise covariances in the State of Charge estimation process is implemented by an idea of covariance matching in the unscented Kalman filter context. Experimental results indicate that the adaptive unscented Kalman filter-based algorithm has a good performance in estimating the battery State of Charge. A comparison with the adaptive extended Kalman filter, extended Kalman filter, and unscented Kalman filter-based algorithms shows that the proposed State of Charge estimation method has a better accuracy. -- Highlights: → Adaptive unscented Kalman filtering is proposed to estimate State of Charge of a lithium-ion battery for electric vehicles. → The proposed method has a good performance in estimating the battery State of Charge. → A comparison with three other Kalman filtering algorithms shows that the proposed method has a better accuracy.

A concise account of techniques available for shipboard sea state estimation

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam

2017-01-01

This article gives a review of techniques applied to make sea state estimation on the basis of measured responses on a ship. The general concept of the procedures is similar to that of a classical wave buoy, which exploits a linear assumption between waves and the associated motions. In the frequ......This article gives a review of techniques applied to make sea state estimation on the basis of measured responses on a ship. The general concept of the procedures is similar to that of a classical wave buoy, which exploits a linear assumption between waves and the associated motions...

National Health Expenditure Data

Data.gov (United States)

U.S. Department of Health & Human Services — National Health Expenditure Accounts are comprised of the following, National Health Expenditures - Historical and Projected, Age Estimates, State Health...

A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

Directory of Open Access Journals (Sweden)

Hongxiao Yu

2015-05-01

Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

Dynamic state estimation and prediction for real-time control and operation

NARCIS (Netherlands)

Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.

2013-01-01

Real-time control and operation are crucial to deal with increasing complexity of modern power systems. To effectively enable those functions, it is required a Dynamic State Estimation (DSE) function to provide accurate network state variables at the right moment and predict their trends ahead. This

Kalman-Filter-Based State Estimation for System Information Exchange in a Multi-bus Islanded Microgrid

DEFF Research Database (Denmark)

Wang, Yanbo; Tian, Yanjun; Wang, Xiongfei

2014-01-01

State monitoring and analysis of distribution systems has become an urgent issue, and state estimation serves as an important tool to deal with it. In this paper, a Kalman-Filter-based state estimation method for a multi-bus islanded microgrid is presented. First, an overall small signal model wi...

Stated time preferences for health: a systematic review and meta analysis of private and social discount rates.

Science.gov (United States)

Mahboub-Ahari, Alireza; Pourreza, Abolghasem; Sari, Ali Akbari; Rahimi Foroushani, Abbas; Heydari, Hassan

2014-01-01

The present study aimed to provide better insight on methodological issues related to time preference studies, and to estimate private and social discount rates, using a rigorous systematic review and meta-analysis. We searched PubMed, EMBASE and Proquest databases in June 2013. All studies had estimated private and social time preference rates for health outcomes through stated preference approach, recognized eligible for inclusion. We conducted both fixed and random effect meta-analyses using mean discount rate and standard deviation of the included studies. I-square statistics was used for testing heterogeneity of the studies. Private and social discount rates were estimated separately via Stata11 software. Out of 44 screened full texts, 8 population-based empirical studies were included in qualitative synthesis. Reported time preference rates for own health were from 0.036 to 0.07 and for social health from 0.04 to 0.2. Private and social discount rates were estimated at 0.056 (95% CI: 0.038, 0.074) and 0.066 (95% CI: 0.064, 0.068), respectively. Considering the impact of time preference on healthy behaviors and because of timing issues, individual's time preference as a key determinant of policy making should be taken into account. Direct translation of elicited discount rates to the official discount rates has been remained questionable. Decisions about the proper discount rate for health context, may need a cross-party consensus among health economists and policy makers.

A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors.

Science.gov (United States)

Song, Yu; Nuske, Stephen; Scherer, Sebastian

2016-12-22

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight.

Trends in pregnancies and pregnancy rates by outcome: estimates for the United States, 1976-96.

Science.gov (United States)

Ventura, S J; Mosher, W D; Curtin, S C; Abma, J C; Henshaw, S

2000-01-01

This report presents national estimates of pregnancies and pregnancy rates according to women's age, race, and Hispanic origin, and by marital status, race, and Hispanic origin. Data are presented for 1976-96. Data from the National Survey of Family Growth (NSFG) are used to show information on sexual activity, contraceptive practices, and infertility, as well as women's reports of pregnancy intentions. Tables of pregnancy rates and the factors affecting pregnancy rates are presented and interpreted. Birth data are from the birth-registration system for all births registered in the United States and reported by State health departments to NCHS; abortion data are from The Alan Guttmacher Institute (AGI) and the National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC); and fetal loss data are from pregnancy history information collected in the NSFG. In 1996 an estimated 6.24 million pregnancies resulted in 3.89 million live births, 1.37 million induced abortions, and 0.98 million fetal losses. The pregnancy rate in 1996 was 104.7 pregnancies per 1,000 women aged 15-44 years, 9 percent lower than in 1990 (115.6), and the lowest recorded since 1976 (102.7). Since 1990 rates have dropped 8 percent for live births, 16 percent for induced abortions, and 4 percent for fetal losses. The teenage pregnancy rate has declined considerably in the 1990's, falling 15 percent from its 1991 high of 116.5 per 1,000 women aged 15-19 years to 98.7 in 1996. Among the factors accounting for this decline are decreased sexual activity, increases in condom use, and the adoption of the injectable and implant contraceptives.

A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

KAUST Repository

Ait-El-Fquih, Boujemaa; El Gharamti, Mohamad; Hoteit, Ibrahim

2016-01-01

Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface ground-water models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model's state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKF(OSA). Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25% more accurate state and parameter estimations than the joint and dual approaches.

A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

KAUST Repository

Ait-El-Fquih, Boujemaa

2016-08-12

Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface ground-water models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model\\'s state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKF(OSA). Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25% more accurate state and parameter estimations than the joint and dual approaches.

Distributed and decentralized state estimation in gas networks as distributed parameter systems.

Science.gov (United States)

Ahmadian Behrooz, Hesam; Boozarjomehry, R Bozorgmehry

2015-09-01

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline networks. In the construction of local models, due to the existence of common states and interconnections among the subsystems, the assimilation and prediction steps of the Kalman filter are modified to take the overlapping and external states into account. However, dynamic Riccati equation for each subsystem is constructed based on the local model, which introduces a maximum error of 5% in the estimated standard deviation of the states in the benchmarks studied in this paper. The performance of the proposed methodology has been shown based on the comparison of its accuracy and computational demands against their counterparts in centralized Kalman filter for two viable benchmarks. In a real life network, it is shown that while the accuracy is not significantly decreased, the real-time factor of the state estimation is increased by a factor of 10. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

Science.gov (United States)

Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

2013-01-01

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Estimating health service utilization for treatment of pneumococcal disease: the case of Brazil.

Science.gov (United States)

Sartori, A M C; Novaes, C G; de Soárez, P C; Toscano, C M; Novaes, H M D

2013-07-02

Health service utilization (HSU) is an essential component of economic evaluations of health initiatives. Defining HSU for cases of pneumococcal disease (PD) is particularly complex considering the varying clinical manifestations and diverse severity. We describe the process of developing estimates of HSU for PD as part of an economic evaluation of the introduction of pneumococcal conjugate vaccine in Brazil. Nationwide inpatient and outpatient HSU by children under-5 years with meningitis (PM), sepsis (PS), non-meningitis non-sepsis invasive PD (NMNS), pneumonia, and acute otitis media (AOM) was estimated. We assumed that all cases of invasive PD (PM, PS, and NMNS) required hospitalization. The study perspective was the health system, including both the public and private sectors. Data sources were obtained from national health information systems, including the Hospital Information System (SIH/SUS) and the Notifiable Diseases Information System (SINAN); surveys; and community-based and health care facility-based studies. We estimated hospitalization rates of 7.69 per 100,000 children under-5 years for PM (21.4 for children Brazil. Estimating HSU for noninvasive disease was challenging, particularly in the case of outpatient care, for which secondary data are scarce. Information for the private sector is lacking in Brazil, but estimates were possible with data from the public sector and national population surveys. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparative Study of Online Open Circuit Voltage Estimation Techniques for State of Charge Estimation of Lithium-Ion Batteries

Directory of Open Access Journals (Sweden)

Hicham Chaoui

2017-04-01

Full Text Available Online estimation techniques are extensively used to determine the parameters of various uncertain dynamic systems. In this paper, online estimation of the open-circuit voltage (OCV of lithium-ion batteries is proposed by two different adaptive filtering methods (i.e., recursive least square, RLS, and least mean square, LMS, along with an adaptive observer. The proposed techniques use the battery’s terminal voltage and current to estimate the OCV, which is correlated to the state of charge (SOC. Experimental results highlight the effectiveness of the proposed methods in online estimation at different charge/discharge conditions and temperatures. The comparative study illustrates the advantages and limitations of each online estimation method.

Connections of geometric measure of entanglement of pure symmetric states to quantum state estimation

International Nuclear Information System (INIS)

Chen Lin; Zhu Huangjun; Wei, Tzu-Chieh

2011-01-01

We study the geometric measure of entanglement (GM) of pure symmetric states related to rank 1 positive-operator-valued measures (POVMs) and establish a general connection with quantum state estimation theory, especially the maximum likelihood principle. Based on this connection, we provide a method for computing the GM of these states and demonstrate its additivity property under certain conditions. In particular, we prove the additivity of the GM of pure symmetric multiqubit states whose Majorana points under Majorana representation are distributed within a half sphere, including all pure symmetric three-qubit states. We then introduce a family of symmetric states that are generated from mutually unbiased bases and derive an analytical formula for their GM. These states include Dicke states as special cases, which have already been realized in experiments. We also derive the GM of symmetric states generated from symmetric informationally complete POVMs (SIC POVMs) and use it to characterize all inequivalent SIC POVMs in three-dimensional Hilbert space that are covariant with respect to the Heisenberg-Weyl group. Finally, we describe an experimental scheme for creating the symmetric multiqubit states studied in this article and a possible scheme for measuring the permanence of the related Gram matrix.

Power System Real-Time Monitoring by Using PMU-Based Robust State Estimation Method

DEFF Research Database (Denmark)

Zhao, Junbo; Zhang, Gexiang; Das, Kaushik

2016-01-01

Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions...... the system real-time states with good robustness and can address several kinds of BD.......-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track...

Social capital, ideology, and health in the United States.

Science.gov (United States)

Herian, Mitchel N; Tay, Louis; Hamm, Joseph A; Diener, Ed

2014-03-01

Research from across disciplines has demonstrated that social and political contextual factors at the national and subnational levels can impact the health and health behavior risks of individuals. This paper examines the impact of state-level social capital and ideology on individual-level health outcomes in the U.S. Leveraging the variation that exists across states in the U.S., the results reveal that individuals report better health in states with higher levels of governmental liberalism and in states with higher levels of social capital. Critically, however, the effect of social capital was moderated by liberalism such that social capital was a stronger predictor of health in states with low levels of liberalism. We interpret this finding to mean that social capital within a political unit-as indicated by measures of interpersonal trust-can serve as a substitute for the beneficial impacts that might result from an active governmental structure. Copyright © 2014 Elsevier Ltd. All rights reserved.

A state-space Bayesian framework for estimating biogeochemical transformations using time-lapse geophysical data

Energy Technology Data Exchange (ETDEWEB)

Chen, J.; Hubbard, S.; Williams, K.; Pride, S.; Li, L.; Steefel, C.; Slater, L.

2009-04-15

We develop a state-space Bayesian framework to combine time-lapse geophysical data with other types of information for quantitative estimation of biogeochemical parameters during bioremediation. We consider characteristics of end-products of biogeochemical transformations as state vectors, which evolve under constraints of local environments through evolution equations, and consider time-lapse geophysical data as available observations, which could be linked to the state vectors through petrophysical models. We estimate the state vectors and their associated unknown parameters over time using Markov chain Monte Carlo sampling methods. To demonstrate the use of the state-space approach, we apply it to complex resistivity data collected during laboratory column biostimulation experiments that were poised to precipitate iron and zinc sulfides during sulfate reduction. We develop a petrophysical model based on sphere-shaped cells to link the sulfide precipitate properties to the time-lapse geophysical attributes and estimate volume fraction of the sulfide precipitates, fraction of the dispersed, sulfide-encrusted cells, mean radius of the aggregated clusters, and permeability over the course of the experiments. Results of the case study suggest that the developed state-space approach permits the use of geophysical datasets for providing quantitative estimates of end-product characteristics and hydrological feedbacks associated with biogeochemical transformations. Although tested here on laboratory column experiment datasets, the developed framework provides the foundation needed for quantitative field-scale estimation of biogeochemical parameters over space and time using direct, but often sparse wellbore data with indirect, but more spatially extensive geophysical datasets.

Health Spending by State of Residence, 1991–2009

Science.gov (United States)

Cuckler, Gigi; Martin, Anne; Whittle, Lekha; Heffler, Stephen; Sisko, Andrea; Lassman, Dave; Benson, Joseph

2011-01-01

Objective Provide a detailed discussion of baseline health spending by state of residence (per capita personal health care spending, per enrollee Medicare spending, and per enrollee Medicaid spending) in 2009, over the last decade (1998–2009), as well as the differential regional and state impacts of the recent recession. Data Source State Health Expenditures by State of Residence for 1991–2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. Principal Findings In 2009, the 10 states where per capita spending was highest ranged from 13 to 36 percent higher than the national average, and the 10 states where per capita spending was lowest ranged from 8 to 26 percent below the national average. States with the highest per capita spending tended to have older populations and the highest per capita incomes; states with the lowest per capita spending tended to have younger populations, lower per capita incomes, and higher rates of uninsured. Over the last decade, the New England and Mideast regions exhibited the highest per capita personal health care spending, while states in the Southwest and Rocky Mountain regions had the lowest per capita spending. Variation in per enrollee Medicaid spending, however, has consistently been greater than that of total per capita personal health care spending or per enrollee Medicare spending from 1998–2009. The Great Lakes, New England, and Far West regions experienced the largest slowdown in per person health spending growth during the recent recession, largely as a result of higher unemployment rates. PMID:22340779

Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Science.gov (United States)

This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.

Estimating health expectancies from two cross-sectional surveys: The intercensal method

Directory of Open Access Journals (Sweden)

Michel Guillot

2009-10-01

Full Text Available Health expectancies are key indicators for monitoring the health of populations, as well as for informing debates about compression or expansion of morbidity. However, current methodologies for estimating them are not entirely satisfactory. They are either of limited applicability because of high data requirements (the multistate method or based on questionable assumptions (the Sullivan method. This paper proposes a new method, called the "intercensal" method, which relies on the multistate framework but uses widely available data. The method uses age-specific proportions "healthy" at two successive, independent cross-sectional health surveys, and, together with information on general mortality, solves for the set of transition probabilities that produces the observed sequence of proportions healthy. The system is solved by making realistic parametric assumptions about the age patterns of transition probabilities. Using data from the Health and Retirement Survey (HRS and from the National Health Interview Survey (NHIS, the method is tested against both the multistate method and the Sullivan method. We conclude that the intercensal approach is a promising framework for the indirect estimation of health expectancies.

State-of-charge estimation in lithium-ion batteries: A particle filter approach

Science.gov (United States)

Tulsyan, Aditya; Tsai, Yiting; Gopaluni, R. Bhushan; Braatz, Richard D.

2016-11-01

The dynamics of lithium-ion batteries are complex and are often approximated by models consisting of partial differential equations (PDEs) relating the internal ionic concentrations and potentials. The Pseudo two-dimensional model (P2D) is one model that performs sufficiently accurately under various operating conditions and battery chemistries. Despite its widespread use for prediction, this model is too complex for standard estimation and control applications. This article presents an original algorithm for state-of-charge estimation using the P2D model. Partial differential equations are discretized using implicit stable algorithms and reformulated into a nonlinear state-space model. This discrete, high-dimensional model (consisting of tens to hundreds of states) contains implicit, nonlinear algebraic equations. The uncertainty in the model is characterized by additive Gaussian noise. By exploiting the special structure of the pseudo two-dimensional model, a novel particle filter algorithm that sweeps in time and spatial coordinates independently is developed. This algorithm circumvents the degeneracy problems associated with high-dimensional state estimation and avoids the repetitive solution of implicit equations by defining a 'tether' particle. The approach is illustrated through extensive simulations.

Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

Energy Technology Data Exchange (ETDEWEB)

Dhondt, Stijn, E-mail: stijn.dhondt@vub.ac.be [Department of Medical Sociology and Health Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090, Brussels (Belgium); Beckx, Carolien, E-mail: Carolien.Beckx@vito.be [Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol (Belgium); Degraeuwe, Bart, E-mail: Bart.Degraeuwe@vito.be [Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol (Belgium); Lefebvre, Wouter, E-mail: Wouter.Lefebvre@vito.be [Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol (Belgium); Kochan, Bruno, E-mail: Bruno.Kochan@uhasselt.be [Transportation Research Institute, Hasselt University, Wetenschapspark 5 bus 6, 3590 Diepenbeek (Belgium); Bellemans, Tom, E-mail: Tom.Bellemans@uhasselt.be [Transportation Research Institute, Hasselt University, Wetenschapspark 5 bus 6, 3590 Diepenbeek (Belgium); Int Panis, Luc, E-mail: Luc.intpanis@vito.be [Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol (Belgium); Transportation Research Institute, Hasselt University, Wetenschapspark 5 bus 6, 3590 Diepenbeek (Belgium); Macharis, Cathy, E-mail: cjmachar@vub.ac.be [Department MOSI-Transport and Logistics, Vrije Universiteit Brussel, Pleinlaan 2, B-1050, Brussels (Belgium); Putman, Koen, E-mail: kputman@vub.ac.be [Department of Medical Sociology and Health Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090, Brussels (Belgium); Interuniversity Centre for Health Economics Research (I-CHER), Vrije Universiteit Brussel, Brussels (Belgium)

2012-09-15

In both ambient air pollution epidemiology and health impact assessment an accurate assessment of the population exposure is crucial. Although considerable advances have been made in assessing human exposure outdoors, the assessments often do not consider the impact of individual travel behavior on such exposures. Population-based exposures to NO{sub 2} and O{sub 3} using only home addresses were compared with models that integrate all time-activity patterns-including time in commute-for Flanders and Brussels. The exposure estimates were used to estimate the air pollution impact on years of life lost due to respiratory mortality. Health impact of NO{sub 2} using an exposure that integrates time-activity information was on average 1.2% higher than when assuming that people are always at their home address. For ozone the overall estimated health impact was 0.8% lower. Local differences could be much larger, with estimates that differ up to 12% from the exposure using residential addresses only. Depending on age and gender, deviations from the population average were seen. Our results showed modest differences on a regional level. At the local level, however, time-activity patterns indicated larger differences in exposure and health impact estimates, mainly for people living in more rural areas. These results suggest that for local analyses the dynamic approach can contribute to an improved assessment of the health impact of various types of pollution and to the understanding of exposure differences between population groups. - Highlights: Black-Right-Pointing-Pointer Exposure to ambient air pollution was assessed integrating population mobility. Black-Right-Pointing-Pointer This dynamic exposure was integrated into a health impact assessment. Black-Right-Pointing-Pointer Differences between the dynamic and residential exposure were quantified. Black-Right-Pointing-Pointer Modest differences in health impact were found at a regional level. Black

Estimating the Health and Economic Impacts of Changes in Local Air Quality

Science.gov (United States)

Carvour, Martha L.; Hughes, Amy E.; Fann, Neal

2018-01-01

Objectives. To demonstrate the benefits-mapping software Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE), which integrates local air quality data with previously published concentration–response and health–economic valuation functions to estimate the health effects of changes in air pollution levels and their economic consequences. Methods. We illustrate a local health impact assessment of ozone changes in the 10-county nonattainment area of the Dallas–Fort Worth region of Texas, estimating the short-term effects on mortality predicted by 2 scenarios for 3 years (2008, 2011, and 2013): an incremental rollback of the daily 8-hour maximum ozone levels of all area monitors by 10 parts per billion and a rollback-to-a-standard ambient level of 65 parts per billion at only monitors above that level. Results. Estimates of preventable premature deaths attributable to ozone air pollution obtained by the incremental rollback method varied little by year, whereas those obtained by the rollback-to-a-standard method varied by year and were sensitive to the choice of ordinality and the use of preloaded or imported data. Conclusions. BenMAP-CE allows local and regional public health analysts to generate timely, evidence-based estimates of the health impacts and economic consequences of potential policy options in their communities. PMID:29698094

Pre-Trained Neural Networks used for Non-Linear State Estimation

DEFF Research Database (Denmark)

Bayramoglu, Enis; Andersen, Nils Axel; Ravn, Ole

2011-01-01

of the paramters in the distribution. This transformation is approximated by a neural network using offline training, which is based on monte carlo sampling. In the paper, there will also be presented a method to construct a flexible distributions well suited for covering the effect of the non-linearities......The paper focuses on nonlinear state estimation assuming non-Gaussian distributions of the states and the disturbances. The posterior distribution and the aposteriori distribution is described by a chosen family of paramtric distributions. The state transformation then results in a transformation...

A Methodology of Health Effects Estimation from Air Pollution in Large Asian Cities