WorldWideScience

Sample records for cognitive state estimation

  1. 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)

  2. Why is Mini-Mental state examination performance correlated with estimated premorbid cognitive ability?

    Science.gov (United States)

    Dykiert, D; Der, G; Starr, J M; Deary, I J

    2016-09-01

    Tests requiring the pronunciation of irregular words are used to estimate premorbid cognitive ability in patients with clinical diagnoses, and prior cognitive ability in normal ageing. However, scores on these word-reading tests correlate with scores on the Mini-Mental State Examination (MMSE), a widely used screening test for possible cognitive pathology. This study aimed to test whether the word-reading tests' correlations with MMSE scores in healthy older people are explained by childhood IQ or education. Wechsler Test of Adult Reading (WTAR), National Adult Reading Test (NART), MMSE scores and information about education were obtained from 1024 70-year-olds, for whom childhood intelligence test scores were available. WTAR and NART were positively correlated with the MMSE (r ≈ 0.40, p < 0.001). The shared variance of WTAR and NART with MMSE was significantly attenuated by ~70% after controlling for childhood intelligence test scores. Education explained little additional variance in the association between the reading tests and the MMSE. MMSE, which is often used to index cognitive impairment, is associated with prior cognitive ability. MMSE score is related to scores on WTAR and NART largely due to their shared association with prior ability. Obtained MMSE scores should be interpreted in the context of prior ability (or WTAR/NART score as its proxy).

  3. The Compression Flow as a Measure to Estimate the Cognitive Impairment Severity in Resting State fMRI and 18FDG-PET Alzheimer's Disease Connectomes

    Directory of Open Access Journals (Sweden)

    Antonio Giuliano Zippo

    2015-12-01

    Full Text Available The human brain appears organized in compartments characterized by seemingly specific functional purposes on many spatial scales. A complementary functional state binds information from specialized districts to return what is called integrated information. This fundamental network dynamics undergoes to severe disarrays in diverse degenerative conditions such as Alzheimer's Diseases (AD. The AD represents a multifarious syndrome characterized by structural, functional and metabolic landmarks. In particular, in the early stages of AD, adaptive functional modifications of the brain networks mislead initial diagnoses because cognitive abilities may result indiscernible from normal subjects. As a matter of facts, current measures of functional integration fail to catch significant differences among normal, mild cognitive impairment (MCI and even AD subjects. The aim of this work is to introduce a new topological feature called Compression Flow (CF to finely estimate the extent of the functional integration in the brain networks. The method uses a Monte Carlo-like estimation of the information integration flows returning the compression ratio between the size of the injected information and the size of the condensed information within the network. We analyzed the resting state connectomes of 75 subjects of the Alzheimer's Disease Neuroimaging Initiative 2 (ADNI repository. Our analyses are focused on the 18FGD-PET and functional MRI (fMRI acquisitions in several clinical screening conditions. Results indicated that CF effectively discriminate MCI, AD and normal subjects by showing a significant decrease of the functional integration in the AD and MCI brain connectomes. This result did not emerge by using a set of common complex network statistics. Furthermore, CF was best correlated with individual clinical scoring scales. In conclusion, we presented a novel measure to quantify the functional integration that resulted efficient to discriminate

  4. 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

  5. Channel Selection and Feature Projection for Cognitive Load Estimation Using Ambulatory EEG

    Directory of Open Access Journals (Sweden)

    Tian Lan

    2007-01-01

    Full Text Available We present an ambulatory cognitive state classification system to assess the subject's mental load based on EEG measurements. The ambulatory cognitive state estimator is utilized in the context of a real-time augmented cognition (AugCog system that aims to enhance the cognitive performance of a human user through computer-mediated assistance based on assessments of cognitive states using physiological signals including, but not limited to, EEG. This paper focuses particularly on the offline channel selection and feature projection phases of the design and aims to present mutual-information-based techniques that use a simple sample estimator for this quantity. Analyses conducted on data collected from 3 subjects performing 2 tasks (n-back/Larson at 2 difficulty levels (low/high demonstrate that the proposed mutual-information-based dimensionality reduction scheme can achieve up to 94% cognitive load estimation accuracy.

  6. An RSS based location estimation technique for cognitive relay networks

    KAUST Repository

    Qaraqe, Khalid A.; Hussain, Syed Imtiaz; Ç elebi, Hasari Burak; Abdallah, Mohamed M.; Alouini, Mohamed-Slim

    2010-01-01

    In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine

  7. 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.

  8. COGNITIVE MODELING OF EPISTEMIC MENTAL STATES

    Directory of Open Access Journals (Sweden)

    Yurovitskaya, L.N.

    2017-03-01

    Full Text Available Epistemic states of mind, connected with the cognitive activity of a man, are aimed not only at apprehending the world around us, but also at the process of this apprehension. A very important step on this way is an attempt to model these states and processes in terms of formal logics and semantics, irrespective of the language of cognition. The article presents the idea of how formal logical and linguistic modeling of the process of thinking shows the correlation and the interdependence of semantic units connected with mental activities of human brain. The basic notions of the conceptual field of cognition are presented in the article

  9. 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

  10. 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.

  11. 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...

  12. Cognitive deficits in the remitted state of unipolar depressive disorder

    DEFF Research Database (Denmark)

    Hasselbalch, Bo Jacob; Knorr, Ulla Benedichte Søsted; Hasselbalch, Steen

    2012-01-01

    Patients with unipolar depressive disorder may present with cognitive deficits in the remitted state, and the aim of the present study was to investigate whether cognitive deficits within specific cognitive domains are present.......Patients with unipolar depressive disorder may present with cognitive deficits in the remitted state, and the aim of the present study was to investigate whether cognitive deficits within specific cognitive domains are present....

  13. 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 ...

  14. 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.

  15. 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

  16. 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.

  17. An RSS based location estimation technique for cognitive relay networks

    KAUST Repository

    Qaraqe, Khalid A.

    2010-11-01

    In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine the location of the source using the direct and the relayed signal at the destination. We derive the Cramer-Rao lower bound (CRLB) expressions separately for x and y coordinates of the location estimate. We analyze the effects of cognitive behaviour of the relay on the performance of the proposed method. We also discuss and quantify the reliability of the location estimate using the proposed technique if the source is not stationary. The overall performance of the proposed method is presented through simulations. ©2010 IEEE.

  18. 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.

  19. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.

    Science.gov (United States)

    Allen, Genevera I; Amoroso, Nicola; Anghel, Catalina; Balagurusamy, Venkat; Bare, Christopher J; Beaton, Derek; Bellotti, Roberto; Bennett, David A; Boehme, Kevin L; Boutros, Paul C; Caberlotto, Laura; Caloian, Cristian; Campbell, Frederick; Chaibub Neto, Elias; Chang, Yu-Chuan; Chen, Beibei; Chen, Chien-Yu; Chien, Ting-Ying; Clark, Tim; Das, Sudeshna; Davatzikos, Christos; Deng, Jieyao; Dillenberger, Donna; Dobson, Richard J B; Dong, Qilin; Doshi, Jimit; Duma, Denise; Errico, Rosangela; Erus, Guray; Everett, Evan; Fardo, David W; Friend, Stephen H; Fröhlich, Holger; Gan, Jessica; St George-Hyslop, Peter; Ghosh, Satrajit S; Glaab, Enrico; Green, Robert C; Guan, Yuanfang; Hong, Ming-Yi; Huang, Chao; Hwang, Jinseub; Ibrahim, Joseph; Inglese, Paolo; Iyappan, Anandhi; Jiang, Qijia; Katsumata, Yuriko; Kauwe, John S K; Klein, Arno; Kong, Dehan; Krause, Roland; Lalonde, Emilie; Lauria, Mario; Lee, Eunjee; Lin, Xihui; Liu, Zhandong; Livingstone, Julie; Logsdon, Benjamin A; Lovestone, Simon; Ma, Tsung-Wei; Malhotra, Ashutosh; Mangravite, Lara M; Maxwell, Taylor J; Merrill, Emily; Nagorski, John; Namasivayam, Aishwarya; Narayan, Manjari; Naz, Mufassra; Newhouse, Stephen J; Norman, Thea C; Nurtdinov, Ramil N; Oyang, Yen-Jen; Pawitan, Yudi; Peng, Shengwen; Peters, Mette A; Piccolo, Stephen R; Praveen, Paurush; Priami, Corrado; Sabelnykova, Veronica Y; Senger, Philipp; Shen, Xia; Simmons, Andrew; Sotiras, Aristeidis; Stolovitzky, Gustavo; Tangaro, Sabina; Tateo, Andrea; Tung, Yi-An; Tustison, Nicholas J; Varol, Erdem; Vradenburg, George; Weiner, Michael W; Xiao, Guanghua; Xie, Lei; Xie, Yang; Xu, Jia; Yang, Hojin; Zhan, Xiaowei; Zhou, Yunyun; Zhu, Fan; Zhu, Hongtu; Zhu, Shanfeng

    2016-06-01

    Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Advanced Physiological Estimation of Cognitive Status. Part 2

    Science.gov (United States)

    2011-05-24

    fatigue, overload) Technology Transfer Opportunity Technology from PDT – Methods to acquire various physiological signals (EEG, EOG , EMG, ECG, etc...Integrated Hardware for Experiments EEG Sensor Array EOG Sensor Array Eye Tracker Amplifiers and Signal Conditioners Laptop Computer...REPORT Advanced Physiological Estimation of Cognitive Status - Part II 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: This report describes ongoing work

  1. On the Estimation of Standard Errors in Cognitive Diagnosis Models

    Science.gov (United States)

    Philipp, Michel; Strobl, Carolin; de la Torre, Jimmy; Zeileis, Achim

    2018-01-01

    Cognitive diagnosis models (CDMs) are an increasingly popular method to assess mastery or nonmastery of a set of fine-grained abilities in educational or psychological assessments. Several inference techniques are available to quantify the uncertainty of model parameter estimates, to compare different versions of CDMs, or to check model…

  2. 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

  3. 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.

  4. State Estimation for Humanoid Robots

    Science.gov (United States)

    2015-07-01

    how the noise is modeled. In the original paper [23], the UKF formulation does not assume additive noise, and it augments the state mean and covariance...with state constraints is an open research area, and there have been many studies in the past few decades. A recent survey paper on this topic [52...3.1 USB-based microcontroller board, and an adapter board that connects them. The Teensy board provides 3.3V DC power to the IMUs, and receives data

  5. Cognitive profiles and heritability estimates in the Old Order Amish.

    Science.gov (United States)

    Kuehner, Ryan M; Kochunov, Peter; Nugent, Katie L; Jurius, Deanna E; Savransky, Anya; Gaudiot, Christopher; Bruce, Heather A; Gold, James; Shuldiner, Alan R; Mitchell, Braxton D; Hong, L Elliot

    2016-08-01

    This study aimed to establish the applicability of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in the Old Order Amish (OOA) and to assess the genetic contribution toward the RBANS total score and its cognitive domains using a large family-based sample of OOA. RBANS data were collected in 103 OOA individuals from Lancaster County, Pennsylvania, including 85 individuals without psychiatric illness and 18 individuals with current psychiatric diagnoses. The RBANS total score and all five cognitive domains of in nonpsychiatric OOA were within half a SD of the normative data of the general population. The RBANS total score was highly heritable (h=0.51, P=0.019). OOA with psychiatric diagnoses had a numerically lower RBANS total score and domain scores compared with the nonpsychiatric participants. The RBANS appears to be a suitable cognitive battery for the OOA population as measurements obtained from the OOA are comparable with normative data in the US population. The heritability estimated from the OOA is in line with heritabilities of other cognitive batteries estimated in other populations. These results support the use of RBANS in cognitive assessment, clinical care, and behavioral genetic studies of neuropsychological functioning in this population.

  6. 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.

  7. 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

  8. 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.

  9. Information matrix estimation procedures for cognitive diagnostic models.

    Science.gov (United States)

    Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei

    2018-03-06

    Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.

  10. 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.

  11. 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.

  12. 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

  13. 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...

  14. 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...

  15. 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.

  16. 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...

  17. Activity flow over resting-state networks shapes cognitive task activations.

    Science.gov (United States)

    Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

    2016-12-01

    Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. Mini‑Mental State Exam versus Montreal Cognitive Assessment in ...

    African Journals Online (AJOL)

    Background: Mini‑mental state exam (MMSE) was used several times but no study has examined cognition on the Montreal Cognitive Assessment (MoCA) in diabetes and diabetic retinopathy (DR). In this study, we compared MMSE with MoCA in patients with DR and searched for an association between the severity of DR ...

  3. 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

  4. 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.

  5. 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

  6. State Mindfulness During Meditation Predicts Enhanced Cognitive Reappraisal

    OpenAIRE

    Garland, Eric L.; Hanley, Adam; Farb, Norman A.; Froeliger, Brett E.

    2013-01-01

    Putatively, mindfulness meditation involves generation of a state of “nonappraisal”, yet, little is known about how mindfulness may influence appraisal processes. We investigated whether the state and practice of mindfulness could enhance cognitive reappraisal. Participants (N = 44; M age = 24.44, SD = 4.00, range 19 – 38, 82.2% female) were randomized to either 1) mindfulness, 2) suppression, or 3) mind-wandering induction training conditions. Cognitive reappraisal was assessed with the Emot...

  7. A Parameter Estimation Method for Dynamic Computational Cognitive Models

    NARCIS (Netherlands)

    Thilakarathne, D.J.

    2015-01-01

    A dynamic computational cognitive model can be used to explore a selected complex cognitive phenomenon by providing some features or patterns over time. More specifically, it can be used to simulate, analyse and explain the behaviour of such a cognitive phenomenon. It generates output data in the

  8. 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.

  9. The Problem State : A Cognitive Bottleneck in Multitasking

    NARCIS (Netherlands)

    Borst, Jelmer P.; Taatgen, Niels A.; van Rijn, Hedderik

    The main challenge for theories of multitasking is to predict when and how tasks interfere. He re, we focus on interference related to the problem state. a directly accessible intermediate representation of the current state of a task. On the basis of Salvucci and Taatgen's (2008) threaded cognition

  10. Visual steady state in relation to age and cognitive function

    DEFF Research Database (Denmark)

    Horwitz, Anna; Dyhr Thomsen, Mia; Wiegand, Iris

    2017-01-01

    Neocortical gamma activity is crucial for sensory perception and cognition. This study examines the value of using non-task stimulation-induced EEG oscillations to predict cognitive status in a birth cohort of healthy Danish males (Metropolit) with varying cognitive ability. In particular, we...... examine the steady-state VEP power response (SSVEP-PR) in the alpha (8Hz) and gamma (36Hz) bands in 54 males (avg. age: 62.0 years) and compare these with 10 young healthy participants (avg. age 27.6 years). Furthermore, we correlate the individual alpha-to-gamma difference in relative visual-area power...

  11. Cognitive Distortions in Depressed Women: Trait, or State Dependent?

    Directory of Open Access Journals (Sweden)

    Sedat BATMAZ

    2015-12-01

    Conclusion: The results have revealed that self-criticism, helplessness, hopelessness and preoccupation with danger related distortions had trait-like features, whereas self-blame related distortions were state dependent. This has clinical implications for the psychotherapeutic treatment of cognitive distortions in depression. Specifically, self-criticism related distortions should be managed during cognitive therapy for depression since the other subscales seem rather problematic. [JCBPR 2015; 4(3.000: 147-152

  12. Multilingualism and cognitive state in the oldest old.

    Science.gov (United States)

    Kavé, Gitit; Eyal, Nitza; Shorek, Aviva; Cohen-Mansfield, Jiska

    2008-03-01

    In this study, the authors examined whether the number of languages a person speaks predicts performance on 2 cognitive-screening tests. Data were drawn from a representative sample of the oldest Israeli Jewish population (N = 814, M age = 83.0 years; SD = 5.4) that was interviewed first in 1989 and then twice more within the following 12 years. Cognitive state differed significantly among groups of self-reported bilingual, trilingual, and multilingual individuals at each of the 3 interview waves. Regression analyses showed that the number of languages spoken contributed to the prediction of cognitive test scores beyond the effect of other demographic variables, such as age, gender, place of birth, age at immigration, or education. Multilingualism was also found to be a significant predictor of cognitive state in a group of individuals who acquired no formal education at all. Those who reported being most fluent in a language other than their mother tongue scored higher on average than did those whose mother tongue was their best language, but the effect of number of languages on cognitive state was significant in both groups, with no significant interaction. Results are discussed in the context of theories of cognitive reserve. (c) 2008 APA, all rights reserved.

  13. 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

  14. Visual steady state in relation to age and cognitive function.

    Science.gov (United States)

    Horwitz, Anna; Dyhr Thomsen, Mia; Wiegand, Iris; Horwitz, Henrik; Klemp, Marc; Nikolic, Miki; Rask, Lene; Lauritzen, Martin; Benedek, Krisztina

    2017-01-01

    Neocortical gamma activity is crucial for sensory perception and cognition. This study examines the value of using non-task stimulation-induced EEG oscillations to predict cognitive status in a birth cohort of healthy Danish males (Metropolit) with varying cognitive ability. In particular, we examine the steady-state VEP power response (SSVEP-PR) in the alpha (8Hz) and gamma (36Hz) bands in 54 males (avg. age: 62.0 years) and compare these with 10 young healthy participants (avg. age 27.6 years). Furthermore, we correlate the individual alpha-to-gamma difference in relative visual-area power (ΔRV) with cognitive scores for the older adults. We find that ΔRV decrease with age by just over one standard deviation when comparing young with old participants (pintelligence is significantly negatively correlated with ΔRV in the older adult cohort, even when processing speed, global cognition, executive function, memory, and education (pincrease in ΔRV of one standard deviation is associated with a reduction in intelligence of 48% of a standard deviation (p<0.01). Finally, we conclude that the difference in cerebral rhythmic activity between the alpha and gamma bands is associated with age and cognitive status, and that ΔRV therefore provide a non-subjective clinical tool with which to examine cognitive status in old age.

  15. Visual steady state in relation to age and cognitive function.

    Directory of Open Access Journals (Sweden)

    Anna Horwitz

    Full Text Available Neocortical gamma activity is crucial for sensory perception and cognition. This study examines the value of using non-task stimulation-induced EEG oscillations to predict cognitive status in a birth cohort of healthy Danish males (Metropolit with varying cognitive ability. In particular, we examine the steady-state VEP power response (SSVEP-PR in the alpha (8Hz and gamma (36Hz bands in 54 males (avg. age: 62.0 years and compare these with 10 young healthy participants (avg. age 27.6 years. Furthermore, we correlate the individual alpha-to-gamma difference in relative visual-area power (ΔRV with cognitive scores for the older adults. We find that ΔRV decrease with age by just over one standard deviation when comparing young with old participants (p<0.01. Furthermore, intelligence is significantly negatively correlated with ΔRV in the older adult cohort, even when processing speed, global cognition, executive function, memory, and education (p<0.05. In our preferred specification, an increase in ΔRV of one standard deviation is associated with a reduction in intelligence of 48% of a standard deviation (p<0.01. Finally, we conclude that the difference in cerebral rhythmic activity between the alpha and gamma bands is associated with age and cognitive status, and that ΔRV therefore provide a non-subjective clinical tool with which to examine cognitive status in old age.

  16. 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.

  17. 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....

  18. State Mindfulness During Meditation Predicts Enhanced Cognitive Reappraisal

    Science.gov (United States)

    Hanley, Adam; Farb, Norman A.; Froeliger, Brett E.

    2013-01-01

    Putatively, mindfulness meditation involves generation of a state of “nonappraisal”, yet, little is known about how mindfulness may influence appraisal processes. We investigated whether the state and practice of mindfulness could enhance cognitive reappraisal. Participants (N = 44; M age = 24.44, SD = 4.00, range 19 – 38, 82.2% female) were randomized to either 1) mindfulness, 2) suppression, or 3) mind-wandering induction training conditions. Cognitive reappraisal was assessed with the Emotion Regulation Questionnaire (ERQ) prior to experimental induction, and state mindfulness was assessed immediately following induction using the Toronto Mindfulness Scale (TMS). Participants practiced their assigned strategy for one week and then were reassessed with the ERQ reappraisal subscale. Participants receiving mindfulness training reported significantly higher levels of state mindfulness than participants in the thought suppression and mind wandering conditions. Although brief mindfulness training did not lead to significantly greater increases in reappraisal than the other two conditions, state mindfulness during mindfulness meditation was prospectively associated with increases in reappraisal. Path analysis revealed that the indirect effect between mindfulness training and reappraisal was significant through state mindfulness. Degree of state mindfulness achieved during the act of mindfulness meditation significantly predicted increases in reappraisal over time, suggesting that mindfulness may promote emotion regulation by enhancing cognitive reappraisal. PMID:26085851

  19. State-dependent cognition and its relevance to cultural evolution.

    Science.gov (United States)

    Nettle, Daniel

    2018-02-05

    Individuals cope with their worlds by using information. In humans in particular, an important potential source of information is cultural tradition. Evolutionary models have examined when it is advantageous to use cultural information, and psychological studies have examined the cognitive biases and priorities that may transform cultural traditions over time. However, these studies have not generally incorporated the idea that individuals vary in state. I argue that variation in state is likely to influence the relative payoffs of using cultural information versus gathering personal information; and also that people in different states will have different cognitive biases and priorities, leading them to transform cultural information in different ways. I explore hunger as one example of state variable likely to have consequences for cultural evolution. Variation in state has the potential to explain why cultural traditions and dynamics are so variable between individuals and populations. It offers evolutionarily-grounded links between the ecology in which individuals live, individual-level cognitive processes, and patterns of culture. However, incorporating heterogeneity of state also makes the modelling of cultural evolution more complex, particularly if the distribution of states is itself influenced by the distribution of cultural beliefs and practices. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Montreal Cognitive Assessment and Mini-Mental State Examination reliable change indices in healthy older adults.

    Science.gov (United States)

    Kopecek, Miloslav; Bezdicek, Ondrej; Sulc, Zdenek; Lukavsky, Jiri; Stepankova, Hana

    2017-08-01

    Cognitive tests are used repeatedly to assess the treatment response or progression of cognitive disorders. The Montreal Cognitive Assessment (MoCA) is a valid screening test for mild cognitive impairment. The aim of our study was to establish 90% reliable change indices (RCI) for the MoCA together with the Mini-Mental State Examination (MMSE) in cognitively healthy older adults. We analyzed 197 cognitively healthy and functional independent volunteers aged 60-94 years, who met strict inclusion criteria for four consecutive years. The RCI methods by Chelune and Hsu were used. For 1, 2, and 3 years, the 90% RCI for MoCA using Chelune's formula were -4 ≤, ≥4; -4 ≤, ≥4 and -5 ≤, ≥4 points, respectively, and -3 ≤, ≥3 for the MMSE each year. Ninety percent RCI for MoCA using Hsu's formula ranged from -6 to 0, respectively, and +3 to +8 dependent on the baseline MoCA. Our study demonstrated RCI for the MoCA and MMSE in a 3-year time period that can be used for the estimation of cognitive decline or improvement in clinical settings. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Using neurophysiological signals that reflect cognitive or affective state

    NARCIS (Netherlands)

    Brouwer, Anne-Marie; Zander, Thorsten O.; van Erp, Johannes Bernardus Fransiscus

    2015-01-01

    What can we learn from spontaneously occurring brain and other physiological signals about an individual’s cognitive and affective state and how can we make use of this information? One line of research that is actively involved with this question is Passive Brain-Computer-Interfaces (BCI). To date

  2. Actions States and Communities Can Take to Address Cognitive Health

    Centers for Disease Control (CDC) Podcasts

    2014-06-09

    In this podcast, CDC’s Dr. Lynda Anderson highlights the important roles that states and communities can play in addressing cognitive health as part of overall health.  Created: 6/9/2014 by National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP).   Date Released: 6/9/2014.

  3. Cognitive constraints increase estimation biases: Cognitive load and delay in judgments

    OpenAIRE

    Allred, Sarah; Crawford, L. Elizabeth; Duffy, Sean; Smith, John

    2014-01-01

    Previous work has demonstrated that memory for simple stimuli can be biased by information about the category of which the stimulus is a member. These biases have been interpreted as optimally integrating noisy sensory information with category information. A separate literature has demonstrated that cognitive load can lead to biases in social cognition. Here we link the two, asking whether delay (Experiment 1) and cognitive load (Experiment 2) affect the extent to which observers' memories f...

  4. 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...

  5. EEG Estimates of Cognitive Workload and Engagement Predict Math Problem Solving Outcomes

    Science.gov (United States)

    Beal, Carole R.; Galan, Federico Cirett

    2012-01-01

    In the present study, the authors focused on the use of electroencephalography (EEG) data about cognitive workload and sustained attention to predict math problem solving outcomes. EEG data were recorded as students solved a series of easy and difficult math problems. Sequences of attention and cognitive workload estimates derived from the EEG…

  6. A comparison of the mini mental state exam to the Montreal cognitive assessment in identifying cognitive deficits in Parkinson's disease

    NARCIS (Netherlands)

    Zadikoff, Cindy; Fox, Susan H.; Tang-Wai, David F.; Thomsen, Teri; de Bie, Rob M. A.; Wadia, Pettarusup; Miyasaki, Janis; Duff-Canning, Sarah; Lang, Anthony E.; Marras, Connie

    2008-01-01

    Dementia is an important and increasingly recognized problem in Parkinson's disease (PD). The mini-mental state examination (MMSE) often fails to detect early cognitive decline. The Montreal cognitive assessment (MoCA) is a brief tool developed to detect mild cognitive impairment that assesses a

  7. The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

    Directory of Open Access Journals (Sweden)

    B. Alexander eDiaz

    2013-08-01

    Full Text Available Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ. Based on ARSQ data from 813 participants assessed after five minutes eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer’s disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease.

  8. The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

    Science.gov (United States)

    Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

    2013-01-01

    Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease. PMID:23964225

  9. Estimated maximal and current brain volume predict cognitive ability in old age

    Science.gov (United States)

    Royle, Natalie A.; Booth, Tom; Valdés Hernández, Maria C.; Penke, Lars; Murray, Catherine; Gow, Alan J.; Maniega, Susana Muñoz; Starr, John; Bastin, Mark E.; Deary, Ian J.; Wardlaw, Joanna M.

    2013-01-01

    Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging. PMID:23850342

  10. 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...

  11. Stated Preference Survey Estimating the Willingness to Pay ...

    Science.gov (United States)

    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

  12. 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.

  13. Estimating the Technology of Cognitive and Noncognitive Skill Formation. NBER Working Paper No. 15664

    Science.gov (United States)

    Cunha, Flavio; Heckman, James; Schennach, Susanne

    2010-01-01

    This paper formulates and estimates multistage production functions for childrens' cognitive and noncognitive skills. Skills are determined by parental environments and investments at different stages of childhood. We estimate the elasticity of substitution between investments in one period and stocks of skills in that period to assess the…

  14. SCREENING FOR POSTSTROKE COGNITIVE IMPAIRMENT VIA MINI MENTAL STATE EXAMINATION AND MONTREAL COGNITIVE ASSESSMENT SCALE

    Directory of Open Access Journals (Sweden)

    Mirena Valkova

    2012-10-01

    Full Text Available Objective: The aim of our study is to examine cognitive performance after mild stroke via Mini Mental State Examination (MMSE and Montreal cognitive assessment scale (MoCA and to compare the results.Material and methods: We examined 54 patients with mild stroke (aged 52 to 72 (mean 63.17, SD 5.96; 34 males and 20 females and 54 controls, adjusted by age, sex and education level. All subjects were tested via MMSE (Bulgarian version and MoCa (Bulgarian version. Data was collected in the single step model at the 90th day after stroke incident for patients and at the day of obtaining informed consent for controls. Results: Patients have poorer performance on both MMSE and MoCa than controls. MoCa has comparatively good discriminative validity and sensitivity.Conclusions: Although MMSE is one of the classical screening tools for cognitive impairment widely used in Bulgaria, other screening tools should not be ignored. On the basis of our results, MoCa is also a good screening instrument, especially for poststroke cognitive impairment.

  15. State Estimation for the Automotive SCR Process

    DEFF Research Database (Denmark)

    Zhou, Guofeng; Huusom, Jakob Kjøbsted; Jørgensen, John Bagterp

    2012-01-01

    Selective catalytic reduction (SCR) of NOx is a widely applied diesel engine exhaust gas aftertreatment technology. For advanced SCR process control, like model predictive control, full state information of the process is required. The ammonia coverage ratio inside the catalyst is difficult to me...

  16. Cognitive and affective components of challenge and threat states.

    Science.gov (United States)

    Meijen, Carla; Jones, Marc V; McCarthy, Paul J; Sheffield, David; Allen, Mark S

    2013-01-01

    We explored the cognitive and affective components of the Theory of Challenge and Threat States in Athletes (TCTSA) using a cross-sectional design. One hundred and seventy-seven collegiate athletes indicated how they typically approached an important competition on measures of self-efficacy, perceived control, achievement goals, emotional states and interpretation of emotional states. Participants also indicated to what extent they typically perceived the important competition as a challenge and/or a threat. The results suggest that a perception of challenge was not predicted by any of the cognitive components. A perception of threat was positively predicted by avoidance goals and negatively predicted by self-efficacy and approach goals. Both challenge and threat had a positive relationship with anxiety. Practical implications of this study are that an avoidance orientation appeared to be related to potentially negative constructs such as anxiety, threat and dejection. The findings may suggest that practitioners and researchers should focus on reducing an avoidance orientation, however the results should be treated with caution in applied settings, as this study did not examine how the combination of constructs exactly influences sport performance. The results provided partial support for the TCTSA with stronger support for proposed relationships with threat rather than challenge states.

  17. 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 ...

  18. 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...

  19. Exponentially convergent state estimation for delayed switched recurrent neural networks.

    Science.gov (United States)

    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.

  20. Montreal Cognitive Assessment and Mini-Mental State Examination are both valid cognitive tools in stroke.

    Science.gov (United States)

    Cumming, T B; Churilov, L; Linden, T; Bernhardt, J

    2013-08-01

    To determine the validity of the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) as screening tools for cognitive impairment after stroke. Cognitive assessments were administered over 2 sessions (1 week apart) at 3 months post-stroke. Scores on the MoCA and MMSE were evaluated against a diagnosis of cognitive impairment derived from a comprehensive neuropsychological battery (the criterion standard). Sixty patients participated in the study [mean age 72.1 years (SD = 13.9), mean education 10.5 years (SD = 3.9), median acute NIHSS score 5 (IQR 3-7)]. The MoCA yielded lower scores (median = 21, IQR = 17-24; mean = 20.0, SD = 5.4) than the MMSE (median = 26, IQR = 22-27; mean = 24.2, SD = 4.5). MMSE data were more skewed towards ceiling than MoCA data (skewness = -1.09 vs -0.73). Area under the receiver operator curve was higher for MoCA than for MMSE (0.87 vs 0.84), although this difference was not significant (χ(2) = 0.48, P = 0.49). At their optimal cut-offs, the MoCA had better sensitivity than the MMSE (0.92 vs 0.82) but poorer specificity (0.67 vs 0.76). The MoCA is a valid screening tool for post-stroke cognitive impairment; it is more sensitive but less specific than the MMSE. Contrary to the prevailing view, the MMSE also exhibited acceptable validity in this setting. © 2013 John Wiley & Sons A/S.

  1. 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...

  2. 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...

  3. Semi-Markov models for interval censored transient cognitive states with back transitions and a competing risk.

    Science.gov (United States)

    Wei, Shaoceng; Kryscio, Richard J

    2016-12-01

    Continuous-time multi-state stochastic processes are useful for modeling the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient cognitive states and death as a competing risk. Each subject's cognition is assessed periodically resulting in interval censoring for the cognitive states while death without dementia is not interval censored. Since back transitions among the transient states are possible, Markov chains are often applied to this type of panel data. In this manuscript, we apply a semi-Markov process in which we assume that the waiting times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and in which we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for likelihood estimation. We apply our model to a real dataset, the Nun Study, a cohort of 461 participants. © The Author(s) 2014.

  4. 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.

  5. 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.

  6. 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

  7. Crowdsourced estimation of cognitive decline and resilience in Alzheimer’s disease

    Science.gov (United States)

    Allen, Genevera I; Amoroso, Nicola; Anghel, Catalina; Balagurusamy, Venkat; Bare, Christopher J; Beaton, Derek; Bellotti, Roberto; Bennett, David A; Boehme, Kevin; Boutros, Paul C; Caberlotto, Laura; Caloian, Cristian; Campbell, Frederick; Neto, Elias Chaibub; Chang, Yu-Chuan; Chen, Beibei; Chen, Chien-Yu; Chien, Ting-Ying; Clark, Tim; Das, Sudeshna; Davatzikos, Christos; Deng, Jieyao; Dillenberger, Donna; Dobson, Richard JB; Dong, Qilin; Doshi, Jimit; Duma, Denise; Errico, Rosangela; Erus, Guray; Everett, Evan; Fardo, David W; Friend, Stephen H; Fröhlich, Holger; Gan, Jessica; St George-Hyslop, Peter; Ghosh, Satrajit S; Glaab, Enrico; Green, Robert C; Guan, Yuanfang; Hong, Ming-Yi; Huang, Chao; Hwang, Jinseub; Ibrahim, Joseph; Inglese, Paolo; Jiang, Qijia; Katsumata, Yuriko; Kong, Dehan; Krause, Roland; Lalonde, Emilie; Lauria, Mario; Lee, Eunjee; Lin, Xihui; Liu, Zhandong; Livingstone, Julie; Logsdon, Benjamin A; Lovestone, Simon; Lyappan, Anandhi; Ma, Michelle; Malhotra, Ashutosh; Maxwell, Taylor J; Merrill, Emily; Nagorski, John; Namasivayam, Aishwarya; Narayan, Manjari; Naz, Mufassra; Newhouse, Stephen J; Norman, Thea C; Nurtdinov, Ramil N; Oyang, Yen-Jen; Pawitan, Yudi; Peng, Shengwen; Piccolo, Stephen R; Praveen, Paurush; Priami, Corrado; Sabelnykova, Veronica Y; Senger, Philipp; Shen, Xia; Simmons, Andrew; Sotiras, Aristeidis; Stolovitzky, Gustavo; Tangaro, Sabina; Tateo, Andrea; Tung, Yi-An; Tustison, Nicholas J; Varol, Erdem; Vradenburg, George; Weiner, Michael W; Xiao, Guanghua; Xie, Lei; Xie, Yang; Xu, Jia; Yang, Hojin; Zhan, Xiaowei; Zhou, Yunyun; Zhu, Fan; Zhu, Hongtu; Zhu, Shanfeng

    2017-01-01

    Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer’s Disease. The Alzheimer’s Disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer’s Disease based on high-dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for to prediction of cognitive performance. PMID:27079753

  8. 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....

  9. 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.

  10. Cognitive two-way relay beamforming: Design with resilience to channel state uncertainties

    KAUST Repository

    Ubaidulla, P.; Alouini, Mohamed-Slim; Aissa, Sonia

    2016-01-01

    In this paper, we propose a robust distributed relay beamformer design for cognitive radio network operating under uncertainties in the available channel state information. The cognitive network consists of a pair of transceivers and a set of non

  11. Sensitivity of fNIRS to cognitive state and load

    Directory of Open Access Journals (Sweden)

    Frank Anthony Fishburn

    2014-02-01

    Full Text Available Functional near-infrared spectroscopy (fNIRS is an emerging low-cost noninvasive neuroimaging technique that measures cortical bloodflow. While fNIRS has gained interest as a potential alternative to fMRI for use with clinical and pediatric populations, it remains unclear whether fNIRS has the necessary sensitivity to serve as a replacement for fMRI. The present study set out to examine whether fNIRS has the sensitivity to detect linear changes in activation and functional connectivity in response to cognitive load, and functional connectivity changes when transitioning from a task-free resting state to a task. Sixteen young adult subjects were scanned with a continuous-wave fNIRS system during a 10-minute resting-state scan followed by a letter n-back task with three load conditions. Five optical probes were placed over frontal and parietal cortices, covering bilateral dorsolateral PFC (dlPFC, bilateral ventrolateral PFC (vlPFC, frontopolar cortex (FP, and bilateral parietal cortex. Activation was found to scale linearly with working memory load in bilateral prefrontal cortex. Functional connectivity increased with increasing n-back loads for fronto-parietal, interhemispheric dlPFC, and local connections. Functional connectivity differed between the resting state scan and the n-back scan, with fronto-parietal connectivity greater during the n-back, and interhemispheric vlPFC connectivity greater during rest. These results demonstrate that fNIRS is sensitive to both cognitive load and state, suggesting that fNIRS is well-suited to explore the full complement of neuroimaging research questions and will serve as a viable alternative to fMRI.

  12. 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.

  13. 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)

  14. 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...

  15. An Integrated Theory of Prospective Time Interval Estimation: The Role of Cognition, Attention, and Learning

    Science.gov (United States)

    Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John

    2007-01-01

    A theory of prospective time perception is introduced and incorporated as a module in an integrated theory of cognition, thereby extending existing theories and allowing predictions about attention and learning. First, a time perception module is established by fitting existing datasets (interval estimation and bisection and impact of secondary…

  16. 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.

  17. Cognitive relaying and power allocation under channel state uncertainties

    KAUST Repository

    Pandarakkottilil, Ubaidulla

    2013-04-01

    In this paper, we present robust joint relay precoder designs and transceiver power allocations for a cognitive radio network under imperfect channel state information (CSI). The secondary (or cognitive) network consists of a pair of single-antenna transceiver nodes and a non-regenerative two-way relay with multiple antennas which aids the communication process between the transceiver pair. The secondary nodes share the spectrum with a licensed primary user (PU) while guaranteeing that the interference to the PU receiver is maintained below a specified threshold. We consider two robust designs: the first is based on the minimization of the total transmit power of the secondary relay node required to provide the minimum quality of service, measured in terms of mean-square error (MSE) of the transceiver nodes, and the second is based on the minimization of the sum-MSE of the transceiver nodes. The robust designs are based on worst-case optimization and take into account known parameters of the error in the CSI to render the performance immune to the presence of errors in the CSI. Though the original problem is non-convex, we show that the proposed designs can be reformulated as tractable convex optimization problems that can be solved efficiently. We illustrate the performance of the proposed designs through some selected numerical simulations. © 2013 IEEE.

  18. 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%.

  19. 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

  20. 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.

  1. Nonlinear Filtering Techniques Comparison for Battery State Estimation

    Directory of Open Access Journals (Sweden)

    Aspasia Papazoglou

    2014-09-01

    Full Text Available The performance of estimation algorithms is vital for the correct functioning of batteries in electric vehicles, as poor estimates will inevitably jeopardize the operations that rely on un-measurable quantities, such as State of Charge and State of Health. This paper compares the performance of three nonlinear estimation algorithms: the Extended Kalman Filter, the Unscented Kalman Filter and the Particle Filter, where a lithium-ion cell model is considered. The effectiveness of these algorithms is measured by their ability to produce accurate estimates against their computational complexity in terms of number of operations and execution time required. The trade-offs between estimators' performance and their computational complexity are analyzed.

  2. 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.

  3. Fuzzy filter for state estimation of a glucoregulatory system.

    Science.gov (United States)

    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.

  4. Structure-function relationships in elderly resting-state-networks : influence of age and cognitive performance

    OpenAIRE

    Jockwitz, Christiane

    2016-01-01

    The aim of this work was to investigate the structure-function relationship in cognitive resting state networks in a large population-based elderly sample. The first study characterized the functional connectivity in four cognitive resting state networks with respect to age, gender and cognitive performance: Default Mode Network (DMN), executive, and left and right frontoparietal resting state networks. The second study assessed the structural correlates of the functional reorganization of th...

  5. Minimax estimation of qubit states with Bures risk

    Science.gov (United States)

    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.

  6. 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

  7. Comparison of montreal cognitive assessment and mini-mental state examination in evaluating cognitive domain deficit following aneurysmal subarachnoid haemorrhage.

    Directory of Open Access Journals (Sweden)

    George Kwok Chu Wong

    Full Text Available Cognitive deficits are common after aneurysmal subarachnoid haemorrhage (aSAH, and clinical evaluation is important for their management. Our hypothesis was that the Montreal Cognitive Assessment (MoCa is superior to the Mini-Mental State Examination (MMSE in screening for cognitive domain deficit in aSAH patients.We carried out a prospective observational and diagnostic accuracy study on Hong Kong aSAH patients aged 21 to 75 years who had been admitted within 96 hours of ictus. The domain-specific neuropsychological assessment battery, the MoCA and MMSE were administered 2-4 weeks and 1 year after ictus. A cognitive domain deficit was defined as a cognitive domain z score <-1.65 (below the fifth percentile. Cognitive impairment was defined as two or more cognitive domain deficits. The study is registered at ClinicalTrials.gov of the US National Institutes of Health (NCT01038193.Both the MoCA and the MMSE were successful in differentiating between patients with and without cognitive domain deficits and cognitive impairment at both assessment periods. At 1 year post-ictus, the MoCA produced higher area under the curve scores for cognitive impairment than the MMSE (MoCA, 0.92; 95% CI, 0.83 to 0.97 versus MMSE, 0.77; 95% CI, 0.66 to 0.83, p = 0.009.Cognitive domain deficits and cognitive impairment in patients with aSAH can be screened with the MoCA in both the subacute and chronic phases.

  8. Dynamic state estimation assisted power system monitoring and protection

    Science.gov (United States)

    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

  9. 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.

  10. Estimating annualized earthquake losses for the conterminous United States

    Science.gov (United States)

    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.

  11. Sex Differences in Fluid Reasoning: Manifest and Latent Estimates from the Cognitive Abilities Test

    Directory of Open Access Journals (Sweden)

    Joni M. Lakin

    2014-06-01

    Full Text Available The size and nature of sex differences in cognitive ability continues to be a source of controversy. Conflicting findings result from the selection of measures, samples, and methods used to estimate sex differences. Existing sex differences work on the Cognitive Abilities Test (CogAT has analyzed manifest variables, leaving open questions about sex differences in latent narrow cognitive abilities and the underlying broad ability of fluid reasoning (Gf. This study attempted to address these questions. A confirmatory bifactor model was used to estimate Gf and three residual narrow ability factors (verbal, quantitative, and figural. We found that latent mean differences were larger than manifest estimates for all three narrow abilities. However, mean differences in Gf were trivial, consistent with previous research. In estimating group variances, the Gf factor showed substantially greater male variability (around 20% greater. The narrow abilities varied: verbal reasoning showed small variability differences while quantitative and figural showed substantial differences in variance (up to 60% greater. These results add precision and nuance to the study of the variability and masking hypothesis.

  12. 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.

  13. 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.

  14. Cognitive screening in substance users: Diagnostic accuracies of the Mini-Mental State Examination, Addenbrooke's Cognitive Examination-Revised, and Montreal Cognitive Assessment.

    Science.gov (United States)

    Ridley, Nicole; Batchelor, Jennifer; Draper, Brian; Demirkol, Apo; Lintzeris, Nicholas; Withall, Adrienne

    2018-03-01

    Despite the considerable prevalence of cognitive impairment in substance-using populations, there has been little investigation of the utility of cognitive screening measures within this context. In the present study the accuracy of three cognitive screening measures in this population was examined-the Mini-Mental State Examination (MMSE), the Addenbrooke's Cognitive Examination-Revised (ACE-R), and the Montreal Cognitive Assessment (MoCA). A sample of 30 treatment-seeking substance users and 20 healthy individuals living in the community were administered the screening measures and a neuropsychological battery (NPB). Agreement of classification of cognitive impairment by the screening measures and NPB was examined. Results indicated that the ACE-R and MoCA had good discriminative ability in detection of cognitive impairment, with areas under the receiver-operating characteristic (ROC) curve of .85 (95% confidence interval, CI [.75. .94] and .84 (95% CI [.71, .93]) respectively. The MMSE had fair discriminative ability (.78, 95% CI [.65, .93]). The optimal cut-score for the ACE-R was 93 (impairment = score of 92 or less), at which it correctly classified 89% of individuals as cognitively impaired or intact, while the optimal cut-score for the MoCA was cognitive impairment in the context of substance use.

  15. Using Lego robots to estimate cognitive ability in children who have severe physical disabilities.

    Science.gov (United States)

    Cook, Albert M; Adams, Kim; Volden, Joanne; Harbottle, Norma; Harbottle, Cheryl

    2011-01-01

    To determine whether low-cost robots provide a means by which children with severe disabilities can demonstrate understanding of cognitive concepts. Ten children, ages 4 to 10, diagnosed with cerebral palsy and related motor conditions, participated. Participants had widely variable motor, cognitive and receptive language skills, but all were non-speaking. A Lego Invention 'roverbot' was used to carry out a range of functional tasks from single-switch replay of pre-stored movements to total control of the movement in two dimensions. The level of sophistication achieved on hierarchically arranged play tasks was used to estimate cognitive skills. The 10 children performed at one of the six hierarchically arranged levels from 'no interaction' through 'simple cause and effect' to 'development and execution of a plan'. Teacher interviews revealed that children were interested in the robot, enjoyed interacting with it and demonstrated changes in behaviour and social and language skills following interaction. Children with severe physical disabilities can control a Lego robot to perform un-structured play tasks. In some cases, they were able to display more sophisticated cognitive skills through manipulating the robot than in traditional standardised tests. Success with the robot could be a proxy measure for children who have cognitive abilities but cannot demonstrate them in standard testing.

  16. Vehicle State Information Estimation with the Unscented Kalman Filter

    Directory of Open Access Journals (Sweden)

    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.

  17. The state of the "state" debate in hypnosis: a view from the cognitive-behavioral perspective.

    Science.gov (United States)

    Chaves, J F

    1997-07-01

    For most of the past 50 years, hypnosis research has been driven by a debate about whether hypnotic phenomena can be best described and understood as the product of an altered state of consciousness. The meanings of some of the pivotal concepts in this debate and the nature of the phenomena that gave rise to them were ambiguous at the outset and led to misconceptions and surplus meanings that have obscured the debate through most of its history. The nature of the posited hypnotic state and its assumed consequences have changed during this period, reflecting the abandonment of untenable versions of hypnotic state theory. Carefully conducted studies in laboratories around the world have refined our understanding of hypnotic phenomena and helped identify the critical variables that interact to elicit them. With the maturation of the cognitive-behavioral perspective and the growing refinement of state conceptions of hypnosis, questions arise whether the state debate is still the axis about which hypnosis research and theory pivots. Although heuristic value of this debate has been enormous, we must guard against the cognitive constraints of our own metaphors and conceptual frameworks.

  18. 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

  19. Remote optimal state estimation over communication channels with random delays

    KAUST Repository

    Mahmoud, Magdi S.

    2014-01-22

    This paper considers the optimal estimation of linear systems over unreliable communication channels with random delays. In this work, it is assumed that the system to be estimated is far away from the filter. The observations of the system are capsulized without time stamp and then transmitted to the network node at which the filter is located. The probabilities of time delays are assumed to be known. The event-driven estimation scheme is applied in this paper and the estimate of the states is updated only at each time instant when any measurement arrives. To capture the feature of communication, the system considered is augmented, and the arrived measurements are regarded as the uncertain observations of the augmented system. The corresponding optimal estimation algorithm is proposed and additionally, a numerical simulation represents the performance of this work. © 2014 The authors. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  20. 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)

  1. Transitions across cognitive states and death among older adults in relation to education: A multistate survival model using data from six longitudinal studies.

    Science.gov (United States)

    Robitaille, Annie; van den Hout, Ardo; Machado, Robson J M; Bennett, David A; Čukić, Iva; Deary, Ian J; Hofer, Scott M; Hoogendijk, Emiel O; Huisman, Martijn; Johansson, Boo; Koval, Andriy V; van der Noordt, Maaike; Piccinin, Andrea M; Rijnhart, Judith J M; Singh-Manoux, Archana; Skoog, Johan; Skoog, Ingmar; Starr, John; Vermunt, Lisa; Clouston, Sean; Muniz Terrera, Graciela

    2018-04-01

    This study examines the role of educational attainment, an indicator of cognitive reserve, on transitions in later life between cognitive states (normal Mini-Mental State Examination (MMSE), mild MMSE impairment, and severe MMSE impairment) and death. Analysis of six international longitudinal studies was performed using a coordinated approach. Multistate survival models were used to estimate the transition patterns via different cognitive states. Life expectancies were estimated. Across most studies, a higher level of education was associated with a lower risk of transitioning from normal MMSE to mild MMSE impairment but was not associated with other transitions. Those with higher levels of education and socioeconomic status had longer nonimpaired life expectancies. This study highlights the importance of education in later life and that early life experiences can delay later compromised cognitive health. This study also demonstrates the feasibility and benefit in conducting coordinated analysis across multiple studies to validate findings. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  2. Resting-state slow wave power, healthy aging and cognitive performance

    OpenAIRE

    Eleni L. Vlahou; Franka Thurm; Iris-Tatjana Kolassa; Winfried Schlee

    2014-01-01

    Cognitive functions and spontaneous neural activity show significant changes over the life-span, but the interrelations between age, cognition and resting-state brain oscillations are not well understood. Here, we assessed performance on the Trail Making Test and resting-state magnetoencephalographic (MEG) recordings from 53 healthy adults (18–89 years old) to investigate associations between age-dependent changes in spontaneous oscillatory activity and cognitive performance. Results show tha...

  3. Lithium-Ion Battery Capacity Estimation: A Method Based on Visual Cognition

    Directory of Open Access Journals (Sweden)

    Yujie Cheng

    2017-01-01

    Full Text Available This study introduces visual cognition into Lithium-ion battery capacity estimation. The proposed method consists of four steps. First, the acquired charging current or discharge voltage data in each cycle are arranged to form a two-dimensional image. Second, the generated image is decomposed into multiple spatial-frequency channels with a set of orientation subbands by using non-subsampled contourlet transform (NSCT. NSCT imitates the multichannel characteristic of the human visual system (HVS that provides multiresolution, localization, directionality, and shift invariance. Third, several time-domain indicators of the NSCT coefficients are extracted to form an initial high-dimensional feature vector. Similarly, inspired by the HVS manifold sensing characteristic, the Laplacian eigenmap manifold learning method, which is considered to reveal the evolutionary law of battery performance degradation within a low-dimensional intrinsic manifold, is used to further obtain a low-dimensional feature vector. Finally, battery capacity degradation is estimated using the geodesic distance on the manifold between the initial and the most recent features. Verification experiments were conducted using data obtained under different operating and aging conditions. Results suggest that the proposed visual cognition approach provides a highly accurate means of estimating battery capacity and thus offers a promising method derived from the emerging field of cognitive computing.

  4. The Impact of Age and Cognitive Reserve on Resting-State Brain Connectivity

    Directory of Open Access Journals (Sweden)

    Jessica I. Fleck

    2017-12-01

    Full Text Available Cognitive reserve (CR is a protective mechanism that supports sustained cognitive function following damage to the physical brain associated with age, injury, or disease. The goal of the research was to identify relationships between age, CR, and brain connectivity. A sample of 90 cognitively normal adults, ages 45–64 years, had their resting-state brain activity recorded with electroencephalography (EEG and completed a series of memory and executive function assessments. CR was estimated using years of education and verbal IQ scores. Participants were divided into younger and older age groups and low- and high-CR groups. We observed greater left- than right-hemisphere coherence in younger participants, and greater right- than left-hemisphere coherence in older participants. In addition, greater coherence was observed under eyes-closed than eyes-open recording conditions for both low-CR and high-CR participants, with a more substantial difference between recording conditions in individuals high in CR regardless of age. Finally, younger participants low in CR exhibited greater mean coherence than younger participants high in CR, whereas the opposite pattern was observed in older participants, with greater coherence in older participants high in CR. Together, these findings suggest the possibility of a shift in the relationship between CR and brain connectivity during aging.

  5. Cognitive impairment in the remitted state of unipolar depressive disorder: A systematic review

    DEFF Research Database (Denmark)

    Hasselbalch, Bo Jacob; Knorr, Ulla; Kessing, Lars Vedel

    2010-01-01

    BACKGROUND: It is unclear whether cognitive impairment is prevalent in the remitted state of unipolar disorder. AIM: To evaluate whether cognitive function is impaired in the remitted state in patients with unipolar depression compared with healthy control individuals, and to investigate the asso...

  6. Survey of cognitive rehabilitation practices in the state of Kuwait.

    Science.gov (United States)

    Manee, Fahad S; Nadar, Mohammed Sh; Jassem, Zainab; Chavan, Shashidhar Rao

    2017-03-01

    Background Rehabilitation professionals must be astute at recognizing, assessing, and treating individuals with cognitive deficits. No research is available to examine cognitive rehabilitation practices applied to individuals with neurological conditions in Kuwait. To identify the use of cognitive assessments, the availability of resources, and the barriers to cognitive rehabilitation practices in Kuwait. Methods Face-to-face interviews were conducted with health care professionals working with adult individuals with neurological conditions. These professionals included occupational therapists, speech-language pathologists, psychiatrists, and neurologists. Results The most commonly used cognitive based assessments are MMSE (41%), and MoCA and LOTCA (15.2%). The only clinical assessment used is the Line-Bisection Test (2.2%). The most used occupation-based assessments are FIM (6.5%), COPM (4.3%), the Interest Checklist (2.2%), and the Barthel Index (2.2%). Resources related to cognitive rehabilitation in Kuwait that are unavailable to practitioners include journal clubs (91%), special interest groups (89%), and continuing education programmes (82.6%). Barriers to cognitive rehabilitation practice included lack of sufficient funds for continuing education, lack of time, lack of standardized assessments, and lack of inter-professional teamwork. Conclusion Many adults in Kuwait live with cognitive impairment. There is a need to develop appropriate evidence-based cognitive rehabilitation clinical guidelines in Kuwait.

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

    Science.gov (United States)

    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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

    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...

  13. The Influence of Affective States Varying in Motivational Intensity on Cognitive Scope

    Directory of Open Access Journals (Sweden)

    Eddie eHarmon-Jones

    2012-09-01

    Full Text Available We review a program of research that has suggested that affective states high in motivationally intensity (e.g., enthusiasm, disgust narrow cognitive scope, whereas affective states low in motivationally intensity (e.g., joy, sadness broaden cognitive scope. Further supporting this interpretation, indices of brain activations, derived from human electroencephalography, suggest that the motivational intensity of the affective state predicts the narrowing of cognitive scope. Finally, research suggests that the relationship between emotive intensity and cognitive scope is bi-directional, such that manipulated changes in cognitive scope influence early brain activations associated with emotive intensity. In the end, the review highlights how emotion can impair and improve certain cognitive processes.

  14. Resting-state abnormalities in amnestic mild cognitive impairment: a meta-analysis.

    Science.gov (United States)

    Lau, W K W; Leung, M-K; Lee, T M C; Law, A C K

    2016-04-26

    Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD). As no effective drug can cure AD, early diagnosis and intervention for aMCI are urgently needed. The standard diagnostic procedure for aMCI primarily relies on subjective neuropsychological examinations that require the judgment of experienced clinicians. The development of other objective and reliable aMCI markers, such as neural markers, is therefore required. Previous neuroimaging findings revealed various abnormalities in resting-state activity in MCI patients, but the findings have been inconsistent. The current study provides an updated activation likelihood estimation meta-analysis of resting-state functional magnetic resonance imaging (fMRI) data on aMCI. The authors searched on the MEDLINE/PubMed databases for whole-brain resting-state fMRI studies on aMCI published until March 2015. We included 21 whole-brain resting-state fMRI studies that reported a total of 156 distinct foci. Significant regional resting-state differences were consistently found in aMCI patients relative to controls, including the posterior cingulate cortex, right angular gyrus, right parahippocampal gyrus, left fusiform gyrus, left supramarginal gyrus and bilateral middle temporal gyri. Our findings support that abnormalities in resting-state activities of these regions may serve as neuroimaging markers for aMCI.

  15. Large-scale resting state network correlates of cognitive impairment in Parkinson’s disease and related dopaminergic deficits

    Directory of Open Access Journals (Sweden)

    Alexander V Lebedev

    2014-04-01

    Full Text Available Cognitive impairment is a common non-motor feature of Parkinson’s disease (PD. The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson’s Progression Marker Initiative (PPMI database. Eighteen patients from this sample were also scanned with 123I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs defined from the AAL brain atlas. The Brain Connectivity Toolbox was used to extract nodal strength from all ROIs and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable scores were correlated with performances in the three cognitive domains and striatal dopamine transporter binding ratios (SBR using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on modularity of the cognitive network was analyzed. Less severe executive impairment was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This pattern was positively influenced by the relative preservation of nigrostriatal dopaminergic function. The pattern associated with better memory performance favored prefronto-limbic processing, and did not reveal associations with presynaptic striatal dopamine uptake. SBR ratios were negatively associated with modularity of the cognitive network, suggesting integrative effects of the preserved nigrostriatal dopamine system on this

  16. 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.

  17. 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.

  18. Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation

    Science.gov (United States)

    Nicolae, Irina-Emilia; Acqualagna, Laura; Blankertz, Benjamin

    2017-01-01

    Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70–90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces. PMID:29046625

  19. Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation

    Directory of Open Access Journals (Sweden)

    Irina-Emilia Nicolae

    2017-10-01

    Full Text Available Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain.Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing within three distinct domains (memory, language, and visual imagination. Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs and in the extend and duration of event-related desynchronization (ERD which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing.Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70–90% for all conditions and classification pairs.Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces.

  20. Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation.

    Science.gov (United States)

    Nicolae, Irina-Emilia; Acqualagna, Laura; Blankertz, Benjamin

    2017-01-01

    Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70-90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces.

  1. The Cognitive Estimation Task Is Nonunitary: Evidence for Multiple Magnitude Representation Mechanisms Among Normative and ADHD College Students

    Directory of Open Access Journals (Sweden)

    Sarit Ashkenazi

    2017-02-01

    Full Text Available There is a current debate on whether the cognitive system has a shared representation for all magnitudes or whether there are unique representations. To investigate this question, we used the Biber cognitive estimation task. In this task, participants were asked to provide estimates for questions such as, “How many sticks of spaghetti are in a package?” The task uses different estimation categories (e.g., time, numerical quantity, distance, and weight to look at real-life magnitude representations. Experiment 1 assessed (N = 95 a Hebrew version of the Biber Cognitive Estimation Task and found that different estimation categories had different relations, for example, weight, time, and distance shared variance, but numerical estimation did not. We suggest that numerical estimation does not require the use of measurement in units, hence, it represents a more “pure” numerical estimation. Experiment 2 found that different factors explain individual abilities in different estimation categories. For example, numerical estimation was predicted by preverbal innate quantity understanding (approximate number sense and working memory, whereas time estimations were supported by IQ. These results demonstrate that cognitive estimation is not a unified construct.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Memory, Cognition and the Endogenous Evoked Potentials of the Brain: the Estimation of the Disturbance of Cognitive Functions and Capacity of Working Memory Without the Psychological Testing.

    Science.gov (United States)

    Gnezditskiy, V V; Korepina, O S; Chatskaya, A V; Klochkova, O I

    2017-01-01

    Cognition, cognitive and memory impairments is widely discussed in the literature, especially in the psycho physiological and the neurologic. In essence, this literature is dedicated to the psycho physiological tests, different scales. However, instrument neurophysiologic methods not so widely are used for these purposes. This review is dedicated to the instrument methods of neurophysiology, in particular to the endogenous evoked potentials method Р 300 (by characteristic latency 300 ms), in the estimation of cognitive functions and memory, to their special features dependent on age and to special features to their changes with the pathology. Method cognitive EP - Р 300 is the response of the brain, recorded under the conditions of the identification of the significant distinguishing stimulus, it facilitates the inspection of cognitive functions and memory in the healthy persons and patients with different manifestation of cognitive impairments. In the review it is shown on the basis of literature and our own data, that working (operative) memory and the capacity of the working memory it can be evaluated with the aid of the indices Р 300 within the normal subject and with the pathology. Testing with the estimation of working memory according to latent period of the peak Р 300 can be carried out and when conducting psychological testing is not possible for any reasons. Together with these cognitive EP are used for evidence pharmacotherapy of many neurotropic drugs.

  7. The effect of embodied emotive states on cognitive categorization.

    Science.gov (United States)

    Price, Tom F; Harmon-Jones, Eddie

    2010-12-01

    Research has uncovered that positive affect broadens cognitive categorization. The motivational dimensional model, however, posits that positive affect is not a unitary construct with only one cognitive consequence. Instead, this model puts forth that there are different positive affects varying in approach motivational intensity. According to this model, only positive affects lower in motivational intensity should broaden cognitive processes, whereas positive affects higher in motivational intensity should narrow cognitive processes. Consistent with these predictions, high approach positive affect has been shown to narrow attention, whereas low approach positive affect has been shown to broaden it (Gable & Harmon-Jones, 2008). High approach positive affect, therefore, might narrow categorization. Two experiments investigated this possibility by having participants respond to cognitive categorization tasks in 3 body postures designed to elicit different levels of approach motivation: reclining backward, which should evoke low approach motivation; sitting upright, which should evoke moderate approach motivation; and leaning forward, which should evoke high approach motivation. Participants smiled while in each posture in order to experience positive affect. Experiment 1 provided initial support for the idea that high approach positive affect narrows categorization and low approach positive affect broadens categorization. Experiment 2 replicated these findings with improved smiling instructions. These results extend previous work by showing that the motivational model's predictions hold for basic attentional processes as well as higher level cognitive processes such as categorization.

  8. 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...

  9. 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...

  10. 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.

  11. 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

  12. Cognition Is Related to Resting-State Small-World Network Topology: An Magnetoencephalographic Study

    NARCIS (Netherlands)

    Douw, L.; Schoonheim, M.M.; Landi, D.; van der Meer, M.L.; Geurts, J.J.G.; Reijneveld, J.C.; Klein, M.; Stam, C.J.

    2011-01-01

    Brain networks and cognition have recently begun to attract attention: studies suggest that more efficiently wired resting-state brain networks are indeed correlated with better cognitive performance. "Small-world" brain networks combine local segregation with global integration, hereby subserving

  13. 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

  14. Dynamic goal states: adjusting cognitive control without conflict monitoring.

    Science.gov (United States)

    Scherbaum, Stefan; Dshemuchadse, Maja; Ruge, Hannes; Goschke, Thomas

    2012-10-15

    A central topic in the cognitive sciences is how cognitive control is adjusted flexibly to changing environmental demands at different time scales to produce goal-oriented behavior. According to an influential account, the context-sensitive recruitment of cognitive control is mediated by a specialized conflict monitoring process that registers current conflict and signals the demand for enhanced control in subsequent trials. This view has been immensely successful not least due to supporting evidence from neuroimaging studies suggesting that the conflict monitoring function is localized within the anterior cingulate cortex (ACC) which, in turn, signals the demand for enhanced control to the prefrontal cortex (PFC). In this article, we propose an alternative model of the adaptive regulation of cognitive control based on multistable goal attractor network dynamics and adjustments of cognitive control within a conflict trial. Without incorporation of an explicit conflict monitoring module, the model mirrors behavior in conflict tasks accounting for effects of response congruency, sequential conflict adaptation, and proportion of incongruent trials. Importantly, the model also mirrors frequency tagged EEG data indicating continuous conflict adaptation and suggests a reinterpretation of the correlation between ACC and the PFC BOLD data reported in previous imaging studies. Together, our simulation data propose an alternative interpretation of both behavioral data as well as imaging data that have previously been interpreted in favor of a specialized conflict monitoring process in the ACC. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Experimental demonstration of a cognitive quality of transmission estimator for optical communication systems

    DEFF Research Database (Denmark)

    Caballero Jambrina, Antonio; Aguado, Juan Carlos; Borkowski, Robert

    2012-01-01

    small and not optimized underlying knowledge base, it achieves between 79% and 98.7% successful classifications based on the error vector magnitude (EVM) parameter, and approximately 100% when the classification is based on the optical signal to noise ratio (OSNR).......The impact of physical layer impairments in optical network design and operation has received significant attention in the last years, thereby requiring estimation techniques to predict the quality of transmission (QoT) of optical connections before being established. In this paper, we report...... on the experimental demonstration of a case-based reasoning (CBR) technique to predict whether optical channels fulfill QoT requirements, thus supporting impairment-aware networking. The validation of the cognitive QoT estimator is performed in a WDM 80 Gb/s PDM-QPSK testbed, and we demonstrate that even with a very...

  16. 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.

  17. Estimating Climate Trends: Application to United States Plant Hardiness Zones

    Directory of Open Access Journals (Sweden)

    Nir Y. Krakauer

    2012-01-01

    Full Text Available The United States Department of Agriculture classifies plant hardiness zones based on mean annual minimum temperatures over some past period (currently 1976–2005. Since temperatures are changing, these values may benefit from updating. I outline a multistep methodology involving imputation of missing station values, geostatistical interpolation, and time series smoothing to update a climate variable’s expected value compared to a climatology period and apply it to estimating annual minimum temperature change over the coterminous United States. I show using hindcast experiments that trend estimation gives more accurate predictions of minimum temperatures 1-2 years in advance compared to the previous 30 years’ mean alone. I find that annual minimum temperature increased roughly 2.5 times faster than mean temperature (~2.0 K versus ~0.8 K since 1970, and is already an average of 1.2  0.5 K (regionally up to ~2 K above the 1976–2005 mean, so that much of the country belongs to warmer hardiness zones compared to the current map. The methods developed may also be applied to estimate changes in other climate variables and geographic regions.

  18. 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.

  19. Interference Tolerant Functional Near Infrared Spectrometer (fNIRS) for Cognitive State Monitoring

    Data.gov (United States)

    National Aeronautics and Space Administration — Measuring hemoglobin concentration changes in the brain with Functional Near Infrared Spectroscopy (fNIRS) is a promising technique for monitoring cognitive state...

  20. Low Loss Tapered Fiber Waveguide Modulator for Crew Cognitive State Monitoring (CSM)

    Data.gov (United States)

    National Aeronautics and Space Administration — Many crew-related errors in aviation and astronautics are caused by hazardous cognitive states including overstress, disengagement, high fatigue and ineffective crew...

  1. Cognitive impairment in the remitted state of unipolar depressive disorder: A systematic review

    DEFF Research Database (Denmark)

    Hasselbalch, Bo Jacob; Knorr, Ulla; Kessing, Lars Vedel

    2010-01-01

    BACKGROUND: It is unclear whether cognitive impairment is prevalent in the remitted state of unipolar disorder. AIM: To evaluate whether cognitive function is impaired in the remitted state in patients with unipolar depression compared with healthy control individuals, and to investigate...... were prevalent including non-stringent definition of remission and non-correction for multiple testing. Only few studies investigated the association between cognition and prior course of illness and the results were divergent. LIMITATIONS: Stringent criteria were used in the assessment of eligibility...... of studies. The studies were first and foremost selected according to the criteria for remission used. CONCLUSION: Cognitive dysfunction seems to be present in individuals suffering from unipolar disorder in the remitted state. We recommend that future studies should focus on disentangling the state...

  2. Assessment of Mild Cognitive Impairment with Mini Mental State ...

    African Journals Online (AJOL)

    Background: Mild cognitive impairment is a recently described neuropsychiatric entity with the possibility of evolving into overt dementia. It has been found to respond to therapeutic intervention, thus halting or significantly retarding the progression to dementia. Resource.poor countries like Nigeria can hardly afford to ...

  3. Use of Addenbrooke’s cognitive examination-revised to evaluate the patients’ state in general medical practice

    Directory of Open Access Journals (Sweden)

    Nikolai Nikolayevich Ivanets

    2012-01-01

    Full Text Available The differential diagnosis of cognitive impairments is of great importance in mental disorders detectable in general medical practice. Objective: to study whether Addenbrooke's Cognitive Examination — Revised (ACE-R may be used in these patients. Patients and methods. The study was conducted in two steps at somatic hospitals and city polyclinics. It enrolled 130patients (36 men and 94 women with anxiety-depression spectrum disorders (ADSD, mild cognitive disorders (MCD and a concurrence of these conditions. The authors used the following psychometric scales: the hospital anxiety and depression scale; the mini-mental state examination; the frontal assessment battery; ACE-R; ten words learning test. The psychometric characteristics of ACE-R and the possibilities of its use were estimated to detect MCD. The differences in the spectrum of cognitive impairments were analyzed in patients with different types of ADSD. Results. ACE-R is shown to be an effective neuropsychological tool for the primary diagnosis, detection, and evaluation of MCD in the general medical network. The results of ACE-R use indicate that the spectrum of cognitive impairments has substantial differences in patients with different types of non-psychotic disorders.

  4. Role of state-dependent learning in the cognitive effects of caffeine in mice

    OpenAIRE

    Sanday, Leandro [UNIFESP; Zanin, Karina Agustini [UNIFESP; Patti, Camilla de Lima [UNIFESP; Fernandes-Santos, Luciano [UNIFESP; Oliveira, Larissa C. [UNIFESP; Longo, Beatriz Monteiro [UNIFESP; Andersen, Monica Levy [UNIFESP; Tufik, Sergio [UNIFESP; Frussa-Filho, Roberto [UNIFESP

    2013-01-01

    Caffeine is the most widely used psychoactive substance in the world and it is generally believed that it promotes beneficial effects on cognitive performance. However, there is also evidence suggesting that caffeine has inhibitory effects on learning and memory. Considering that caffeine may have anxiogenic effects, thus changing the emotional state of the subjects, state-dependent learning may play a role in caffeine-induced cognitive alterations. Mice were administered 20 mg/kg caffeine be...

  5. Optimization-based particle filter for state and parameter estimation

    Institute of Scientific and Technical Information of China (English)

    Li Fu; Qi Fei; Shi Guangming; Zhang Li

    2009-01-01

    In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

  6. Adaptive optimisation-offline cyber attack on remote state estimator

    Science.gov (United States)

    Huang, Xin; Dong, Jiuxiang

    2017-10-01

    Security issues of cyber-physical systems have received increasing attentions in recent years. In this paper, deception attacks on the remote state estimator equipped with the chi-squared failure detector are considered, and it is assumed that the attacker can monitor and modify all the sensor data. A novel adaptive optimisation-offline cyber attack strategy is proposed, where using the current and previous sensor data, the attack can yield the largest estimation error covariance while ensuring to be undetected by the chi-squared monitor. From the attacker's perspective, the attack is better than the existing linear deception attacks to degrade the system performance. Finally, some numerical examples are provided to demonstrate theoretical results.

  7. Using Emotion as Information in Future-Oriented Cognition: Individual Differences in the Context of State Negative Affect

    Science.gov (United States)

    Marroquín, Brett; Boyle, Chloe C.; Nolen-Hoeksema, Susan; Stanton, Annette L.

    2016-01-01

    Predictions about the future are susceptible to mood-congruent influences of emotional state. However, recent work suggests individuals also differ in the degree to which they incorporate emotion into cognition. This study examined the role of such individual differences in the context of state negative emotion. We examined whether trait tendencies to use negative or positive emotion as information affect individuals' predictions of what will happen in the future (likelihood estimation) and how events will feel (affective forecasting), and whether trait influences depend on emotional state. Participants (N=119) reported on tendencies to use emotion as information (“following feelings”), underwent an emotion induction (negative versus neutral), and made likelihood estimates and affective forecasts for future events. Views of the future were predicted by both emotional state and individual differences in following feelings. Whereas following negative feelings affected most future-oriented cognition across emotional states, following positive feelings specifically buffered individuals' views of the future in the negative emotion condition, and specifically for positive future events, a category of future-event prediction especially important in psychological health. Individual differences may confer predisposition toward optimistic or pessimistic expectations of the future in the context of acute negative emotion, with implications for adaptive and maladaptive functioning. PMID:27041783

  8. Inline state of health estimation of lithium-ion batteries using state of charge calculation

    Science.gov (United States)

    Sepasi, Saeed; Ghorbani, Reza; Liaw, Bor Yann

    2015-12-01

    The determination of state-of-health (SOH) and state-of-charge (SOC) is challenging and remains as an active research area in academia and industry due to its importance for Li-ion battery applications. The estimation process poses more challenges after substantial battery aging. This paper presents an inline SOH and SOC estimation method for Li-ion battery packs, specifically for those based on LiFePO4 chemistry. This new hybridized SOC and SOH estimator can be used for battery packs. Inline estimated model parameters were used in a compounded SOC + SOH estimator consisting of the SOC calculation based on coulomb counting method as an expedient approach and an SOH observer using an extended Kalman filter (EKF) technique for calibrating the estimates from the coulomb counting method. The algorithm's low SOC and SOH estimation error, fast response time, and less-demanding computational requirement make it practical for on-board estimations. The simulation and experimental results, along with the test bed structure, are presented to validate the proposed methodology on a single cell and a 3S1P LiFePO4 battery pack.

  9. 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

  10. State Estimation in the Automotive SCR DeNOx Process

    DEFF Research Database (Denmark)

    Zhou, Guofeng; Jørgensen, John Bagterp; Duwig, Christophe

    2012-01-01

    on exhaust gas emissions. For advanced control, e.g. Model Predictive Control (MPC), of the SCR process, accurate state estimates are needed. We investigate the performance of the ordinary and the extended Kalman filters based on a simple first principle system model. The performance is tested through......Selective catalytic reduction (SCR) of nitrogen oxides (NOx) is a widely applied diesel engine exhaust gas after-treatment technology. For effective NOx removal in a transient operating automotive application, controlled dosing of urea can be used to meet the increasingly restrictive legislations...

  11. Estimating the inbreeding depression on cognitive behavior: a population based study of child cohort.

    Directory of Open Access Journals (Sweden)

    Mohd Fareed

    Full Text Available Cognitive ability tests are widely assumed to measure maximal intellectual performance and predictive associations between intelligence quotient (IQ scores and later mental health problems. Very few epidemiologic studies have been done to demonstrate the relationship between familial inbreeding and modest cognitive impairments in children.We aimed to estimate the effect of inbreeding on children's cognitive behavior in comparison with non-inbred children.A cohort of 408 children (6 to 15 years of age was selected from inbred and non-inbred families of five Muslim populations of Jammu region. The Wechsler Intelligence Scales for Children (WISC was used to measure the verbal IQ (VIQ, performance IQ (PIQ and full scale IQ (FSIQ. Family pedigrees were drawn to access the family history and children's inbred status in terms of coefficient of inbreeding (F.We found significant decline in child cognitive abilities due to inbreeding and high frequency of mental retardation among offspring from inbred families. The mean differences (95% C.I. were reported for the VIQ, being -22.00 (-24.82, -19.17, PIQ -26.92 (-29.96, -23.87 and FSIQ -24.47 (-27.35,-21.59 for inbred as compared to non-inbred children (p<0.001 [corrected].The higher risk of being mentally retarded was found to be more obvious among inbred categories corresponding to the degree of inbreeding and the same accounts least for non-inbred children (p<0.0001. We observed an increase in the difference in mean values for VIQ, PIQ and FSIQ with the increase of inbreeding coefficient and these were found to be statistically significant (p<0.05. The regression analysis showed a fitness decline (depression for VIQ (R2 = 0.436, PIQ (R2 = 0.468 and FSIQ (R2 = 0.464 with increasing inbreeding coefficients (p<0.01.Our comprehensive assessment provides the evidence for inbreeding depression on cognitive abilities among children.

  12. State Estimation for Sensor Monitoring System with Uncertainty and Disturbance

    Directory of Open Access Journals (Sweden)

    Jianhong Sun

    2014-10-01

    Full Text Available This paper considers the state estimation problem for the sensor monitoring system which contains system uncertainty and nonlinear disturbance. In the sensor monitoring system, states of each inner sensor node usually contains system uncertainty, and external noise often works as nonlinear item. Besides, information transmission in the system is also time consuming. All mentioned above may arouse in unstable of the monitoring system. In this case, states of sensors could be wrongly sampled. Under this circumstance, a proper mathematical model is proposed and by the use of Lipschitz condition, the nonlinear item is transformed to linear one. In addition, we suppose that all sensor nodes are distributed arranged, no interface occurs with each other. By establishing proper Lyapunov– Krasovskii functional, sufficient conditions are acquired by solving linear matrix inequality to make the error augmented system stable, and the gains of observers are also derived. Finally, an illustrated example is given to show that system observed value tracks system states well, which fully demonstrate the effectiveness of our result.

  13. Estimated use of water in the United States in 1970

    Science.gov (United States)

    Murray, Charles Richard; Reeves, E. Bodette

    1972-01-01

    Estimates of water use in the United States in 1970 indicate that an average of about 370 bgd (billion gallons per day)about 1,800 gallons per capita per day--was withdrawn for the four principal off-channel uses which are (1) public-supply (for domestic, commercial, and industrial uses), (2) rural (domestic and livestock), (3) irrigation, and (4) self-supplied industrial (including thermoelectric power). In 1970, withdrawals for these uses exceeded by 19 percent the 310 bgd estimated for 1965. Increases in the various categories of off-channel water use since 1965 were: approximately 25 percent for self-supplied industry (mainly in electric-utility thermoelectric plants), 13 percent for public supplies, 13 percent for rural supplies, and 8 percent for irrigation. Industrial water withdrawals included 54 bgd of saline water, a 20 percent increase in 5 years. The fifth principal withdrawal use, hydroelectric power (an in-channel use), amounted to 2,800 bgd, a 5-year increase of 22 percent. In computing total withdrawals, recycling within a plant (reuse) is not counted, but withdrawal of the same water by a downstream user (cumulative withdrawals) is counted. The quantity of fresh water consumed--that is, water made unavailable for further possible withdrawal because of evaporation, incorporation in crops and manufactured products, and other causes--was estimated to average 87 bgd for 1970, an increase of about 12 percent since 1965.

  14. Improving Distribution Resiliency with Microgrids and State and Parameter Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Tuffner, Francis K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Schneider, Kevin P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sun, Yannan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Chen-Ching [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Xu, Yin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gourisetti, Sri Nikhil Gup [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-09-30

    Modern society relies on low-cost reliable electrical power, both to maintain industry, as well as provide basic social services to the populace. When major disturbances occur, such as Hurricane Katrina or Hurricane Sandy, the nation’s electrical infrastructure can experience significant outages. To help prevent the spread of these outages, as well as facilitating faster restoration after an outage, various aspects of improving the resiliency of the power system are needed. Two such approaches are breaking the system into smaller microgrid sections, and to have improved insight into the operations to detect failures or mis-operations before they become critical. Breaking the system into smaller sections of microgrid islands, power can be maintained in smaller areas where distribution generation and energy storage resources are still available, but bulk power generation is no longer connected. Additionally, microgrid systems can maintain service to local pockets of customers when there has been extensive damage to the local distribution system. However, microgrids are grid connected a majority of the time and implementing and operating a microgrid is much different than when islanded. This report discusses work conducted by the Pacific Northwest National Laboratory that developed improvements for simulation tools to capture the characteristics of microgrids and how they can be used to develop new operational strategies. These operational strategies reduce the cost of microgrid operation and increase the reliability and resilience of the nation’s electricity infrastructure. In addition to the ability to break the system into microgrids, improved observability into the state of the distribution grid can make the power system more resilient. State estimation on the transmission system already provides great insight into grid operations and detecting abnormal conditions by leveraging existing measurements. These transmission-level approaches are expanded to using

  15. Mental workload and cognitive task automaticity: an evaluation of subjective and time estimation metrics.

    Science.gov (United States)

    Liu, Y; Wickens, C D

    1994-11-01

    The evaluation of mental workload is becoming increasingly important in system design and analysis. The present study examined the structure and assessment of mental workload in performing decision and monitoring tasks by focusing on two mental workload measurements: subjective assessment and time estimation. The task required the assignment of a series of incoming customers to the shortest of three parallel service lines displayed on a computer monitor. The subject was either in charge of the customer assignment (manual mode) or was monitoring an automated system performing the same task (automatic mode). In both cases, the subjects were required to detect the non-optimal assignments that they or the computer had made. Time pressure was manipulated by the experimenter to create fast and slow conditions. The results revealed a multi-dimensional structure of mental workload and a multi-step process of subjective workload assessment. The results also indicated that subjective workload was more influenced by the subject's participatory mode than by the factor of task speed. The time estimation intervals produced while performing the decision and monitoring tasks had significantly greater length and larger variability than those produced while either performing no other tasks or performing a well practised customer assignment task. This result seemed to indicate that time estimation was sensitive to the presence of perceptual/cognitive demands, but not to response related activities to which behavioural automaticity has developed.

  16. 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

  17. Remaining lifetime modeling using State-of-Health estimation

    Science.gov (United States)

    Beganovic, Nejra; Söffker, Dirk

    2017-08-01

    Technical systems and system's components undergo gradual degradation over time. Continuous degradation occurred in system is reflected in decreased system's reliability and unavoidably lead to a system failure. Therefore, continuous evaluation of State-of-Health (SoH) is inevitable to provide at least predefined lifetime of the system defined by manufacturer, or even better, to extend the lifetime given by manufacturer. However, precondition for lifetime extension is accurate estimation of SoH as well as the estimation and prediction of Remaining Useful Lifetime (RUL). For this purpose, lifetime models describing the relation between system/component degradation and consumed lifetime have to be established. In this contribution modeling and selection of suitable lifetime models from database based on current SoH conditions are discussed. Main contribution of this paper is the development of new modeling strategies capable to describe complex relations between measurable system variables, related system degradation, and RUL. Two approaches with accompanying advantages and disadvantages are introduced and compared. Both approaches are capable to model stochastic aging processes of a system by simultaneous adaption of RUL models to current SoH. The first approach requires a priori knowledge about aging processes in the system and accurate estimation of SoH. An estimation of SoH here is conditioned by tracking actual accumulated damage into the system, so that particular model parameters are defined according to a priori known assumptions about system's aging. Prediction accuracy in this case is highly dependent on accurate estimation of SoH but includes high number of degrees of freedom. The second approach in this contribution does not require a priori knowledge about system's aging as particular model parameters are defined in accordance to multi-objective optimization procedure. Prediction accuracy of this model does not highly depend on estimated SoH. This model

  18. Estimated Use of Water in the United States in 1985

    Science.gov (United States)

    Solley, Wayne B.; Merk, Charles F.; Pierce, Robert R.

    1988-01-01

    Water withdrawals in the United States during 1985 were estimated to average 399,000 million gallons per day (Mgal/d) of freshwater and saline water for offstream uses--10 percent less than the 1980 estimate. Average per-capita use for all offstream uses was 1,650 gallons per day (gal/d) of freshwater and saline water combined and 1,400 gal/d of freshwater alone. Offstream water-use categories are classified in this report as public supply, domestic, commercial, irrigation, livestock, industrial, mining, and thermoelectric power. During 1985, public-supply withdrawals were estimated to be 36,500 Mgal/d, and self-supplied withdrawals were estimated as follows: domestic, 3,320 Mgal/d: commercial, 1,230 Mgal/d; irrigation, 137,000 Mgal/d: livestock, 4,470 Mgal/d; industrial, 25,800 Mgal/d; mining, 3,440 Mgal/d; and thermoelectric power, 187,000 Mgal/d. Water use for hydroelectric power generation, the only instream use compiled in this report, was estimated to be 3,050,000 Mgal/d during 1985, or 7 percent less than during 1980. This is in contrast to an increasing trend that persisted from 1950 to 1980. Estimates of withdrawals by source indicate that, during 1985, total surface-water withdrawals were 325,000 Mgal/d, or 10 percent less than during 1980, and total ground-water withdrawals were 74,000 Mgal/d, or 12 percent less than during 1980. Total saline-water withdrawals during 1985 were 60,300 Mgal/d, or 16 percent less than during 1980; most was saline surface water. Reclaimed sewage averaged about 579 Mgal/d during 1985, or 22 percent more than during 1980. Total freshwater consumptive use was estimated to be 92,300 Mgal/d during 1985, or 9 percent less than during 1980. Consumptive use by irrigation accounted for the largest part of consumptive use during 1985 and was estimated to be 73,800 Mgal/d. A comparison of total withdrawals (fresh and saline) by State indicates that 37 States and Puerto Rico had less water withdrawn for offstream uses during 1985 than

  19. Parameter and state estimation in nonlinear dynamical systems

    Science.gov (United States)

    Creveling, Daniel R.

    This thesis is concerned with the problem of state and parameter estimation in nonlinear systems. The need to evaluate unknown parameters in models of nonlinear physical, biophysical and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. When verifying and validating these models, it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, this thesis develops a framework for presenting data to a candidate model of a physical process in a way that makes efficient use of the measured data while allowing for estimation of the unknown parameters in the model. The approach presented here builds on existing work that uses synchronization as a tool for parameter estimation. Some critical issues of stability in that work are addressed and a practical framework is developed for overcoming these difficulties. The central issue is the choice of coupling strength between the model and data. If the coupling is too strong, the model will reproduce the measured data regardless of the adequacy of the model or correctness of the parameters. If the coupling is too weak, nonlinearities in the dynamics could lead to complex dynamics rendering any cost function comparing the model to the data inadequate for the determination of model parameters. Two methods are introduced which seek to balance the need for coupling with the desire to allow the model to evolve in its natural manner without coupling. One method, 'balanced' synchronization, adds to the synchronization cost function a requirement that the conditional Lyapunov exponents of the model system, conditioned on being driven by the data, remain negative but small in magnitude. Another method allows the coupling between the data and the model to vary in time according to a specific form of differential equation. The coupling dynamics is damped to allow for a tendency toward zero coupling

  20. 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.

  1. Chapter 16 - Predictive Analytics for Comprehensive Energy Systems State Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yang, Rui [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Jie [University of Texas at Dallas; Weng, Yang [Arizona State University

    2017-12-01

    Energy sustainability is a subject of concern to many nations in the modern world. It is critical for electric power systems to diversify energy supply to include systems with different physical characteristics, such as wind energy, solar energy, electrochemical energy storage, thermal storage, bio-energy systems, geothermal, and ocean energy. Each system has its own range of control variables and targets. To be able to operate such a complex energy system, big-data analytics become critical to achieve the goal of predicting energy supplies and consumption patterns, assessing system operation conditions, and estimating system states - all providing situational awareness to power system operators. This chapter presents data analytics and machine learning-based approaches to enable predictive situational awareness of the power systems.

  2. An efficient algebraic approach to observability analysis in state estimation

    Energy Technology Data Exchange (ETDEWEB)

    Pruneda, R.E.; Solares, C.; Conejo, A.J. [University of Castilla-La Mancha, 13071 Ciudad Real (Spain); Castillo, E. [University of Cantabria, 39005 Santander (Spain)

    2010-03-15

    An efficient and compact algebraic approach to state estimation observability is proposed. It is based on transferring rows to columns and vice versa in the Jacobian measurement matrix. The proposed methodology provides a unified approach to observability checking, critical measurement identification, determination of observable islands, and selection of pseudo-measurements to restore observability. Additionally, the observability information obtained from a given set of measurements can provide directly the observability obtained from any subset of measurements of the given set. Several examples are used to illustrate the capabilities of the proposed methodology, and results from a large case study are presented to demonstrate the appropriate computational behavior of the proposed algorithms. Finally, some conclusions are drawn. (author)

  3. The functional implications of motor, cognitive, psychiatric, and social problem-solving states in Huntington's disease.

    Science.gov (United States)

    Van Liew, Charles; Gluhm, Shea; Goldstein, Jody; Cronan, Terry A; Corey-Bloom, Jody

    2013-01-01

    Huntington's disease (HD) is a genetic, neurodegenerative disorder characterized by motor, cognitive, and psychiatric dysfunction. In HD, the inability to solve problems successfully affects not only disease coping, but also interpersonal relationships, judgment, and independent living. The aim of the present study was to examine social problem-solving (SPS) in well-characterized HD and at-risk (AR) individuals and to examine its unique and conjoint effects with motor, cognitive, and psychiatric states on functional ratings. Sixty-three participants, 31 HD and 32 gene-positive AR, were included in the study. Participants completed the Social Problem-Solving Inventory-Revised: Long (SPSI-R:L), a 52-item, reliable, standardized measure of SPS. Items are aggregated under five scales (Positive, Negative, and Rational Problem-Solving; Impulsivity/Carelessness and Avoidance Styles). Participants also completed the Unified Huntington's Disease Rating Scale functional, behavioral, and cognitive assessments, as well as additional neuropsychological examinations and the Symptom Checklist-90-Revised (SCL-90R). A structural equation model was used to examine the effects of motor, cognitive, psychiatric, and SPS states on functionality. The multifactor structural model fit well descriptively. Cognitive and motor states uniquely and significantly predicted function in HD; however, neither psychiatric nor SPS states did. SPS was, however, significantly related to motor, cognitive, and psychiatric states, suggesting that it may bridge the correlative gap between psychiatric and cognitive states in HD. SPS may be worth assessing in conjunction with the standard gamut of clinical assessments in HD. Suggestions for future research and implications for patients, families, caregivers, and clinicians are discussed.

  4. INTERVAL STATE ESTIMATION FOR SINGULAR DIFFERENTIAL EQUATION SYSTEMS WITH DELAYS

    Directory of Open Access Journals (Sweden)

    T. A. Kharkovskaia

    2016-07-01

    Full Text Available The paper deals with linear differential equation systems with algebraic restrictions (singular systems and a method of interval observer design for this kind of systems. The systems contain constant time delay, measurement noise and disturbances. Interval observer synthesis is based on monotone and cooperative systems technique, linear matrix inequations, Lyapunov function theory and interval arithmetic. The set of conditions that gives the possibility for interval observer synthesis is proposed. Results of synthesized observer operation are shown on the example of dynamical interindustry balance model. The advantages of proposed method are that it is adapted to observer design for uncertain systems, if the intervals of admissible values for uncertain parameters are given. The designed observer is capable to provide asymptotically definite limits on the estimation accuracy, since the interval of admissible values for the object state is defined at every instant. The obtained result provides an opportunity to develop the interval estimation theory for complex systems that contain parametric uncertainty, varying delay and nonlinear elements. Interval observers increasingly find applications in economics, electrical engineering, mechanical systems with constraints and optimal flow control.

  5. Quantitative EEG and its Correlation with Cardiovascular, Cognition and mood State: an Integrated Study in Simulated Microgravity

    Science.gov (United States)

    Zhang, Jianyuan; Hu, Bin; Chen, Wenjuan; Moore, Philip; Xu, Tingting; Dong, Qunxi; Liu, Zhenyu; Luo, Yuejia; Chen, Shanguang

    2014-12-01

    The focus of the study is the estimation of the effects of microgravity on the central nervous activity and its underlying influencing mechanisms. To validate the microgravity-induced physiological and psychological effects on EEG, quantitative EEG features, cardiovascular indicators, mood state, and cognitive performances data collection was achieved during a 45 day period using a -6°head-down bed rest (HDBR) integrated approach. The results demonstrated significant differences in EEG data, as an increased Theta wave, a decreased Beta wave and a reduced complexity of brain, accompanied with an increased heart rate and pulse rate, decreased positive emotion, and degraded emotion conflict monitoring performance. The canonical correlation analysis (CCA) based cardiovascular and cognitive related EEG model showed the cardiovascular effect on EEG mainly affected bilateral temporal region and the cognitive effect impacted parietal-occipital and frontal regions. The results obtained in the study support the use of an approach which combines a multi-factor influential mechanism hypothesis. The changes in the EEG data may be influenced by both cardiovascular and cognitive effects.

  6. Using support vector machines in the multivariate state estimation technique

    International Nuclear Information System (INIS)

    Zavaljevski, N.; Gross, K.C.

    1999-01-01

    One approach to validate nuclear power plant (NPP) signals makes use of pattern recognition techniques. This approach often assumes that there is a set of signal prototypes that are continuously compared with the actual sensor signals. These signal prototypes are often computed based on empirical models with little or no knowledge about physical processes. A common problem of all data-based models is their limited ability to make predictions on the basis of available training data. Another problem is related to suboptimal training algorithms. Both of these potential shortcomings with conventional approaches to signal validation and sensor operability validation are successfully resolved by adopting a recently proposed learning paradigm called the support vector machine (SVM). The work presented here is a novel application of SVM for data-based modeling of system state variables in an NPP, integrated with a nonlinear, nonparametric technique called the multivariate state estimation technique (MSET), an algorithm developed at Argonne National Laboratory for a wide range of nuclear plant applications

  7. HIV Trends in the United States: Diagnoses and Estimated Incidence.

    Science.gov (United States)

    Hall, H Irene; Song, Ruiguang; Tang, Tian; An, Qian; Prejean, Joseph; Dietz, Patricia; Hernandez, Angela L; Green, Timothy; Harris, Norma; McCray, Eugene; Mermin, Jonathan

    2017-02-03

    The best indicator of the impact of human immunodeficiency virus (HIV) prevention programs is the incidence of infection; however, HIV is a chronic infection and HIV diagnoses may include infections that occurred years before diagnosis. Alternative methods to estimate incidence use diagnoses, stage of disease, and laboratory assays of infection recency. Using a consistent, accurate method would allow for timely interpretation of HIV trends. The objective of our study was to assess the recent progress toward reducing HIV infections in the United States overall and among selected population segments with available incidence estimation methods. Data on cases of HIV infection reported to national surveillance for 2008-2013 were used to compare trends in HIV diagnoses, unadjusted and adjusted for reporting delay, and model-based incidence for the US population aged ≥13 years. Incidence was estimated using a biomarker for recency of infection (stratified extrapolation approach) and 2 back-calculation models (CD4 and Bayesian hierarchical models). HIV testing trends were determined from behavioral surveys for persons aged ≥18 years. Analyses were stratified by sex, race or ethnicity (black, Hispanic or Latino, and white), and transmission category (men who have sex with men, MSM). On average, HIV diagnoses decreased 4.0% per year from 48,309 in 2008 to 39,270 in 2013 (Pyear (Pyears, overall, the percentage of persons who ever had received an HIV test or had had a test within the past year remained stable; among MSM testing increased. For women, all 3 incidence models corroborated the decreasing trend in HIV diagnoses, and HIV diagnoses and 2 incidence models indicated decreases among blacks and whites. The CD4 and Bayesian hierarchical models, but not the stratified extrapolation approach, indicated decreases in incidence among MSM. HIV diagnoses and CD4 and Bayesian hierarchical model estimates indicated decreases in HIV incidence overall, among both sexes and all

  8. Call Arrival Rate Prediction and Blocking Probability Estimation for Infrastructure based Mobile Cognitive Radio Personal Area Network

    Directory of Open Access Journals (Sweden)

    Neeta Nathani

    2017-08-01

    Full Text Available The Cognitive Radio usage has been estimated as non-emergency service with low volume traffic. Present work proposes an infrastructure based Cognitive Radio network and probability of success of CR traffic in licensed band. The Cognitive Radio nodes will form cluster. The cluster nodes will communicate on Industrial, Scientific and Medical band using IPv6 over Low-Power Wireless Personal Area Network based protocol from sensor to Gateway Cluster Head. For Cognitive Radio-Media Access Control protocol for Gateway to Cognitive Radio-Base Station communication, it will use vacant channels of licensed band. Standalone secondary users of Cognitive Radio Network shall be considered as a Gateway with one user. The Gateway will handle multi-channel multi radio for communication with Base Station. Cognitive Radio Network operators shall define various traffic data accumulation counters at Base Station for storing signal strength, Carrier-to-Interference and Noise Ratio, etc. parameters and record channel occupied/vacant status. The researches has been done so far using hour as interval is too long for parameters like holding time expressed in minutes and hence channel vacant/occupied status time is only probabilistically calculated. In the present work, an infrastructure based architecture has been proposed which polls channel status each minute in contrary to hourly polling of data. The Gateways of the Cognitive Radio Network shall monitor status of each Primary User periodically inside its working range and shall inform to Cognitive Radio- Base Station for preparation of minutewise database. For simulation, the occupancy data for all primary user channels were pulled in one minute interval from a live mobile network. Hourly traffic data and minutewise holding times has been analyzed to optimize the parameters of Seasonal Auto Regressive Integrated Moving Average prediction model. The blocking probability of an incoming Cognitive Radio call has been

  9. Pipeline heating method based on optimal control and state estimation

    Energy Technology Data Exchange (ETDEWEB)

    Vianna, F.L.V. [Dept. of Subsea Technology. Petrobras Research and Development Center - CENPES, Rio de Janeiro, RJ (Brazil)], e-mail: fvianna@petrobras.com.br; Orlande, H.R.B. [Dept. of Mechanical Engineering. POLI/COPPE, Federal University of Rio de Janeiro - UFRJ, Rio de Janeiro, RJ (Brazil)], e-mail: helcio@mecanica.ufrj.br; Dulikravich, G.S. [Dept. of Mechanical and Materials Engineering. Florida International University - FIU, Miami, FL (United States)], e-mail: dulikrav@fiu.edu

    2010-07-01

    In production of oil and gas wells in deep waters the flowing of hydrocarbon through pipeline is a challenging problem. This environment presents high hydrostatic pressures and low sea bed temperatures, which can favor the formation of solid deposits that in critical operating conditions, as unplanned shutdown conditions, may result in a pipeline blockage and consequently incur in large financial losses. There are different methods to protect the system, but nowadays thermal insulation and chemical injection are the standard solutions normally used. An alternative method of flow assurance is to heat the pipeline. This concept, which is known as active heating system, aims at heating the produced fluid temperature above a safe reference level in order to avoid the formation of solid deposits. The objective of this paper is to introduce a Bayesian statistical approach for the state estimation problem, in which the state variables are considered as the transient temperatures within a pipeline cross-section, and to use the optimal control theory as a design tool for a typical heating system during a simulated shutdown condition. An application example is presented to illustrate how Bayesian filters can be used to reconstruct the temperature field from temperature measurements supposedly available on the external surface of the pipeline. The temperatures predicted with the Bayesian filter are then utilized in a control approach for a heating system used to maintain the temperature within the pipeline above the critical temperature of formation of solid deposits. The physical problem consists of a pipeline cross section represented by a circular domain with four points over the pipe wall representing heating cables. The fluid is considered stagnant, homogeneous, isotropic and with constant thermo-physical properties. The mathematical formulation governing the direct problem was solved with the finite volume method and for the solution of the state estimation problem

  10. Estimation of Distribution Algorithm for Resource Allocation in Green Cooperative Cognitive Radio Sensor Networks

    Directory of Open Access Journals (Sweden)

    Alagan Anpalagan

    2013-04-01

    Full Text Available Due to the rapid increase in the usage and demand of wireless sensor networks (WSN, the limited frequency spectrum available for WSN applications will be extremely crowded in the near future. More sensor devices also mean more recharging/replacement of batteries, which will cause significant impact on the global carbon footprint. In this paper, we propose a relay-assisted cognitive radio sensor network (CRSN that allocates communication resources in an environmentally friendly manner. We use shared band amplify and forward relaying for cooperative communication in the proposed CRSN. We present a multi-objective optimization architecture for resource allocation in a green cooperative cognitive radio sensor network (GC-CRSN. The proposed multi-objective framework jointly performs relay assignment and power allocation in GC-CRSN, while optimizing two conflicting objectives. The first objective is to maximize the total throughput, and the second objective is to minimize the total transmission power of CRSN. The proposed relay assignment and power allocation problem is a non-convex mixed-integer non-linear optimization problem (NC-MINLP, which is generally non-deterministic polynomial-time (NP-hard. We introduce a hybrid heuristic algorithm for this problem. The hybrid heuristic includes an estimation-of-distribution algorithm (EDA for performing power allocation and iterative greedy schemes for constraint satisfaction and relay assignment. We analyze the throughput and power consumption tradeoff in GC-CRSN. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results.

  11. Resting-State Functional Connectivity and Cognitive Impairment in Children with Perinatal Stroke

    Directory of Open Access Journals (Sweden)

    Nigul Ilves

    2016-01-01

    Full Text Available Perinatal stroke is a leading cause of congenital hemiparesis and neurocognitive deficits in children. Dysfunctions in the large-scale resting-state functional networks may underlie cognitive and behavioral disability in these children. We studied resting-state functional connectivity in patients with perinatal stroke collected from the Estonian Pediatric Stroke Database. Neurodevelopment of children was assessed by the Pediatric Stroke Outcome Measurement and the Kaufman Assessment Battery. The study included 36 children (age range 7.6–17.9 years: 10 with periventricular venous infarction (PVI, 7 with arterial ischemic stroke (AIS, and 19 controls. There were no differences in severity of hemiparesis between the PVI and AIS groups. A significant increase in default mode network connectivity (FDR 0.1 and lower cognitive functions (p<0.05 were found in children with AIS compared to the controls and the PVI group. The children with PVI had no significant differences in the resting-state networks compared to the controls and their cognitive functions were normal. Our findings demonstrate impairment in cognitive functions and neural network profile in hemiparetic children with AIS compared to children with PVI and controls. Changes in the resting-state networks found in children with AIS could possibly serve as the underlying derangements of cognitive brain functions in these children.

  12. fMRI resting state networks and their association with cognitive fluctuations in dementia with Lewy bodies

    Directory of Open Access Journals (Sweden)

    Luis R. Peraza

    2014-01-01

    Full Text Available Cognitive fluctuations are a core symptom in dementia with Lewy bodies (DLB and may relate to pathological alterations in distributed brain networks. To test this we analysed resting state fMRI changes in a cohort of fluctuating DLB patients (n = 16 compared with age matched controls (n = 17 with the aim of finding functional connectivity (FC differences between these two groups and whether these associate with cognitive fluctuations in DLB. Resting state networks (RSNs were estimated using independent component analysis and FC between the RSN maps and the entirety of the brain was assessed using dual regression. The default mode network (DMN appeared unaffected in DLB compared to controls but significant cluster differences between DLB and controls were found for the left fronto-parietal, temporal, and sensory–motor networks. Desynchronization of a number of cortical and subcortical areas related to the left fronto-parietal network was associated with the severity and frequency of cognitive fluctuations. Our findings provide empirical evidence for the potential role of attention–executive networks in the aetiology of this core symptom in DLB.

  13. Estimated use of water in the United States, 1960

    Science.gov (United States)

    MacKichan, K.A.; Kammerer, J.C.

    1961-01-01

    The estimated overage withdrawal use of water in the United States during 1960 was almost 270,000 mgd (million gallons per day), exclusive of water used to develop water power. This estimated use amounts to about 1,500 gpd (galIons per day) per capita. An additional 2,000,000 mgd were used to develop waterpower.Withdrawal use of water requires that the water be removed from the ground or diverted from a stream or lake. In this report the use is divided into five types: public supplies, rural, irrigation, self-supplied industrial, and waterpower. Consumptive use of water is the quantity discharged to the atmosphere or incorporated in the products of the process in which it was used. Only 61,000 mgd of the 270,000 mgd withdrawn was consumed.Of the water withdrawn in 1960, 220,000 mgd (including irrigation conveyance losses) was taken from surface sources and 47,000 from underground sources. Withdrawal of water for uses other than waterpower has increased 12 percent since 1955. The amount of water used for generation of waterpower has! increased 33 percent since 1955. The use of saline water was almost twice as great in 1960 as in 1955.The upper limit of our water supply is the average annual runoff, nearly 1,200,000 mgd. The supply in 1960 was depleted by 61,000 mgd, the amount of water consumed. However, a large part of the water withdrawn but not consumed was deteriorated in quality.

  14. [Effects of cognitive state on balance disturbances and gait disorders in institutionalised elderly].

    Science.gov (United States)

    Díaz-Pelegrina, Ana; Cabrera-Martos, Irene; López-Torres, Isabel; Rodríguez-Torres, Janet; Valenza, Marie Carmen

    2016-01-01

    Ageing has been linked to a high prevalence of cognitive impairment, which, in turn, has been related to balance disturbances and gait disorders. The aim of this study was to identify whether there are differences between subjects with and without cognitive impairment regarding the quality of gait and balance. An observational study was conducted on institutionalised people older than 65 years (n=82). Gait and balance was evaluated after the assessment of cognitive impairment using the Mini-Mental State Examination (MMSE). Single and dual tests were used including, the 6-minute walking, stride length, and gait speed. Timed Up and Go tests were also used to evaluate balance. The participants were divided into three groups: 28 subjects in the group without cognitive impairment (MMSE≥27), 29 subjects with mild (27cognitive impairment (MMSE<21). Gait assessment showed significant between-groups differences in all the variables (P<.05). The variables assessing balance also showed significantly worse values in those groups with cognitive impairment. The severity of cognitive impairment is related to impaired balance and gait, thus the clinical monitoring of these variables in population at risk is needed. Copyright © 2015 SEGG. Published by Elsevier Espana. All rights reserved.

  15. Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method.

    Science.gov (United States)

    Van Calster, Laurens; D'Argembeau, Arnaud; Salmon, Eric; Peters, Frédéric; Majerus, Steve

    2017-01-01

    Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top-down versus bottom-up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.

  16. Estimation of the Level of Cognitive Development of a Preschool Child Using the System of Situations with Mathematical Contents

    Science.gov (United States)

    Gorev, Pavel M.; Bichurina, Svetlana Y.; Yakupova, Rufiya M.; Khairova, Irina V.

    2016-01-01

    Cognitive development of personality can be considered as one of the key directions of preschool education presented in the world practice, where preschool programs are educational ones, and preschool education is the first level of the general education. Thereby the purpose of the research is to create a model of reliable estimation of cognitive…

  17. Steady State Visual Evoked Potential Based Brain-Computer Interface for Cognitive Assessment

    DEFF Research Database (Denmark)

    Westergren, Nicolai; Bendtsen, Rasmus L.; Kjær, Troels W.

    2016-01-01

    decline is important. Cognitive decline may be detected using fullyautomated computerized assessment. Such systems will provide inexpensive and widely available screenings of cognitive ability. The aim of this pilot study is to develop a real time steady state visual evoked potential (SSVEP) based brain-computer...... interface (BCI) for neurological cognitive assessment. It is intended for use by patients who suffer from diseases impairing their motor skills, but are still able to control their gaze. Results are based on 11 healthy test subjects. The system performance have an average accuracy of 100% ± 0%. The test...... subjects achieved an information transfer rate (ITR) of 14:64 bits/min ± 7:63 bits=min and a subject test performance of 47:22% ± 34:10%. This study suggests that BCI may be applicable in practice as a computerized cognitive assessment tool. However, many improvements are required for the system...

  18. Conversion between Addenbrooke's Cognitive Examination III and Mini-Mental State Examination.

    Science.gov (United States)

    Matías-Guiu, Jordi A; Pytel, Vanesa; Cortés-Martínez, Ana; Valles-Salgado, María; Rognoni, Teresa; Moreno-Ramos, Teresa; Matías-Guiu, Jorge

    2017-12-10

    We aim to provide a conversion between Addenbrooke's Cognitive Examination III (ACE-III) and Mini-Mental State Examination (MMSE) scores, to predict the MMSE result based on ACE-III, thus avoiding the need for both tests, and improving their comparability. Equipercentile equating method was used to elaborate a conversion table using a group of 400 participants comprising healthy controls and Alzheimer's disease (AD) patients. Then, reliability was assessed in a group of 100 healthy controls and patients with AD, 52 with primary progressive aphasia and 22 with behavioral variant frontotemporal dementia. The conversion table between ACE-III and MMSE denoted a high reliability, with intra-class correlation coefficients of 0.940, 0.922, and 0.902 in the groups of healthy controls and AD, behavioral variant frontotemporal dementia, and primary progressive aphasia, respectively. Our conversion table between ACE-III and MMSE suggests that MMSE may be estimated based on the ACE-III score, which could be useful for clinical and research purposes.

  19. Guidelines for Cognitive Behavioral Training within Doctoral Psychology Programs in the United States: Report of the Inter-Organizational Task Force on Cognitive and Behavioral Psychology Doctoral Education

    Science.gov (United States)

    Klepac, Robert K.; Ronan, George F.; Andrasik, Frank; Arnold, Kevin D.; Belar, Cynthia D.; Berry, Sharon L.; Christofff, Karen A.; Craighead, Linda W.; Dougher, Michael J.; Dowd, E. Thomas; Herbert, James D.; McFarr, Lynn M.; Rizvi, Shireen L.; Sauer, Eric M.; Strauman, Timothy J.

    2012-01-01

    The Association for Behavioral and Cognitive Therapies initiated an interorganizational task force to develop guidelines for integrated education and training in cognitive and behavioral psychology at the doctoral level in the United States. Fifteen task force members representing 16 professional associations participated in a yearlong series of…

  20. Remote optimal state estimation over communication channels with random delays

    KAUST Repository

    Mahmoud, Magdi S.; Al-Sunni, Fouad; Liu, Bo

    2014-01-01

    This paper considers the optimal estimation of linear systems over unreliable communication channels with random delays. In this work, it is assumed that the system to be estimated is far away from the filter. The observations of the system

  1. Evaluation of cognitive load and emotional states during multidisciplinary critical care simulation sessions.

    Science.gov (United States)

    Pawar, Swapnil; Jacques, Theresa; Deshpande, Kush; Pusapati, Raju; Meguerdichian, Michael J

    2018-04-01

    The simulation in critical care setting involves a heterogeneous group of participants with varied background and experience. Measuring the impacts of simulation on emotional state and cognitive load in this setting is not often performed. The feasibility of such measurement in the critical care setting needs further exploration. Medical and nursing staff with varying levels of experience from a tertiary intensive care unit participated in a standardised clinical simulation scenario. The emotional state of each participant was assessed before and after completion of the scenario using a validated eight-item scale containing bipolar oppositional descriptors of emotion. The cognitive load of each participant was assessed after the completion of the scenario using a validated subjective rating tool. A total of 103 medical and nursing staff participated in the study. The participants felt more relaxed (-0.28±1.15 vs 0.14±1, Pcognitive load for all participants was 6.67±1.41. There was no significant difference in the cognitive loads among medical staff versus nursing staff (6.61±2.3 vs 6.62±1.7; P>0.05). A well-designed complex high fidelity critical care simulation scenario can be evaluated to identify the relative cognitive load of the participants' experience and their emotional state. The movement of learners emotionally from a more negative state to a positive state suggests that simulation can be an effective tool for improved knowledge transfer and offers more opportunity for dynamic thinking.

  2. National scale biomass estimators for United States tree species

    Science.gov (United States)

    Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

    2003-01-01

    Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

  3. Estimated use of water in the United States in 2015

    Science.gov (United States)

    Dieter, Cheryl A.; Maupin, Molly A.; Caldwell, Rodney R.; Harris, Melissa A.; Ivahnenko, Tamara I.; Lovelace, John K.; Barber, Nancy L.; Linsey, Kristin S.

    2018-06-19

    Water use in the United States in 2015 was estimated to be about 322 billion gallons per day (Bgal/d), which was 9 percent less than in 2010. The 2015 estimates put total withdrawals at the lowest level since before 1970, following the same overall trend of decreasing total withdrawals observed from 2005 to 2010. Freshwater withdrawals were 281 Bgal/d, or 87 percent of total withdrawals, and saline-water withdrawals were 41.0 Bgal/d, or 13 percent of total withdrawals. Fresh surface-water withdrawals (198 Bgal/d) were 14 percent less than in 2010, and fresh groundwater withdrawals (82.3 Bgal/day) were about 8 percent greater than in 2010. Saline surface-water withdrawals were 38.6 Bgal/d, or 14 percent less than in 2010. Total saline groundwater withdrawals in 2015 were 2.34 Bgal/d, mostly for mining use.Thermoelectric power and irrigation remained the two largest uses of water in 2015, and total withdrawals decreased for thermoelectric power but increased for irrigation. With­drawals in 2015 for thermoelectric power were 18 percent less and withdrawals for irrigation were 2 percent greater than in 2010. Similarly, other uses showed reductions compared to 2010, specifically public supply (–7 percent), self-supplied domestic (–8 percent), self-supplied industrial (–9 percent), and aquaculture (–16 percent). In addition to irrigation (2 percent), mining (1 percent) reported larger withdrawals in 2015 than in 2010. Livestock withdrawals remained essentially the same in 2015 compared to 2010 (0 percent change). Thermoelectric power, irrigation, and public-supply withdrawals accounted for 90 percent of total withdrawals in 2015.Withdrawals for thermoelectric power were 133 Bgal/d in 2015 and represented the lowest levels since before 1970. Surface-water withdrawals accounted for more than 99 percent of total thermoelectric-power withdrawals, and 72 percent of those surface-water withdrawals were from freshwater sources. Saline surface-water withdrawals for

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

    Science.gov (United States)

    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.

  5. Do enhanced states exist? Boosting cognitive capacities through an action video-game.

    Science.gov (United States)

    Kozhevnikov, Maria; Li, Yahui; Wong, Sabrina; Obana, Takashi; Amihai, Ido

    2018-04-01

    This research reports the existence of enhanced cognitive states in which dramatic temporary improvements in temporal and spatial aspects of attention were exhibited by participants who played (but not by those who merely observed) action video-games meeting certain criteria. Specifically, Experiments 1 and 2 demonstrate that the attentional improvements were exhibited only by participants whose skills matched the difficulty level of the video game. Experiment 2 showed that arousal (as reflected by the reduction in parasympathetic activity and increase in sympathetic activity) is a critical physiological condition for enhanced cognitive states and corresponding attentional enhancements. Experiment 3 showed that the cognitive enhancements were transient, and were no longer observed after 30 min of rest following video-gaming. Moreover, the results suggest that the enhancements were specific to tasks requiring visual-spatial focused attention, but not distribution of spatial attention as has been reported to improve significantly and durably as a result of long-term video-game playing. Overall, the results suggest that the observed enhancements cannot be simply due to the activity of video-gaming per se, but might rather represent an enhanced cognitive state resulting from specific conditions (heightened arousal in combination with active engagement and optimal challenge), resonant with what has been described in previous phenomenological literature as "flow" (Csikszentmihalyi, 1975) or "peak experiences" (Maslov, 1962). The findings provide empirical evidence for the existence of the enhanced cognitive states and suggest possibilities for consciously accessing latent resources of our brain to temporarily boost our cognitive capacities upon demand. Copyright © 2018 Elsevier B.V. All rights reserved.

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

    KAUST Repository

    Majeed, Muhammad Usman

    2017-01-01

    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

  7. Effect of Integrated Cognitive Therapy on Hippocampal Functional Connectivity Patterns in Stroke Patients with Cognitive Dysfunction: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Shanli Yang

    2014-01-01

    Full Text Available Objective. This study aimed to identify abnormal hippocampal functional connectivity (FC following ischemic stroke using resting-state fMRI. We also explored whether abnormal hippocampal FC could be modulated by integrated cognitive therapy and tested whether these alterations were associated with cognitive performance. Methods. 18 right-handed cognitively impaired ischemic stroke patients and 18 healty control (HC subjects were included in this study. Stroke subjects were scanned at baseline and after integrated cognitive therapy, while HCs were only scanned at baseline, to identify regions that show significant correlations with the seed region. Behavioral and cognitive assessments were obtained before each scan. Results. During the resting state, we found abnormal hippocampal FC associated with temporal regions, insular cortex, cerebellum, and prefrontal cortex in stroke patients compared to HCs. After integrated cognitive therapy, however, the stroke group showed increased hippocampal FC mainly located in the prefrontal gyrus and the default mode network (DMN. Altered hippocampal FC was associated with cognitive improvement. Conclusion. Resting-state fMRI may provide novel insight into the study of functional networks in the brain after stroke. Furthermore, altered hippocampal FC may be a compensatory mechanism for cognitive recovery after ischemic stroke.

  8. Common effects of amnestic mild cognitive impairment on resting-state connectivity across four independent studies

    Directory of Open Access Journals (Sweden)

    Angela eTam

    2015-12-01

    Full Text Available Resting-state functional connectivity is a promising biomarker for Alzheimer’s disease. However, previous resting-state functional magnetic resonance imaging studies in Alzheimer’s disease and amnestic mild cognitive impairment (aMCI have shown limited reproducibility as they have had small sample sizes and substantial variation in study protocol. We sought to identify functional brain networks and connections that could consistently discriminate normal aging from aMCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore combined four datasets collected independently, including 112 healthy controls and 143 patients with aMCI. We systematically tested multiple brain connections for associations with aMCI using a weighted average routinely used in meta-analyses. The largest effects involved the superior medial frontal cortex (including the anterior cingulate, dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with aMCI exhibited significantly decreased connectivity between default mode network nodes and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified common aMCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 140 to upwards of 600 total subjects to achieve adequate statistical power in the context of a multisite study with 5-10 scanning sites and about 10 subjects per group and per site. If our findings can be replicated and associated with other established biomarkers of Alzheimer’s disease (e.g. amyloid and tau quantification, then these functional connections may be promising candidate biomarkers for Alzheimer’s disease.

  9. Automatic feedback on cognitive load and emotional state of traffic controllers

    NARCIS (Netherlands)

    Neerincx, M.A.; Harbers, M.; Lim, D.; Tas, V. van der

    2014-01-01

    Workload research in command, information and process-control centers, resulted in a modular and formal Cognitive Load and Emotional State (CLES) model with transparent and easy-to-modify classification and assessment techniques. The model distinguishes three representation and analysis layers with

  10. Training Nurses in Cognitive Assessment: Uses and Misuses of the Mini-Mental State Examination

    Science.gov (United States)

    Koder, Deborah-Anne; Klahr, Amanda

    2010-01-01

    The Mini-Mental State Examination (MMSE) is one of the most commonly used instruments to screen for cognitive deficits within the hospital setting. However training in how to administer this widely used tool is scarce with little, if any, formal training for nursing staff. Scores are also often misused with over reliance on results and cut-offs to…

  11. Introduction to using neurophysiological signals that reflect cognitive or affective state (Editorial)

    NARCIS (Netherlands)

    Erp, J.B.F. van; Brouwer, A.M.; Zander, T.O.

    2015-01-01

    The central question of this Frontiers Research Topic is: What can we learn from brain and other physiological signals about an individual's cognitive and affective state and how can we use this information? This question reflects three important issues which are addressed by the 22 articles in this

  12. Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Qi Lin

    2018-04-01

    Full Text Available Resting-state functional connectivity (rs-FC is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11 scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

  13. The Alzheimer's prevention initiative composite cognitive test score: sample size estimates for the evaluation of preclinical Alzheimer's disease treatments in presenilin 1 E280A mutation carriers.

    Science.gov (United States)

    Ayutyanont, Napatkamon; Langbaum, Jessica B S; Hendrix, Suzanne B; Chen, Kewei; Fleisher, Adam S; Friesenhahn, Michel; Ward, Michael; Aguirre, Camilo; Acosta-Baena, Natalia; Madrigal, Lucìa; Muñoz, Claudia; Tirado, Victoria; Moreno, Sonia; Tariot, Pierre N; Lopera, Francisco; Reiman, Eric M

    2014-06-01

    To identify a cognitive composite that is sensitive to tracking preclinical Alzheimer's disease decline to be used as a primary end point in treatment trials. We capitalized on longitudinal data collected from 1995 to 2010 from cognitively unimpaired presenilin 1 (PSEN1) E280A mutation carriers from the world's largest known early-onset autosomal dominant Alzheimer's disease kindred to identify a composite cognitive test with the greatest statistical power to track preclinical Alzheimer's disease decline and estimate the number of carriers age 30 years and older needed to detect a treatment effect in the Alzheimer's Prevention Initiative's (API) preclinical Alzheimer's disease treatment trial. The mean-to-standard-deviation ratios (MSDRs) of change over time were calculated in a search for the optimal combination of 1 to 7 cognitive tests/subtests drawn from the neuropsychological test battery in cognitively unimpaired mutation carriers during a 2- and 5-year follow-up period (n = 78 and 57), using data from noncarriers (n = 31 and 56) during the same time period to correct for aging and practice effects. Combinations that performed well were then evaluated for robustness across follow-up years, occurrence of selected items within top-performing combinations, and representation of relevant cognitive domains. The optimal test combination included Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Recall, CERAD Boston Naming Test (high frequency items), Mini-Mental State Examination (MMSE) Orientation to Time, CERAD Constructional Praxis, and Raven's Progressive Matrices (Set A), with an MSDR of 1.62. This composite is more sensitive than using either the CERAD Word List Recall (MSDR = 0.38) or the entire CERAD-Col battery (MSDR = 0.76). A sample size of 75 cognitively normal PSEN1 E280A mutation carriers aged 30 years and older per treatment arm allows for a detectable treatment effect of 29% in a 60-month trial (80% power, P = .05). We

  14. 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.

  15. Limitations of a Short Demographic Questionnaire for Bedside Estimation of Patients’ Global Cognitive Functioning in Epilepsy Patients

    Directory of Open Access Journals (Sweden)

    Iris Gorny

    2018-03-01

    Full Text Available ObjectivesThe German socio-demographic estimation scale was developed by Jahn et al. (1 to quickly predict premorbid global cognitive functioning in patients. So far, it has been validated in healthy adults and has shown a good correlation with the full and verbal IQ of the Wechsler Adult Intelligence Scale (WAIS in this group. However, there are no data regarding its use as a bedside test in epilepsy patients.MethodsForty native German speaking adult patients with refractory epilepsy were included. They completed a neuropsychological assessment, including a nine scale short form of the German version of the WAIS-III and the German socio-demographic estimation scale by Jahn et al. (1 during their presurgical diagnostic stay in our center. We calculated means, correlations, and the rate of concordance (range ±5 and ±7.5 IQ score points between these two measures for the whole group, and a subsample of 19 patients with a global cognitive functioning level within 1 SD of the mean (IQ score range 85–115 and who had completed their formal education before epilepsy onset.ResultsThe German demographic estimation scale by Jahn et al. (1 showed a significant mean overestimation of the global cognitive functioning level of eight points in the epilepsy patient sample compared with the short form WAIS-III score. The accuracy within a range of ±5 or ±7.5 IQ score points for each patient was similar to that of the healthy controls reported by Jahn et al. (1 in our subsample, but not in our whole sample.ConclusionOur results show that the socio-demographic scale by Jahn et al. (1 is not sufficiently reliable as an estimation tool of global cognitive functioning in epilepsy patients. It can be used to estimate global cognitive functioning in a subset of patients with a normal global cognitive functioning level who have completed their formal education before epilepsy onset, but it does not reliably predict global cognitive functioning in epilepsy patients

  16. Steady-state evoked potentials possibilities for mental-state estimation

    Science.gov (United States)

    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.

  17. Processing deficits in monitoring analog and digital displays: Implications for attentional theory and mental-state estimation research

    Science.gov (United States)

    Payne, David G.; Gunther, Virginia A. L.

    1988-01-01

    Subjects performed short term memory tasks, involving both spatial and verbal components, and a visual monitoring task involving either analog or digital display formats. These two tasks (memory vs. monitoring) were performed both singly and in conjunction. Contrary to expectations derived from multiple resource theories of attentional processes, there was no evidence that when the two tasks involved the same cognitive codes (i.e., either both spatial or both verbal/linguistics) there was more of a dual task performance decrement than when the two tasks employed different cognitive codes/processes. These results are discussed in terms of their implications for theories of attentional processes and also for research in mental state estimation.

  18. Pain treatment for nursing home residents differs according to cognitive state - a cross-sectional study.

    Science.gov (United States)

    Bauer, Ulrike; Pitzer, Stefan; Schreier, Maria Magdalena; Osterbrink, Jürgen; Alzner, Reinhard; Iglseder, Bernhard

    2016-06-17

    Communication skills are known to decrease with advancing cognitive impairment. Analgesic treatment in long-term care may be deficient due to the residents' impaired ability to communicate their pain and needs. Undertreated pain frequently leads to rising BPSD in residents with cognitive impairment, resulting in a treatment with antipsychotics. Aim of this study was the analysis of differences in assessment and pharmacological treatment of pain in nursing home residents relative to their cognitive state and ability to articulate pain. Data stems from the baseline of a non-experimental pre-post-study in 12 Austrian nursing homes. Residents' pain prevalence in relation to pain assessment and cognitive decline was assessed, data on medical diagnoses and prescriptions were retrieved from the nursing homes' documentation (n = 425). Residents were first divided into two groups: Residents with MMSE ≥ 18 were selected into group CUS (cognitively unimpaired/slightly impaired), residents with MMSE ≤ 17 were selected into group CI (cognitively moderately to severely impaired). CI residents were then sub-grouped according to their ability to communicate pain via the Verbal Rating Scale (VRS) (i.e. group CI-V, group CI-NV). Pain behavior of CI residents was assessed with a modified German version of PAINAD. Group differences were tested with ANOVA and H-test, 95 % confidence intervals were calculated and associations were tested with log-binomial regression. Pain prevalence in CI residents irrespective of their ability to communicate pain was 80 % and exceeded the CUS group prevalence significantly by 14 %. CI residents had significantly less analgesic prescriptions. Furthermore, CI residents have a significantly higher risk of getting no analgesics when in pain than CUS residents (CI-V: RR =2.6, CI-NV: RR =3.4). Use of antipsychotics was high in all groups (49 - 65 %) with more prescriptions in the cognitively impaired group. Results point toward an

  19. Information-geometric measures estimate neural interactions during oscillatory brain states

    Directory of Open Access Journals (Sweden)

    Yimin eNie

    2014-02-01

    Full Text Available The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG, a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

  20. State and parameter estimation of state-space model with entry-wise correlated uniform noise

    Czech Academy of Sciences Publication Activity Database

    Pavelková, Lenka; Kárný, Miroslav

    2014-01-01

    Roč. 28, č. 11 (2014), s. 1189-1205 ISSN 0890-6327 R&D Projects: GA TA ČR TA01030123; GA ČR GA13-13502S Institutional research plan: CEZ:AV0Z1075907 Keywords : state-space models * bounded noise * filtering problems * estimation algorithms * uncertain dynamic systems Subject RIV: BC - Control Systems Theory Impact factor: 1.346, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/pavelkova-0422958.pdf

  1. The effect of adult children living in the United States on the likelihood of cognitive impairment for older parents living in Mexico.

    Science.gov (United States)

    Downer, Brian; González-González, Cesar; Goldman, Noreen; Pebley, Anne R; Wong, Rebeca

    2018-01-01

    The increased risk for poor physical and mental health outcomes for older parents in Mexico who have an adult child living in the United States may contribute to an increased risk for cognitive impairment in this population. The objective of this study was to examine if older adults in Mexico who have one or more adult children living in the United States are more or less likely to develop cognitive impairment over an 11-year period compared to older adults who do not have any adult children living in the United States. Data for this study came from Wave I (2001) and Wave III (2012) of the Mexican Health and Aging Study. The final sample included 2609 participants aged 60 and over who were not cognitively impaired in 2001 and had one or more adult children (age ≥15). Participants were matched using a propensity score that was estimated with a multivariable logistic regression model that included sociodemographic characteristics and migration history of the older parents. Having one or more adult children living in the United States is associated with lower socioeconomic status and higher number of depressive symptoms, but greater social engagement for older parents living in Mexico. No significant differences in the odds for developing cognitive impairment according to having one or more adult children living in the United States were detected. In summary, having one or more adult children living in the United States was associated with characteristics that may increase and decrease the risk for cognitive impairment. This may contribute to the non-significant relationship between migration status of adult children and likelihood for cognitive impairment for older parents living in Mexico.

  2. A computerized method of estimation of sensor motor reaction, complicated with additional cognitive component

    Directory of Open Access Journals (Sweden)

    Gennadij V. Ganin

    2011-05-01

    Full Text Available This article is related to new integrated approach to objective computerizing evaluation of cognitive-component which delays the latent period of the sensor-motor reaction on specific visual stimuli, which carried different semantic information. It is recommended to use this method for clinical diagnostic of pathologies associated with disorders of cognitive human activity and for assessment of mental fatigue.

  3. Number line estimation and complex mental calculation: Is there a shared cognitive process driving the two tasks?

    Science.gov (United States)

    Montefinese, Maria; Semenza, Carlo

    2018-05-17

    It is widely accepted that different number-related tasks, including solving simple addition and subtraction, may induce attentional shifts on the so-called mental number line, which represents larger numbers on the right and smaller numbers on the left. Recently, it has been shown that different number-related tasks also employ spatial attention shifts along with general cognitive processes. Here we investigated for the first time whether number line estimation and complex mental arithmetic recruit a common mechanism in healthy adults. Participants' performance in two-digit mental additions and subtractions using visual stimuli was compared with their performance in a mental bisection task using auditory numerical intervals. Results showed significant correlations between participants' performance in number line bisection and that in two-digit mental arithmetic operations, especially in additions, providing a first proof of a shared cognitive mechanism (or multiple shared cognitive mechanisms) between auditory number bisection and complex mental calculation.

  4. Online State Space Model Parameter Estimation in Synchronous Machines

    Directory of Open Access Journals (Sweden)

    Z. Gallehdari

    2014-06-01

    The suggested approach is evaluated for a sample synchronous machine model. Estimated parameters are tested for different inputs at different operating conditions. The effect of noise is also considered in this study. Simulation results show that the proposed approach provides good accuracy for parameter estimation.

  5. Particle filter based MAP state estimation: A comparison

    NARCIS (Netherlands)

    Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha

    2009-01-01

    MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi

  6. A novel Gaussian model based battery state estimation approach: State-of-Energy

    International Nuclear Information System (INIS)

    He, HongWen; Zhang, YongZhi; Xiong, Rui; Wang, Chun

    2015-01-01

    Highlights: • The Gaussian model is employed to construct a novel battery model. • The genetic algorithm is used to implement model parameter identification. • The AIC is used to decide the best hysteresis order of the battery model. • A novel battery SoE estimator is proposed and verified by two kinds of batteries. - Abstract: State-of-energy (SoE) is a very important index for battery management system (BMS) used in electric vehicles (EVs), it is indispensable for ensuring safety and reliable operation of batteries. For achieving battery SoE accurately, the main work can be summarized in three aspects. (1) In considering that different kinds of batteries show different open circuit voltage behaviors, the Gaussian model is employed to construct the battery model. What is more, the genetic algorithm is employed to locate the optimal parameter for the selecting battery model. (2) To determine an optimal tradeoff between battery model complexity and prediction precision, the Akaike information criterion (AIC) is used to determine the best hysteresis order of the combined battery model. Results from a comparative analysis show that the first-order hysteresis battery model is thought of being the best based on the AIC values. (3) The central difference Kalman filter (CDKF) is used to estimate the real-time SoE and an erroneous initial SoE is considered to evaluate the robustness of the SoE estimator. Lastly, two kinds of lithium-ion batteries are used to verify the proposed SoE estimation approach. The results show that the maximum SoE estimation error is within 1% for both LiFePO 4 and LiMn 2 O 4 battery datasets

  7. Methodology for estimating soil carbon for the forest carbon budget model of the United States, 2001

    Science.gov (United States)

    L. S. Heath; R. A. Birdsey; D. W. Williams

    2002-01-01

    The largest carbon (C) pool in United States forests is the soil C pool. We present methodology and soil C pool estimates used in the FORCARB model, which estimates and projects forest carbon budgets for the United States. The methodology balances knowledge, uncertainties, and ease of use. The estimates are calculated using the USDA Natural Resources Conservation...

  8. Neuropsychological profile in Chinese patients with Parkinson's disease and normal global cognition according to Mini-Mental State Examination Score.

    Science.gov (United States)

    Qiao, Jin; Zheng, Xiyuan; Wang, Xiaoyan; Lu, Wenhui; Cao, Hongmei; Qin, Xing

    2015-01-01

    Cognitive impairments have been reported to be more common in non-demented patients with Parkinson's disease (PD) and education levels play an important role in intelligence. The studies on cognitive impairments in Chinese PD patients with higher education levels and normal global cognition according to Mini-Mental State Examination Score (MMSE) have not been reported. We enrolled 69 consecutive PD patients with over 6 years education levels and a MMSE score above 24 (of 30) and performed a battery of neuropsychological scales. There are extensive cognitive domain impairments in PD patients with "normal" global cognitive according to MMSE. Montreal Cognitive Assessment (MoCA) is a highly sensitive scale to screen cognitive impairments in PD. The cutoff score of 28 on the MMSE screening for cognitive impairment in Chinese PD patients with high education levels may be more appropriate.

  9. Resting-state slow wave power, healthy aging and cognitive performance.

    Science.gov (United States)

    Vlahou, Eleni L; Thurm, Franka; Kolassa, Iris-Tatjana; Schlee, Winfried

    2014-05-29

    Cognitive functions and spontaneous neural activity show significant changes over the life-span, but the interrelations between age, cognition and resting-state brain oscillations are not well understood. Here, we assessed performance on the Trail Making Test and resting-state magnetoencephalographic (MEG) recordings from 53 healthy adults (18-89 years old) to investigate associations between age-dependent changes in spontaneous oscillatory activity and cognitive performance. Results show that healthy aging is accompanied by a marked and linear decrease of resting-state activity in the slow frequency range (0.5-6.5 Hz). The effects of slow wave power on cognitive performance were expressed as interactions with age: For older (>54 years), but not younger participants, enhanced delta and theta power in temporal and central regions was positively associated with perceptual speed and executive functioning. Consistent with previous work, these findings substantiate further the important role of slow wave oscillations in neurocognitive function during healthy aging.

  10. Screening an elderly hearing impaired population for mild cognitive impairment using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA).

    Science.gov (United States)

    Lim, Magdalene Yeok Leng; Loo, Jenny Hooi Yin

    2018-07-01

    To determine if there is an association between hearing loss and poorer cognitive scores on Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) and to determine if poor hearing acuity affects scoring on the cognitive screening tests of MMSE and MoCA. One hundred fourteen elderly patients (Singapore residents) aged between 55 and 86 years were sampled. Participants completed a brief history questionnaire, pure tone audiometry, and 2 cognitive screening tests-the MMSE and MoCA. Average hearing thresholds of the better ear in the frequencies of 0.5, 1, 2, and 4 kHz were used for data analysis. Hearing loss was significantly associated with poorer cognitive scores in Poisson regression models adjusted for age. Mini-Mental State Examination scores were shown to decrease by 2.8% (P = .029), and MoCA scores by 3.5% (P = .013) for every 10 dB of hearing loss. Analysis of hearing-sensitive components of "Registration" and "Recall" in MMSE and MoCA using chi-square tests showed significantly poorer performance in the hearing loss group as compared to the normal hearing group. Phonetic analysis of target words with high error rates shows that the poor performance was likely contributed by decreased hearing acuity, on top of a possible true deficit in cognition in the hearing impaired. Hearing loss is associated with poorer cognitive scores on MMSE and MoCA, and cognitive scoring is likely confounded by poor hearing ability. This highlights an important, often overlooked aspect of sensory impairment during cognitive screening. Provisions should be made when testing for cognition in the hearing-impaired population to avoid over-referral and subsequent misdiagnoses of cognitive impairment. Copyright © 2018 John Wiley & Sons, Ltd.

  11. [Mini-Mental State Examination: Screening and Diagnosis of Cognitive Decline, Using New Normative Data].

    Science.gov (United States)

    Santana, Isabel; Duro, Diana; Lemos, Raquel; Costa, Vanessa; Pereira, Miguel; Simões, Mário R; Freitas, Sandra

    2016-04-01

    The Mini-Mental State Examination is the most commonly used cognitive screening test. In Portugal, the cut-off scores are defined according to literacy groups, but different proposals have been recommended by more representative studies. We therefore propose to confirm the influence of demographical variables, such as age and education, in the subjectâs performance; evaluating the discriminant ability of the new normative data; and to further examine the diagnostic acuity of the validated cut-off scoring for mild cognitive impairment and for the most prevalent types of dementia. Our study includes 1 441 educated subjects, divided into seven subgroups: Mild cognitive impairment, Alzheimer's disease, frontotemporal dementia, vascular dementia, dementia with Lewy bodies, community-controls and memory clinic-controls. Altogether age and education explain 10.4% of the Mini-Mental State Examination results variance, with both variables contributing significantly to the resultsâ prediction. The diagnostic acuity based on the most recent normative data was always higher than the one obtained through the validation cut-off scoring, revealing an overall excellent specificity (superior to 90%) and different sensitivity values: excellent for mild Alzheimer's disease (91%), good for dementia with Lewy Bodies (78%) and low for mild cognitive impairment (65%), frontotemporal dementia and vascular dementia (55%). The performance on the Mini-Mental State Examination is influenced by age and education, supporting the use of normative data that consider those variables. With this approach, the Mini-Mental State Examination could be a sensitive and specific instrument for the Alzheimer's disease screening among all healthcare levels. Nevertheless, its diagnostic acuity is limited in other conditions frequently seen in memory clinics, such as Mild Cognitive Impairment and other types of dementia.

  12. Auditory beat stimulation and its effects on cognition and mood states

    Directory of Open Access Journals (Sweden)

    Leila eChaieb

    2015-05-01

    Full Text Available Auditory beat stimulation may be a promising new tool for the manipulation of cognitive processes and the modulation of mood-states. Here we aim to review the literature examining the most current applications of auditory beat stimulation and its targets. We give a brief overview of research on auditory steady-state responses and its relationship to auditory beat stimulation. We have summarized relevant studies investigating the neurophysiological changes related to auditory beat stimulation and how they impact upon the design of appropriate stimulation protocols. Focusing on binaural beat stimulation, we then discuss the role of monaural and binaural beat frequencies in cognition and mood-states, in addition to their efficacy in targeting disease symptoms. We aim to highlight important points concerning stimulation parameters and try to address why there are often contradictory findings with regard to the outcomes of auditory beat stimulation.

  13. Auditory beat stimulation and its effects on cognition and mood States.

    Science.gov (United States)

    Chaieb, Leila; Wilpert, Elke Caroline; Reber, Thomas P; Fell, Juergen

    2015-01-01

    Auditory beat stimulation may be a promising new tool for the manipulation of cognitive processes and the modulation of mood states. Here, we aim to review the literature examining the most current applications of auditory beat stimulation and its targets. We give a brief overview of research on auditory steady-state responses and its relationship to auditory beat stimulation (ABS). We have summarized relevant studies investigating the neurophysiological changes related to ABS and how they impact upon the design of appropriate stimulation protocols. Focusing on binaural-beat stimulation, we then discuss the role of monaural- and binaural-beat frequencies in cognition and mood states, in addition to their efficacy in targeting disease symptoms. We aim to highlight important points concerning stimulation parameters and try to address why there are often contradictory findings with regard to the outcomes of ABS.

  14. Role of state-dependent learning in the cognitive effects of caffeine in mice.

    Science.gov (United States)

    Sanday, Leandro; Zanin, Karina A; Patti, Camilla L; Fernandes-Santos, Luciano; Oliveira, Larissa C; Longo, Beatriz M; Andersen, Monica L; Tufik, Sergio; Frussa-Filho, Roberto

    2013-08-01

    Caffeine is the most widely used psychoactive substance in the world and it is generally believed that it promotes beneficial effects on cognitive performance. However, there is also evidence suggesting that caffeine has inhibitory effects on learning and memory. Considering that caffeine may have anxiogenic effects, thus changing the emotional state of the subjects, state-dependent learning may play a role in caffeine-induced cognitive alterations. Mice were administered 20 mg/kg caffeine before training and/or before testing both in the plus-maze discriminative avoidance task (an animal model that concomitantly evaluates learning, memory, anxiety-like behaviour and general activity) and in the inhibitory avoidance task, a classic paradigm for evaluating memory in rodents. Pre-training caffeine administration did not modify learning, but produced an anxiogenic effect and impaired memory retention. While pre-test administration of caffeine did not modify retrieval on its own, the pre-test administration counteracted the memory deficit induced by the pre-training caffeine injection in both the plus-maze discriminative and inhibitory avoidance tasks. Our data demonstrate that caffeine-induced memory deficits are critically related to state-dependent learning, reinforcing the importance of considering the participation of state-dependency on the interpretation of the cognitive effects of caffeine. The possible participation of caffeine-induced anxiety alterations in state-dependent memory deficits is discussed.

  15. Structurally-constrained relationships between cognitive states in the human brain.

    Directory of Open Access Journals (Sweden)

    Ann M Hermundstad

    2014-05-01

    Full Text Available The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function.

  16. Normalized Mini-Mental State Examination for assessing cognitive change in population-based brain aging studies.

    Science.gov (United States)

    Philipps, Viviane; Amieva, Hélène; Andrieu, Sandrine; Dufouil, Carole; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène; Proust-Lima, Cécile

    2014-01-01

    The Mini-Mental State Examination (MMSE) is widely used in population-based longitudinal studies to quantify cognitive change. However, its poor metrological properties, mainly ceiling/floor effects and varying sensitivity to change, have largely restricted its usefulness. We propose a normalizing transformation that corrects these properties, and makes possible the use of standard statistical methods to analyze change in MMSE scores. The normalizing transformation designed to correct at best the metrological properties of MMSE was estimated and validated on two population-based studies (n = 4,889, 20-year follow-up) by cross-validation. The transformation was also validated on two external studies with heterogeneous samples mixing normal and pathological aging, and samples including only demented subjects. The normalizing transformation provided correct inference in contrast with models analyzing the change in crude MMSE that most often lead to biased estimates of risk factors and incorrect conclusions. Cognitive change can be easily and properly assessed with the normalized MMSE using standard statistical methods such as linear (mixed) models. © 2014 S. Karger AG, Basel.

  17. Optimal state estimation over communication channels with random delays

    KAUST Repository

    Mahmoud, Magdi S.; Liu, Bo

    2013-01-01

    This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node stores the sum of arrived measurements between two adjacent processing time instants and also counts the number of arrived measurements. The original linear system is modeled as an extended system with uncertain observation to capture the feature of communication, then the optimal estimation algorithm of systems with uncertain observations is proposed. Additionally, a numerical simulation is presented to show the performance of this work. © 2013 The Franklin Institute.

  18. Optimal state estimation over communication channels with random delays

    KAUST Repository

    Mahmoud, Magdi S.

    2013-04-01

    This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node stores the sum of arrived measurements between two adjacent processing time instants and also counts the number of arrived measurements. The original linear system is modeled as an extended system with uncertain observation to capture the feature of communication, then the optimal estimation algorithm of systems with uncertain observations is proposed. Additionally, a numerical simulation is presented to show the performance of this work. © 2013 The Franklin Institute.

  19. Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

    International Nuclear Information System (INIS)

    Ng, Kong Soon; Moo, Chin-Sien; Chen, Yi-Ping; Hsieh, Yao-Ching

    2009-01-01

    The coulomb counting method is expedient for state-of-charge (SOC) estimation of lithium-ion batteries with high charging and discharging efficiencies. The charging and discharging characteristics are investigated and reveal that the coulomb counting method is convenient and accurate for estimating the SOC of lithium-ion batteries. A smart estimation method based on coulomb counting is proposed to improve the estimation accuracy. The corrections are made by considering the charging and operating efficiencies. Furthermore, the state-of-health (SOH) is evaluated by the maximum releasable capacity. Through the experiments that emulate practical operations, the SOC estimation method is verified to demonstrate the effectiveness and accuracy.

  20. 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 ...

  1. 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...

  2. Subclinical thyroid disorders and cognitive performance among adolescents in the United States

    Directory of Open Access Journals (Sweden)

    Wilson Jim L

    2006-04-01

    Full Text Available Abstract Background Thyroid hormone plays a crucial role in the growth and function of the central nervous system. The purpose of the study was to examine the relationships between the status of subclinical thyroid conditions and cognition among adolescents in the United States. Methods Study sample included 1,327 adolescents 13 to 16 years old who participated in the Third National Health and Nutrition Examination Survey (NHANES III. Serum thyroxine (T4 and thyroid stimulating hormone (TSH were measured and subclinical hypothyroidism, subclinical hyperthyroidism, and euthyroid groups were defined. Cognitive performance was assessed using the subscales of the Wide Range Achievement Test-Revised (WRAT-R and the Wechsler Intelligence Scale for Children-Revised (WISC-R. The age-corrected scaled scores for arithmetic, reading, block design, and digit span were derived from the cognitive assessments. Results Subclinical hypothyroidism was found in 1.7% and subclinical hyperthyroidism was found in 2.3% of the adolescents. Cognitive assessment scores on average tended to be lower in adolescents with subclinical hyperthyroidism and higher in those with subclinical hypothyroidism than the score for the euthyroid group. Adolescents with subclinical hypothyroidism had significantly better scores in block design and reading than the euthyroid subjects even after adjustment for a number of variables including sex, age, and family income level. Conclusion Subclinical hypothyroidism was associated with better performance in some areas of cognitive functions while subclinical hyperthyroidism could be a potential risk factor.

  3. Subclinical thyroid disorders and cognitive performance among adolescents in the United States.

    Science.gov (United States)

    Wu, Tiejian; Flowers, Joanne W; Tudiver, Fred; Wilson, Jim L; Punyasavatsut, Natavut

    2006-04-19

    Thyroid hormone plays a crucial role in the growth and function of the central nervous system. The purpose of the study was to examine the relationships between the status of subclinical thyroid conditions and cognition among adolescents in the United States. Study sample included 1,327 adolescents 13 to 16 years old who participated in the Third National Health and Nutrition Examination Survey (NHANES III). Serum thyroxine (T4) and thyroid stimulating hormone (TSH) were measured and subclinical hypothyroidism, subclinical hyperthyroidism, and euthyroid groups were defined. Cognitive performance was assessed using the subscales of the Wide Range Achievement Test-Revised (WRAT-R) and the Wechsler Intelligence Scale for Children-Revised (WISC-R). The age-corrected scaled scores for arithmetic, reading, block design, and digit span were derived from the cognitive assessments. Subclinical hypothyroidism was found in 1.7% and subclinical hyperthyroidism was found in 2.3% of the adolescents. Cognitive assessment scores on average tended to be lower in adolescents with subclinical hyperthyroidism and higher in those with subclinical hypothyroidism than the score for the euthyroid group. Adolescents with subclinical hypothyroidism had significantly better scores in block design and reading than the euthyroid subjects even after adjustment for a number of variables including sex, age, and family income level. Subclinical hypothyroidism was associated with better performance in some areas of cognitive functions while subclinical hyperthyroidism could be a potential risk factor.

  4. The Telephone Interview for Cognitive Status: Creating a crosswalk with the Mini-Mental State Exam

    Science.gov (United States)

    Fong, Tamara G.; Fearing, Michael A.; Jones, Richard N.; Shi, Peilin; Marcantonio, Edward R.; Rudolph, James L.; Yang, Frances M.; Kiely, Dan K.; Inouye, Sharon K.

    2009-01-01

    Background Brief cognitive screening measures are valuable tools for both research and clinical applications. The most widely used instrument, the Mini-Mental State Examination (MMSE) is limited in that it must be administered face-to-face, cannot be used in participants with visual or motor impairments, and is protected by copyright. Alternative screening instruments, such as the Telephone Interview for Cognitive Status (TICS) have been developed and may provide a valid alternative with comparable cut point scores to rate global cognitive function. Methods MMSE, TICS-30, and TICS-40 scores from 746 community dwelling elders who participated in the Aging, Demographics, and Memory Study (ADAMS) were analyzed with equipercentile equating, a statistical process of determining comparable scores based on percentile equivalents on different forms of an examination. Results Scores from the MMSE and the TICS-30 and TICS-40 corresponded well and clinically relevant cut point scores were determined; for example, an MMSE score of 23 is equivalent to 17 and 20 on the TICS-30 and TICS-40, respectively. Conclusions These findings provide scores that can be used to link TICS and MMSE scores directly. Clinically relevant and important MMSE cut points and the respective ADAMS TICS-30 and TICS-40 cut point scores have been included to identify the degree of cognitive impairment among respondents with any type of cognitive disorder. These results will help with the widespread application of the TICS in both research and clinical practice. PMID:19647495

  5. 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...

  6. Do Individual Differences and Aging Effects in the Estimation of Geographical Slant Reflect Cognitive or Perceptual Effects?

    Directory of Open Access Journals (Sweden)

    Abigail M. Dean

    2016-07-01

    Full Text Available Several individual differences including age have been suggested to affect the perception of slant. A cross-sectional study of outdoor hill estimation (N = 106 was analyzed using individual difference measures of age, experiential knowledge, fitness, personality traits, and sex. Of particular note, it was found that for participants who reported any experiential knowledge about slant, estimates decreased (i.e., became more accurate as conscientiousness increased, suggesting that more conscientious individuals were more deliberate about taking their experiential knowledge (rather than perception into account. Effects of fitness were limited to those without experiential knowledge, suggesting that they, too, may be cognitive rather than perceptual. The observed effects of age, which tended to produce lower, more accurate estimates of hill slant, provide more evidence that older adults do not see hills as steeper. The main effect of age was to lower slant estimates; such effects may be due to implicit experiential knowledge acquired over a lifetime. The results indicate the impact of cognitive, rather than perceptual factors on individual differences in slant estimation.

  7. Estimating mental states of a depressed person with bayesian networks

    NARCIS (Netherlands)

    Klein, Michel C.A.; Modena, Gabriele

    2013-01-01

    In this work in progress paper we present an approach based on Bayesian Networks to model the relationship between mental states and empirical observations in a depressed person. We encode relationships and domain expertise as a Hierarchical Bayesian Network. Mental states are represented as latent

  8. Resting-state fMRI and social cognition: An opportunity to connect.

    Science.gov (United States)

    Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

    2017-09-01

    Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

  9. Using brain-computer interfaces and brain-state dependent stimulation as tools in cognitive neuroscience

    Directory of Open Access Journals (Sweden)

    Ole eJensen

    2011-05-01

    Full Text Available Large efforts are currently being made to develop and improve online analysis of brain activity which can be used e.g. for brain-computer interfacing (BCI. A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for aiding the disabled and for augmenting human performance. While technical developments obviously are important, we will here argue that new insight gained from cognitive neuroscience can be used to identify signatures of neural activation which reliably can be modulated by the subject at will. This review will focus mainly on oscillatory activity in the alpha band which is strongly modulated by changes in covert attention. Besides developing BCIs for their traditional purpose, they might also be used as a research tool for cognitive neuroscience. There is currently a strong interest in how brain state fluctuations impact cognition. These state fluctuations are partly reflected by ongoing oscillatory activity. The functional role of the brain state can be investigated by introducing stimuli in real time to subjects depending on the actual state of the brain. This principle of brain-state dependent stimulation may also be used as a practical tool for augmenting human behavior. In conclusion, new approaches based on online analysis of ongoing brain activity are currently in rapid development. These approaches are amongst others informed by new insight gained from EEG/MEG studies in cognitive neuroscience and hold the promise of providing new ways for investigating the brain at work.

  10. Event-based state estimation a stochastic perspective

    CERN Document Server

    Shi, Dawei; Chen, Tongwen

    2016-01-01

    This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs ...

  11. Response-Based Estimation of Sea State Parameters

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2007-01-01

    of measured ship responses. It is therefore interesting to investigate how the filtering aspect, introduced by FRF, affects the final outcome of the estimation procedures. The paper contains a study based on numerical generated time series, and the study shows that filtering has an influence...... calculated by a 3-D time domain code and by closed-form (analytical) expressions, respectively. Based on comparisons with wave radar measurements and satellite measurements it is seen that the wave estimations based on closedform expressions exhibit a reasonable energy content, but the distribution of energy...

  12. Guidelines for cognitive behavioral training within doctoral psychology programs in the United States: report of the Inter-organizational Task Force on Cognitive and Behavioral Psychology Doctoral Education.

    Science.gov (United States)

    Klepac, Robert K; Ronan, George F; Andrasik, Frank; Arnold, Kevin D; Belar, Cynthia D; Berry, Sharon L; Christofff, Karen A; Craighead, Linda W; Dougher, Michael J; Dowd, E Thomas; Herbert, James D; McFarr, Lynn M; Rizvi, Shireen L; Sauer, Eric M; Strauman, Timothy J

    2012-12-01

    The Association for Behavioral and Cognitive Therapies initiated an interorganizational task force to develop guidelines for integrated education and training in cognitive and behavioral psychology at the doctoral level in the United States. Fifteen task force members representing 16 professional associations participated in a year-long series of conferences, and developed a consensus on optimal doctoral education and training in cognitive and behavioral psychology. The recommendations assume solid foundational training that is typical within applied psychology areas such as clinical and counseling psychology programs located in the United States. This article details the background, assumptions, and resulting recommendations specific to doctoral education and training in cognitive and behavioral psychology, including competencies expected in the areas of ethics, research, and practice. Copyright © 2012. Published by Elsevier Ltd.

  13. Using the Oxford Cognitive Screen to Detect Cognitive Impairment in Stroke Patients: A Comparison with the Mini-Mental State Examination.

    Science.gov (United States)

    Mancuso, Mauro; Demeyere, Nele; Abbruzzese, Laura; Damora, Alessio; Varalta, Valentina; Pirrotta, Fabio; Antonucci, Gabriella; Matano, Alessandro; Caputo, Marina; Caruso, Maria Giovanna; Pontiggia, Giovanna Teresa; Coccia, Michela; Ciancarelli, Irene; Zoccolotti, Pierluigi

    2018-01-01

    The Oxford Cognitive Screen (OCS) was recently developed with the aim of describing the cognitive deficits after stroke. The scale consists of 10 tasks encompassing five cognitive domains: attention and executive function, language, memory, number processing, and praxis. OCS was devised to be inclusive and un-confounded by aphasia and neglect. As such, it may have a greater potential to be informative on stroke cognitive deficits of widely used instruments, such as the Mini-Mental State Examination (MMSE) or the Montreal Cognitive Assessment, which were originally devised for demented patients. The present study compared the OCS with the MMSE with regards to their ability to detect cognitive impairments post-stroke. We further aimed to examine performance on the OCS as a function of subtypes of cerebral infarction and clinical severity. 325 first stroke patients were consecutively enrolled in the study over a 9-month period. The OCS and MMSE, as well as the Bamford classification and NIHSS, were given according to standard procedures. About a third of patients (35.3%) had a performance lower than the cutoff (cognitive domains of the OCS. Using the MMSE as a standard of clinical practice, the comparative sensitivity of OCS was 100%. Out of the 208 patients with normal MMSE performance 180 showed impaired performance in at least one domain of the OCS. The discrepancy between OCS and MMSE was particularly strong for patients with milder strokes. As for subtypes of cerebral infarction, fewer patients demonstrated widespread impairments in the OCS in the Posterior Circulation Infarcts category than in the other categories. Overall, the results showed a much higher incidence of cognitive impairment with the OCS than with the MMSE and demonstrated no false negatives for OCS vs MMSE. It is concluded that OCS is a sensitive screen tool for cognitive deficits after stroke. In particular, the OCS detects high incidences of stroke-specific cognitive impairments, not detected

  14. State of the Art in Photon-Density Estimation

    DEFF Research Database (Denmark)

    Hachisuka, Toshiya; Jarosz, Wojciech; Georgiev, Iliyan

    2013-01-01

    scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error...

  15. State of the Art in Photon Density Estimation

    DEFF Research Database (Denmark)

    Hachisuka, Toshiya; Jarosz, Wojciech; Bouchard, Guillaume

    2012-01-01

    scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error...

  16. On algebraic time-derivative estimation and deadbeat state reconstruction

    DEFF Research Database (Denmark)

    Reger, Johann; Jouffroy, Jerome

    2009-01-01

    This paper places into perspective the so-called algebraic time-derivative estimation method recently introduced by Fliess and co-authors with standard results from linear statespace theory for control systems. In particular, it is shown that the algebraic method can essentially be seen...

  17. estimation of background radiation at rivers state university

    African Journals Online (AJOL)

    DJFLEX

    State University of Science and Technology was measured using a specialize digital, radiation meter type, radalert ... KEYWORDS: Radiation, Radalert-50, electronic devices, radiation limit ... electron gun and the back of CRT (Philip and pick,.

  18. Property measurements and inner state estimation of simulated fuel debris

    Energy Technology Data Exchange (ETDEWEB)

    Hirooka, S.; Kato, M.; Morimoto, K.; Washiya, T. [Japan Atomic Energy Agency, Ibaraki (Japan)

    2014-07-01

    Fuel debris properties and inner state such as temperature profile were evaluated by using analysis of simulated fuel debris manufactured from UO{sub 2} and oxidized zircaloy. The center of the fuel debris was expected to be molten state soon after the melt down accident of LWRs because power density was very high. On the other hand, the surface of the fuel debris was cooled in the water. This large temperature gradient may cause inner stress and consequent cracks were expected. (author)

  19. Subclinical thyroid disorders and cognitive performance among adolescents in the United States

    OpenAIRE

    Wilson Jim L; Tudiver Fred; Flowers Joanne W; Wu Tiejian; Punyasavatsut Natavut

    2006-01-01

    Abstract Background Thyroid hormone plays a crucial role in the growth and function of the central nervous system. The purpose of the study was to examine the relationships between the status of subclinical thyroid conditions and cognition among adolescents in the United States. Methods Study sample included 1,327 adolescents 13 to 16 years old who participated in the Third National Health and Nutrition Examination Survey (NHANES III). Serum thyroxine (T4) and thyroid stimulating hormone (TSH...

  20. Tau Protein in Oral Mucosa and Cognitive State: A Cross-sectional Study

    Directory of Open Access Journals (Sweden)

    Luis Fernando Arredondo

    2017-10-01

    Full Text Available Neurodegenerative diseases are characterized by the presence of abnormal aggregates of proteins in brain tissue. Among them, the presence of aggregates of phosphorylated Tau protein (p-Tau is the hallmark of Alzheimer’s disease (AD and other major neurodegenerative disorders such as corticobasal degeneration and frontotemporal dementia among others. Although Tau protein has previously been assumed to be exclusive to the central nervous system, it is also found in peripheral tissues. The purpose of this study was to determine whether there is a differential Tau expression in oral mucosa cells according to cognitive impairment. Eighty-one subjects were enrolled in the study and classified per Mini-Mental State Examination test score into control, mild cognitive impairment (MCI, and severe cognitive impairment (SCI groups. Immunocytochemistry and immunofluorescence revealed the presence of Tau and four p-Tau forms in the cytoplasm and nucleus of oral mucosa cells. More positivity was present in subjects with cognitive impairment than in control subjects, both in the nucleus and cytoplasm, in a speckle pattern. The mRNA expression of Tau by quantitative real-time polymerase chain reaction was higher in SCI as compared with the control group (P < 0.01. A significantly higher percentage of immunopositive cells in the SCI group was found via flow cytometry in comparison to controls and the MCI group (P < 0.01. These findings demonstrate the higher presence of p-Tau and Tau transcript in the oral mucosa of cognitively impaired subjects when compared with healthy subjects. The feasibility of p-Tau quantification by flow cytometry supports the prospective analysis of oral mucosa as a support tool for screening of proteinopathies in cognitively impaired patients.

  1. Effects of acute organophosphate ingestion on cognitive function, assessed with the mini mental state examination

    Directory of Open Access Journals (Sweden)

    S S Jayasinghe

    2012-01-01

    Full Text Available Background : Chronic damage to the central nervous system resulting in cognitive impairment has been shown with repeated, low doses of organophosphorus (OP exposure over month or years. Aim: The study aimed to find out whether there is any cognitive impairment following acute OP exposure that could be detected by a simple screening instrument, the Mini Mental State Examination (MMSE, in clinical settings. Settings and Design: A cohort study. Materials and Methods: The study was conducted with matched controls. Consecutive patients admitted to the hospital with acute ingestion of OP were recruited. Cognitive function was assessed with the MMSE, digit span test, test of long-term memory function and concentration. Patients were assessed twice: at 1 and 6 weeks of exposure. Statistical Analysis: Continuous variables were analyzed with the paired and unpaired T-tests. Non-normally distributed data were analyzed with the Mann-Whitney U test and Wilcoxon Signed Rank test. Discrete variables were analyzed with the Chi-square test. Results: There were 60 patients and 61 controls. The mean age (SD of the patients and controls was 31.5 (11.6 and 31.3 (11.8 years, respectively. Forty-two patients turned up for the second assessment. Significant impairment of cognitive function was seen in the total score of MMSE (95% CI -2.5 to -0.3, orientation (95% CI -1 to -0.2 and language (95% CI -0.9 to -0.1 domains of MMSE, digit span test (95% CI 0.1-1.7 and test of long-term memory function (95% CI 0.3-2.3 in the first assessment compared with the controls. When the results of the second assessment were compared with the controls, no significant differences were seen. Conclusion: Although there was a slight transient cognitive impairment detected with the screening tests following acute OP ingestion, no long-term cognitive defects was detected.

  2. Estimation of working memory in macaques for studying drugs for the treatment of cognitive disorders.

    Science.gov (United States)

    Buccafusco, Jerry J

    2008-12-01

    Non-human primates have served as subjects for studies of the cognition-enhancing potential of novel pharmacological agents for over 25 years. Only recently has a greater appreciation of the translational applicability of this model been realized. Though most Old-World monkeys do not appear to acquire an Alzheimer's-like syndrome in old age, their value resides in the brain physiology they have in common with humans. Paradigms like the delayed matching-to-sample task engender behavior that models aspects of working memory that are substrates for the actions of cognition-enhancing drugs. Our studies have provided information relevant to factors that limit the effectiveness of clinical trial design for compounds that potentially improve cognition. For example, cognition-enhancing compounds from different pharmacological classes, when administered to monkeys, can exhibit remarkable pharmacodynamic effects that outlast the presence of the drug in the body. Studies with non-human primates also can provide information regarding dose ranges and individual subject sensitivity experienced in the clinic. Components of working memory are differentially sensitive to drug effects and may be characterized by different dose ranges for certain compounds, even within the same task. Examples are provided that underscore the possible idiosyncrasies of drug action in the pharmacology of cognition--which could be of critical importance in the design of clinical trials.

  3. 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.

  4. 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.

  5. Impaired insight into illness and cognitive insight in schizophrenia spectrum disorders: Resting state functional connectivity

    Science.gov (United States)

    Gerretsen, Philip; Menon, Mahesh; Mamo, David C.; Fervaha, Gagan; Remington, Gary; Pollock, Bruce G.; Graff-Guerrero, Ariel

    2015-01-01

    Background Impaired insight into illness (clinical insight) in schizophrenia has negative effects on treatment adherence and clinical outcomes. Schizophrenia is described as a disorder of disrupted brain connectivity. In line with this concept, resting state networks (RSNs) appear differentially affected in persons with schizophrenia. Therefore, impaired clinical, or the related construct of cognitive insight (which posits that impaired clinical insight is a function of metacognitive deficits), may reflect alterations in RSN functional connectivity (fc). Based on our previous research, which showed that impaired insight into illness was associated with increased left hemisphere volume relative to right, we hypothesized that impaired clinical insight would be associated with increased connectivity in the DMN with specific left hemisphere brain regions. Methods Resting state MRI scans were acquired for participants with schizophrenia or schizoaffective disorder (n = 20). Seed-to-voxel and ROI-to-ROI fc analyses were performed using the CONN-fMRI fc toolbox v13 for established RSNs. Clinical and cognitive insight were measured with the Schedule for the Assessment of Insight—Expanded Version and Beck Cognitive Insight Scale, respectively, and included as the regressors in fc analyses. Results As hypothesized, impaired clinical insight was associated with increased connectivity in the default mode network (DMN) with the left angular gyrus, and also in the self-referential network (SRN) with the left insula. Cognitive insight was associated with increased connectivity in the dorsal attention network (DAN) with the right inferior frontal cortex (IFC) and left anterior cingulate cortex (ACC). Conclusion Increased connectivity in DMN and SRN with the left angular gyrus and insula, respectively, may represent neural correlates of impaired clinical insight in schizophrenia spectrum disorders, and is consistent with the literature attributing impaired insight to left

  6. Rankings & Estimates: Rankings of the States 2016 and Estimates of School Statistics 2017

    Science.gov (United States)

    National Education Association, 2017

    2017-01-01

    The data presented in this combined report provide facts about the extent to which local, state, and national governments commit resources to public education. NEA Research offers this report to its state and local affiliates as well as to researchers, policymakers, and the public as a tool to examine public education policies, programs, and…

  7. FISH PRODUCTION ESTIMATES FOR GBEDIKERE LAKE, BASSA, KOGI STATE, NIGERIA

    Directory of Open Access Journals (Sweden)

    Samuel Olusegun Adeyemi

    2013-10-01

    Full Text Available Annual estimates of the fish caught by local fishermen in randomly selected fishing villages adjacent to Gbedikere Lake were determined using Catch Assessment (CAS. The studies were carried out within two seasons of low water (February and high water (September periods between 2006 to 2008. Annual fish catch varied from 537.4 mts to 576.9 mts at high water. Mean catch per boat ranged from 7.40 kg to 10.60 kg among the landing sites. A total of 12 fish species were identified belonging to ten families. The catches were dominated by the cichlids with Orechromis niloticus dominating the overall catch compositions. Production estimate was compared with the catches obtained through experimental gill-net sampling and potential fish yield estimates using Ryder’s Morpho - Edaphic Index (MEI as modified by Henderson and Welcomme (1974. Contributions of the gears in use were also done with cast nets ranking above others (29%, followed by the set net (25%, hook and lines (16.6%, traps (16.6%, clap net (8.3%. Management measures were suggested.

  8. State of the art on wind resource estimation

    Energy Technology Data Exchange (ETDEWEB)

    Maribo Pedersen, B.

    1998-12-31

    With the increasing number of wind resource estimation studies carried out for regions, countries and even larger areas all over the world, the IEA finds that the time has come to stop and take stock of the various methods used in these studies. The IEA would therefore like to propose an Experts Meeting on wind resource estimation. The Experts Meeting should describe the models and databases used in the various studies. It should shed light on the strengths and shortcomings of the models and answer questions like: where and under what circumstances should a specific model be used? what is the expected accuracy of the estimate of the model? and what is the applicability? When addressing databases the main goal will be to identify the content and scope of these. Further, the quality, availability and reliability of the databases must also be recognised. In the various studies of wind resources the models and databases have been combined in different ways. A final goal of the Experts Meeting is to see whether it is possible to develop systems of methods which would depend on the available input. These systems of methods should be able to address the simple case (level 0) of a region with barely no data, to the complex case of a region with all available measurements: surface observations, radio soundings, satellite observations and so on. The outcome of the meeting should be an inventory of available models as well as databases and a map of already studied regions. (au)

  9. Estimation of health state utilities in breast cancer

    Directory of Open Access Journals (Sweden)

    Kim SH

    2017-03-01

    Full Text Available Seon-Ha Kim,1 Min-Woo Jo,2 Minsu Ock,2 Hyeon-Jeong Lee,2 Jong-Won Lee3,4 1Department of Nursing, College of Nursing, Dankook University, Cheonan, 2Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, 3Department of Breast and Endocrine Surgery, Asan Medical Center, Seoul, 4Department of Surgery, University of Ulsan College of Medicine, Seoul, South Korea Purpose: The aim of this study is to determine the utility of breast cancer health states using the standard gamble (SG and visual analog scale (VAS methods in the Korean general population.Materials and methods: Eight hypothetical breast cancer health states were developed based on patient education material and previous publications. Data from 509 individuals from the Korean general population were used to evaluate breast cancer health states using the VAS and the SG methods, which were obtained via computer-assisted personal interviews. Mean utility values were calculated for each human papillomavirus (HPV-related health state.Results: The rank of health states was identical between two valuation methods. SG values were higher than VAS values in all health states. The utility values derived from SG were 0.801 (noninvasive breast cancer with mastectomy and followed by reconstruction, 0.790 (noninvasive breast cancer with mastectomy only, 0.779 (noninvasive breast cancer with breast-conserving surgery and radiation therapy, 0.731 (invasive breast cancer with surgery, radiation therapy, and/or chemotherapy, 0.610 (locally advanced breast cancer with radical mastectomy with radiation therapy, 0.587 (inoperable locally advanced breast cancer, 0.496 (loco-regional recurrent breast cancer, and 0.352 (metastatic breast cancer.Conclusion: Our findings might be useful for economic evaluation of breast cancer screening and interventions in general populations. Keywords: breast neoplasm, Korea, quality-adjusted life years, quality of life

  10. Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks.

    Science.gov (United States)

    Cao, Weifang; Cao, Xinyi; Hou, Changyue; Li, Ting; Cheng, Yan; Jiang, Lijuan; Luo, Cheng; Li, Chunbo; Yao, Dezhong

    2016-01-01

    Neuroimaging studies have documented that aging can disrupt certain higher cognitive systems such as the default mode network (DMN), the salience network and the central executive network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a 1-year longitudinal design to explore the cognitive training effect on three higher cognitive networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a 3-months period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging scanning at baseline and at 1 year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three networks. Compared with the baseline, we observed maintained or increased FC within all three networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the aging-related dysfunction of higher cognitive networks.

  11. Improving the accuracy of estimation of eutrophication state index ...

    African Journals Online (AJOL)

    Trophic Level Index (TLI) is oen used to assess the general eutrophication state of inland lakes in water science, technology, and engineering. In this paper, a data-driven inland-lake eutrophication assessment method was proposed by using an articial neural network (ANN) to build relationships from remote sensing data ...

  12. Estimated prevalence of compulsive buying behavior in the United States.

    Science.gov (United States)

    Koran, Lorrin M; Faber, Ronald J; Aboujaoude, Elias; Large, Michael D; Serpe, Richard T

    2006-10-01

    Compulsive buying (uncontrolled urges to buy, with resulting significant adverse consequences) has been estimated to affect from 1.8% to 16% of the adult U.S. population. To the authors' knowledge, no study has used a large general population sample to estimate its prevalence. The authors conducted a random sample, national household telephone survey in the spring and summer of 2004 and interviewed 2,513 adults. The interviews addressed buying attitudes and behaviors, their consequences, and the respondents' financial and demographic data. The authors used a clinically validated screening instrument, the Compulsive Buying Scale, to classify respondents as either compulsive buyers or not. The rate of response was 56.3%, which compares favorably with rates in federal national health surveys. The cooperation rate was 97.6%. Respondents included a higher percentage of women and people ages 55 and older than the U.S. adult population. The estimated point prevalence of compulsive buying among respondents was 5.8% (by gender: 6.0% for women, 5.5% for men). The gender-adjusted prevalence rate was 5.8%. Compared with other respondents, compulsive buyers were younger, and a greater proportion reported incomes under 50,000 US dollars. They exhibited more maladaptive responses on most consumer behavior measures and were more than four times less likely to pay off credit card balances in full. A study using clinically valid interviews is needed to evaluate these results. The emotional and functional toll of compulsive buying and the frequency of comorbid psychiatric disorders suggests that studies of treatments and social interventions are warranted.

  13. 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.

  14. State Estimation in Fermentation of Lignocellulosic Ethanol. Focus on the Use of pH Measurements

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Gernaey, Krist; Huusom, Jakob Kjøbsted

    2015-01-01

    The application of the continuous-discrete extended Kalman filter (CD-EKF) as a powerful tool for state estimation in biochemical systems is assessed here. Using a fermentation process for ethanol production as a case study, the CD-EKF can effectively estimate the model states even when highly non...

  15. Addressing Single and Multiple Bad Data in the Modern PMU-based Power System State Estimation

    DEFF Research Database (Denmark)

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

    2017-01-01

    utilization in state estimation can detect and identify single and multiple bad data in redundant and critical measurements. To validate simulations, IEEE 30 bus system are implemented in PowerFactory and Matlab is used to solve proposed state estimation using postprocessing of PMUs and mixed methods. Bad...

  16. 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

  17. Joint state and parameter estimation for a class of cascade systems: Application to a hemodynamic model

    KAUST Repository

    Zayane, Chadia

    2014-06-01

    In this paper, we address a special case of state and parameter estimation, where the system can be put on a cascade form allowing to estimate the state components and the set of unknown parameters separately. Inspired by the nonlinear Balloon hemodynamic model for functional Magnetic Resonance Imaging problem, we propose a hierarchical approach. The system is divided into two subsystems in cascade. The state and input are first estimated from a noisy measured signal using an adaptive observer. The obtained input is then used to estimate the parameters of a linear system using the modulating functions method. Some numerical results are presented to illustrate the efficiency of the proposed method.

  18. Clinical Trials of Blood Pressure Lowering and Antihypertensive Medication: is Cognitive Measurement State-Of-The-Art?

    Science.gov (United States)

    Elias, Merrill F; Torres, Rachael V; Davey, Adam

    2018-02-22

    Randomized controlled trials of blood pressure (BP) lowering and antihypertensive medication use on cognitive outcomes have often been disappointing, reporting mixed findings and small effect sizes. We evaluate the extent to which cognitive assessment protocols used in these trials approach state-of-the-art. Overall, we find that a primary focus on cognition and the systematic selection of cognitive outcomes across trials take a backseat to other trial goals. Twelve trials investigating change in cognitive functioning were examined and none met criteria for state-of-the-art assessment, including use of at least 4 tests indexing 2 cognitive domains. Four trials investigating incident dementia were also examined. Each trial used state-of-the-art diagnostic criteria to assess dementia, although follow-up periods were relatively short, with only 2 trials lasting for at least 3 years. Weaknesses in each trial may act to obscure or weaken the positive effects of BP lowering on cognitive functioning. Improving trial designs in terms of cognitive outcomes selected and length of follow-up periods employed could lead to more promising findings. We offer logical steps to achieve state-of-the-art assessment protocols, with examples, in hopes of improving future trials.

  19. An integrated theory of prospective time interval estimation : The role of cognition, attention, and learning

    NARCIS (Netherlands)

    Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John

    A theory of prospective time perception is introduced and incorporated as a module in an integrated theory of cognition, thereby extending existing theories and allowing predictions about attention and learning. First, a time perception module is established by fitting existing datasets (interval

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

    Directory of Open Access Journals (Sweden)

    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.

  1. 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.

  2. Dynamic systems models new methods of parameter and state estimation

    CERN Document Server

    2016-01-01

    This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...

  3. Estimating Rn-induced lung cancer in the United States

    International Nuclear Information System (INIS)

    Lubin, J.H.; Boice, J.D. Jr.

    1989-01-01

    The proportion of lung cancer deaths attributable to Rn among residents of single-family homes in the U.S. (approximately 70% of the housing stock) is estimated using the log-normal distribution of Rn concentrations proposed by Nero et al. (1986) and the risk model developed by the National Academy of Sciences' BEIR IV Committee. The risk model, together with the exposure distribution, predicts that approximately 14% of lung cancer deaths among such residents (about 13,300 deaths per year, or 10% of all U.S. lung cancer deaths) may be due to indoor Rn exposure. The 95% confidence interval is 7%-25%, or approximately 6600 to 24,000 lung cancer deaths. These estimated attributable risks due to Rn are similar for males and females and for smokers and nonsmokers, but higher baseline risks of lung cancer result in much larger absolute numbers of Rn-attributable cancers among males (approximately 9000) and among smokers (approximately 11,000). Because of the apparent skewness of the exposure distribution, most of the contribution to the attributable risks arises from exposure rates below 148 Bq m-3 (4 pCi L-1), i.e., below the EPA action level. As a result, if all exposure rates that exceed 148 Bq m-3 (approximately 8% of homes) were eliminated, the models predict that the total annual lung cancer burden in the U.S. would drop by 4-5%, or by about 3800 lung cancer deaths, in contrast to a maximum reduction of 14% if all indoor Rn exposure above the 1st percentile were eliminated

  4. 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.

  5. Validity of the mini-mental state examination and the montreal cognitive assessment in the prediction of driving test outcome.

    Science.gov (United States)

    Hollis, Ann M; Duncanson, Haley; Kapust, Lissa R; Xi, Patricia M; O'Connor, Margaret G

    2015-05-01

    To evaluate the effectiveness of two cognitive screening measures, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), in predicting driving test outcome for individuals with and without cognitive impairment. Retrospective cohort study. A clinical driving evaluation program at a teaching hospital in the United States. Adult drivers who underwent assessment with the MMSE and MoCA as part of a comprehensive driving evaluation between 2010 and 2014 (N=92). MMSE and MoCA total scores were independent variables. The outcome measure was performance on a standardized road test. A preestablished diagnosis of cognitive impairment enhanced the validity of cognitive screening measures in the identification of at-risk drivers. In individuals with cognitive impairment there was a significant relationship between MoCA score and on-road outcome. Specifically, an individual was 1.36 times as likely to fail the road test with each 1-point decrease in MoCA score. No such relationship was detected in those without a diagnosis of cognitive impairment. For individuals who have not been diagnosed with cognitive impairment, neither the MMSE nor the MoCA can be reliably used as an indicator of driving risk, but for individuals with a preestablished diagnosis of cognitive impairment, the MoCA is a useful tool in this regard. A score on the MoCA of 18 or less should raise concerns about driving safety. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

  6. Bridging consciousness and cognition in memory and perception: evidence for both state and strength processes.

    Science.gov (United States)

    Aly, Mariam; Yonelinas, Andrew P

    2012-01-01

    Subjective experience indicates that mental states are discrete, in the sense that memories and perceptions readily come to mind in some cases, but are entirely unavailable to awareness in others. However, a long history of psychophysical research has indicated that the discrete nature of mental states is largely epiphenomenal and that mental processes vary continuously in strength. We used a novel combination of behavioral methodologies to examine the processes underlying perception of complex images: (1) analysis of receiver operating characteristics (ROCs), (2) a modification of the change-detection flicker paradigm, and (3) subjective reports of conscious experience. These methods yielded converging results showing that perceptual judgments reflect the combined, yet functionally independent, contributions of two processes available to conscious experience: a state process of conscious perception and a strength process of knowing; processes that correspond to recollection and familiarity in long-term memory. In addition, insights from the perception experiments led to the discovery of a new recollection phenomenon in a long-term memory change detection paradigm. The apparent incompatibility between subjective experience and theories of cognition can be understood within a unified state-strength framework that links consciousness to cognition across the domains of perception and memory.

  7. Conversion between mini-mental state examination, montreal cognitive assessment, and dementia rating scale-2 scores in Parkinson's disease.

    Science.gov (United States)

    van Steenoven, Inger; Aarsland, Dag; Hurtig, Howard; Chen-Plotkin, Alice; Duda, John E; Rick, Jacqueline; Chahine, Lama M; Dahodwala, Nabila; Trojanowski, John Q; Roalf, David R; Moberg, Paul J; Weintraub, Daniel

    2014-12-01

    Cognitive impairment is one of the earliest, most common, and most disabling non-motor symptoms in Parkinson's disease (PD). Thus, routine screening of global cognitive abilities is important for the optimal management of PD patients. Few global cognitive screening instruments have been developed for or validated in PD patients. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Dementia Rating Scale-2 (DRS-2) have been used extensively for cognitive screening in both clinical and research settings. Determining how to convert the scores between instruments would facilitate the longitudinal assessment of cognition in clinical settings and the comparison and synthesis of cognitive data in multicenter and longitudinal cohort studies. The primary aim of this study was to apply a simple and reliable algorithm for the conversion of MoCA to MMSE scores in PD patients. A secondary aim was to apply this algorithm for the conversion of DRS-2 to both MMSE and MoCA scores. The cognitive performance of a convenience sample of 360 patients with idiopathic PD was assessed by at least two of these cognitive screening instruments. We then developed conversion scores between the MMSE, MoCA, and DRS-2 using equipercentile equating and log-linear smoothing. The conversion score tables reported here enable direct and easy comparison of three routinely used cognitive screening assessments in PD patients. © 2014 International Parkinson and Movement Disorder Society.

  8. White matter microstructural damage in small vessel disease is associated with Montreal cognitive assessment but not with mini mental state examination performances: vascular mild cognitive impairment Tuscany study.

    Science.gov (United States)

    Pasi, Marco; Salvadori, Emilia; Poggesi, Anna; Ciolli, Laura; Del Bene, Alessandra; Marini, Sandro; Nannucci, Serena; Pescini, Francesca; Valenti, Raffaella; Ginestroni, Andrea; Toschi, Nicola; Diciotti, Stefano; Mascalchi, Mario; Inzitari, Domenico; Pantoni, Leonardo

    2015-01-01

    Montreal Cognitive Assessment (MoCA) has been proposed as a screening tool in vascular cognitive impairment. Diffusion tensor imaging is sensitive to white matter microstructural damage. We investigated if diffusion tensor imaging-derived indices are more strongly associated with performances on MoCA or on the widely used mini mental state examination in patients with mild cognitive impairment and small vessel disease. Mild cognitive impairment patients with moderate/severe degrees of white matter hyperintensities on MRI were enrolled. Lacunar infarcts, cortical atrophy, medial temporal lobe atrophy and median values of mean diffusivity and fractional anisotropy of the cerebral white matter were studied and correlated with cognitive tests performances. Seventy-six patients (mean age 75.1±6.8 years, mean years of education 8.0±4.3) were assessed. In univariate analyses, a significant association of both MoCA and mini mental state examination scores with age, education, cortical atrophy, and medial temporal lobe atrophy was found, whereas mean diffusivity and fractional anisotropy were associated with MoCA. In partial correlation analyses, adjusting for all demographic and neuroimaging variables, both mean diffusivity and fractional anisotropy were associated only with MoCA (mean diffusivity: r= -0.275, P=0.023; fractional anisotropy: r=0.246, P=0.043). In patients with mild cognitive impairment and small vessel disease, diffusion tensor imaging-measured white matter microstructural damage is more related to MoCA than mini mental state examination performances. MoCA is suited for the cognitive screening of patients with small vessel disease. © 2014 American Heart Association, Inc.

  9. Evaluation and Comparison of Cognitive State and Depression in Elderly Admitted in Sanitarium with Elderly Sited in Personal Home

    OpenAIRE

    Mohamad-baghere Sohrabi; Pone Zolfaghari; Farzane Mahdizade; Seyd-Mohammad Aghayan; Mojtaba Ghasemian- Aghmashhadi; Zahra Shariati; Ahmad Khosravi

    2008-01-01

    Introduction: In this study cognitive state and geriatric depression in elderly living in sanatorium and personal home were evaluated. Methods: The present study was conducted on 46 aged subjects living in sanitarium and 90 aged subjects staying in personal homes. Mini mental status examination (MMSE) and geriatric depression scale (GDS) questionnaires were completed according to the standard examination. Results: As for the cognitive state of the aged living in sanitarium, 13 cases (28.3%) s...

  10. The resting state fMRI study of patients with Parkinson's disease associated with cognitive dysfunction

    International Nuclear Information System (INIS)

    Feng Jieying; Huang Biao

    2013-01-01

    Parkinson's disease (PD) is the most common neurodegenerative cause of Parkinsonism, but the high morbidity of PD accompanied cognitive dysfunction hasn't drawn enough attention by the clinicians. With the rapid development of the resting state functional MRI (fMRI) technique, the cause of PD patients with cognitive dysfunction may be associated with the damage of functional connectivity of the motor networks and the cognitive networks. The relationship between neuropathologic mechanism of PD patients with cognitive dysfunction and impaired cognitive circuits will be disclosed by building the changes of brain topological structure in patients. The resting state fMRI study can provide the rationale for prevention, diagnosis and treatment of PD. (authors)

  11. State Estimation for Robots with Complementary Redundant Sensors

    Directory of Open Access Journals (Sweden)

    Daniele Carnevale

    2015-10-01

    Full Text Available In this paper, robots equipped with two complementary typologies of redundant sensors are considered: one typology provides sharp measures of some geometrical entity related to the robot pose (e.g., distance or angle but is not univocally associated with this quantity; the other typology is univocal but is characterized by a low level of precision. A technique is proposed to properly combine these two kinds of measurement both in a stochastic and in a deterministic context. This framework may occur in robotics, for example, when the distance from a known landmark is detected by two different sensors, one based on the signal strength or time of flight of the signal, while the other one measures the phase-shift of the signal, which has a sharp but periodical dependence on the robot-landmark distance. In the stochastic case, an effective solution is a two-stage extended Kalman filter (EKF which exploits the precise periodic signal only when the estimate of the robot position is sufficiently precise. In the deterministic setting, an approach based on a switching hybrid observer is proposed, and results are analyzed via simulation examples.

  12. The reliability of assigning individuals to cognitive states using the Mini Mental-State Examination: a population-based prospective cohort study.

    Science.gov (United States)

    Marioni, Riccardo E; Chatfield, Mark; Brayne, Carol; Matthews, Fiona E

    2011-09-06

    Previous investigations of test re-test reliability of the Mini-Mental State Examination (MMSE) have used correlations and statistics such as Cronbach's α to assess consistency. In practice, the MMSE is usually used to group individuals into cognitive states. The reliability of this grouping (state based approach) has not been fully explored. MMSE data were collected on a subset of 2,275 older participants (≥ 65 years) from the population-based Medical Research Council Cognitive Function and Ageing Study. Two measurements taken approximately two months apart were used to investigate three state-based categorisations. Descriptive statistics were used to determine how many people remained in the same cognitive group or went up or down groups. Weighted logistic regression was used to identify predictive characteristics of those who moved group. The proportion of people who remained in the same MMSE group at screen and follow-up assessment ranged from 58% to 78%. The proportion of individuals who went up one or more groups was roughly equal to the proportion that went down one or more groups; most of the change occurred when measurements were close to the cut-points. There was no consistently significant predictor for changing cognitive group. A state-based approach to analysing the reliability of the MMSE provided similar results to correlation analyses. State-based models of cognitive change or individual trajectory models using raw scores need multiple waves to help overcome natural variation in MMSE scores and to help identify true cognitive change.

  13. Clinical relevance of specific cognitive complaints in determining Mild Cognitive Impairment from Cognitively Normal States in a study of Healthy Elderly Controls

    Directory of Open Access Journals (Sweden)

    Marina Avila Villanueva

    2016-10-01

    Full Text Available Introduction: Subjective memory complaints in the elderly have been suggested as an early sign of dementia. This study aims at investigating whether specific cognitive complaints are more useful than others to discriminate Mild Cognitive Impairment (MCI by examining the dimensional structure of the Everyday Memory Questionnaire (EMQ.Material and Methods: A sample of community-dwelling elderly individuals was recruited (766 controls and 78 MCI. The Everyday Memory Questionnaire (EMQ was administered to measure self-perception of cognitive complaints. All participants also underwent a comprehensive clinical and neuropsychological battery. Combined exploratory factor analysis and item response theory were performed to identify the underlying structure of the EMQ. Furthermore, logistic regression analyses were conducted to study whether single cognitive complaints were able to predict MCI.Results: A suitable five-factor solution was found. Each factor focused on a different cognitive domain. Interestingly, just three of them, namely forgetfulness of immediate information, executive functions and prospective memory proved to be effective in distinguishing between cognitively healthy individuals and MCI. Based on these results we propose a shortened EMQ version comprising 10 items (EMQ-10.Discussion: Not all cognitive complaints have the same clinical relevance. Only subjective complaints on specific cognitive domains are able to discriminate MCI. We encourage clinicians to the EMQ-10 as a useful tool to quantify and monitor the progression of individuals who report cognitive complaints.

  14. 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...

  15. Lagged Associations of Metropolitan Statistical Area- and State-Level Income Inequality with Cognitive Function: The Health and Retirement Study.

    Science.gov (United States)

    Kim, Daniel; Griffin, Beth Ann; Kabeto, Mohammed; Escarce, José; Langa, Kenneth M; Shih, Regina A

    2016-01-01

    Much variation in individual-level cognitive function in late life remains unexplained, with little exploration of area-level/contextual factors to date. Income inequality is a contextual factor that may plausibly influence cognitive function. In a nationally-representative cohort of older Americans from the Health and Retirement Study, we examined state- and metropolitan statistical area (MSA)-level income inequality as predictors of individual-level cognitive function measured by the 27-point Telephone Interview for Cognitive Status (TICS-m) scale. We modeled latency periods of 8-20 years, and controlled for state-/metropolitan statistical area (MSA)-level and individual-level factors. Higher MSA-level income inequality predicted lower cognitive function 16-18 years later. Using a 16-year lag, living in a MSA in the highest income inequality quartile predicted a 0.9-point lower TICS-m score (β = -0.86; 95% CI = -1.41, -0.31), roughly equivalent to the magnitude associated with five years of aging. We observed no associations for state-level income inequality. The findings were robust to sensitivity analyses using propensity score methods. Among older Americans, MSA-level income inequality appears to influence cognitive function nearly two decades later. Policies reducing income inequality levels within cities may help address the growing burden of declining cognitive function among older populations within the United States.

  16. 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....

  17. 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

  18. Monitoring hydraulic fractures: state estimation using an extended Kalman filter

    International Nuclear Information System (INIS)

    Rochinha, Fernando Alves; Peirce, Anthony

    2010-01-01

    There is considerable interest in using remote elastostatic deformations to identify the evolving geometry of underground fractures that are forced to propagate by the injection of high pressure viscous fluids. These so-called hydraulic fractures are used to increase the permeability in oil and gas reservoirs as well as to pre-fracture ore-bodies for enhanced mineral extraction. The undesirable intrusion of these hydraulic fractures into environmentally sensitive areas or into regions in mines which might pose safety hazards has stimulated the search for techniques to enable the evolving hydraulic fracture geometries to be monitored. Previous approaches to this problem have involved the inversion of the elastostatic data at isolated time steps in the time series provided by tiltmeter measurements of the displacement gradient field at selected points in the elastic medium. At each time step, parameters in simple static models of the fracture (e.g. a single displacement discontinuity) are identified. The approach adopted in this paper is not to regard the sequence of sampled elastostatic data as independent, but rather to treat the data as linked by the coupled elastic-lubrication equations that govern the propagation of the evolving hydraulic fracture. We combine the Extended Kalman Filter (EKF) with features of a recently developed implicit numerical scheme to solve the coupled free boundary problem in order to form a novel algorithm to identify the evolving fracture geometry. Numerical experiments demonstrate that, despite excluding significant physical processes in the forward numerical model, the EKF-numerical algorithm is able to compensate for the un-modeled dynamics by using the information fed back from tiltmeter data. Indeed the proposed algorithm is able to provide reasonably faithful estimates of the fracture geometry, which are shown to converge to the actual hydraulic fracture geometry as the number of tiltmeters is increased. Since the location of

  19. Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

    Science.gov (United States)

    Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

    2015-12-01

    The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

  20. Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

    Science.gov (United States)

    Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

    2014-11-01

    Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

  1. Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning.

    Science.gov (United States)

    Hearne, Luke J; Cocchi, Luca; Zalesky, Andrew; Mattingley, Jason B

    2017-08-30

    Our capacity for higher cognitive reasoning has a measurable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic "resting-state" network architecture. Here we combined resting-state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting-state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting-state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 × 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting-state and null-task demand conditions were associated with more segregated brain-network topology, whereas increases in reasoning complexity resulted in merging of resting-state modules. Further increments in task complexity did not change the established modular architecture, but affected selective patterns of connectivity between frontoparietal, subcortical, cingulo-opercular, and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity. SIGNIFICANCE STATEMENT Humans have clear limits in their ability to solve complex reasoning problems. It is thought that

  2. Atypical modulation of distant functional connectivity by cognitive state in children with Autism Spectrum Disorders

    Directory of Open Access Journals (Sweden)

    Xiaozhen eYou

    2013-08-01

    Full Text Available We examined whether modulation of functional connectivity by cognitive state differed between pre-adolescent children with Autism Spectrum Disorders (ASD and age and IQ-matched control children. Children underwent functional magnetic resonance imaging (fMRI during two states, a resting state followed by a sustained attention task. A voxel-wise method was used to characterize functional connectivity at two levels, local (within a voxel’s 14 mm neighborhood and distant (outside of the voxel’s 14 mm neighborhood to the rest of the brain and regions exhibiting Group X State interaction were identified for both types of connectivity maps. Distant functional connectivity of regions in the left frontal lobe (dorsolateral [BA 11, 10]; supplementary motor area extending into dorsal anterior cingulate [BA 32/8]; and premotor [BA 6, 8, 9], right parietal lobe (paracentral lobule [BA 6 ]; angular gyrus [BA 39/40], and left posterior middle temporal cortex (BA 19/39 showed a Group X State interaction such that relative to the resting state, connectivity reduced (i.e., became focal in control children but increased (i.e., became diffuse in ASD children during the task state. Higher state-related increase in distant connectivity of left frontal and right angular gyrus predicted worse inattention in ASD children. Two graph theory measures (global efficiency and modularity were also sensitive to Group X State differences, with the magnitude of state-related change predicting inattention in the ASD children. Our results indicate that as ASD children transition from an unconstrained to a sustained attentional state, functional connectivity of frontal and parietal regions with the rest of the brain becomes more widespread in a manner that may be maladaptive as it was associated with attention problems in everyday life.

  3. Toward the Computational Representation of Individual Cultural, Cognitive, and Physiological State: The Sensor Shooter Simulation; TOPICAL

    International Nuclear Information System (INIS)

    RAYBOURN, ELAINE M.; FORSYTHE, JAMES C.

    2001-01-01

    This report documents an exploratory FY 00 LDRD project that sought to demonstrate the first steps toward a realistic computational representation of the variability encountered in individual human behavior. Realism, as conceptualized in this project, required that the human representation address the underlying psychological, cultural, physiological, and environmental stressors. The present report outlines the researchers' approach to representing cognitive, cultural, and physiological variability of an individual in an ambiguous situation while faced with a high-consequence decision that would greatly impact subsequent events. The present project was framed around a sensor-shooter scenario as a soldier interacts with an unexpected target (two young Iraqi girls). A software model of the ''Sensor Shooter'' scenario from Desert Storm was developed in which the framework consisted of a computational instantiation of Recognition Primed Decision Making in the context of a Naturalistic Decision Making model[1]. Recognition Primed Decision Making was augmented with an underlying foundation based on our current understanding of human neurophysiology and its relationship to human cognitive processes. While the Gulf War scenario that constitutes the framework for the Sensor Shooter prototype is highly specific, the human decision architecture and the subsequent simulation are applicable to other problems similar in concept, intensity, and degree of uncertainty. The goal was to provide initial steps toward a computational representation of human variability in cultural, cognitive, and physiological state in order to attain a better understanding of the full depth of human decision-making processes in the context of ambiguity, novelty, and heightened arousal

  4. Resting state glucose utilization and the CERAD cognitive battery in patients with Alzheimer's disease.

    Science.gov (United States)

    Teipel, S J; Willoch, F; Ishii, K; Bürger, K; Drzezga, A; Engel, R; Bartenstein, P; Möller, H-J; Schwaiger, M; Hampel, H

    2006-05-01

    The present study examined the cortical functional representation of neuropsychological domains in Alzheimer's disease (AD) using positron emission tomography (PET) and the neuropsychological assessment battery of the Consortium to Establish a Registry of Alzheimer's Disease (CERAD). Thirty patients with clinical probable AD and 10 elderly healthy controls underwent (18)FDG brain PET imaging during a resting state. Correlations between metabolic values and cognitive measures were determined using a region of interest analysis with NEUROSTAT (University of Michigan, USA) and a voxel-based analysis with SPM96 (Wellcome Department, London, UK). Specific correlations were seen between measures of episodic memory, verbal fluency and naming and left hemispheric temporal and prefrontal metabolism. Drawing was correlated with metabolism in left prefrontal and left inferior parietal regions. The presented data support the use of metabolic-cognitive correlations to demonstrate the neuronal substrates of cognitive impairment in AD. Subtests of the CERAD battery give a good representation of left, but not of right hemisphere function in AD.

  5. Relationship between areas of cognitive functioning on the Mini-Mental State Examination and crash risk.

    Science.gov (United States)

    Huisingh, Carrie; Wadley, Virginia G; McGwin, Gerald; Owsley, Cynthia

    2018-03-01

    Previous studies have suggested that the pattern of cognitive impairment in crash involved older drivers is different from non-crash involved older drivers. This study assessed the relationship between seven areas of cognitive functioning (orientation to time, orientation to place, registration, attention and calculation, recall, language, and visual construction) on the Mini-Mental State Examination (MMSE) collected at baseline and rates of future crash involvement in a prospective population-based sample of older drivers. Motor vehicle collision involvement was obtained from the Alabama Department of Public Safety. Poisson regression was used to calculate crude and adjusted rate ratios (RR). Older drivers having difficulties in place orientation were more than 6 times (95% CI 1.90-19.86) more likely to be involved in a future crash (adjusted RR = 6.14, 95% confidence interval (CI) 1.90-19.86) and at-fault crash (adjusted RR=6.39, 95% CI 1.51-27.10). Impairment in the other cognitive areas was not associated with higher rates of crash or at-fault crash involvement. The findings were validated in an independent sample of high-risk older drivers and a similar pattern of results was observed. Spatial orientation impairment can help identify older drivers who are more likely to crash in the future.

  6. [Beneficial effect of preferred music on cognitive functions in minimally conscious state patients].

    Science.gov (United States)

    Verger, J; Ruiz, S; Tillmann, B; Ben Romdhane, M; De Quelen, M; Castro, M; Tell, L; Luauté, J; Perrin, F

    2014-11-01

    Several studies have shown that music can boost cognitive functions in normal and brain-damaged subjects. A few studies have suggested a beneficial effect of music in patients with a disorder of consciousness but it is difficult to conclude since they did not use quantified measures and a control condition/group. The aim of the present study was to compare the effect of music to that of a continuous sound on the relational behavior of patients in a minimally conscious state (MCS). Behavioral responses of six MCS patients were evaluated using items from the Coma Recovery Scale-Revised. Weekly evaluation sessions were carried out, over four weeks, under two conditions: following the presentation of either the patient's preferred music, or following a continuous sound (control condition). Qualitative and quantitative analyses showed that twelve of the eighteen sessions (66.6%) showed a better result for the music condition than for the control condition. This new protocol suggests that preferred music has a beneficial effect on the cognitive abilities of MCS patients. The results further suggest that cerebral plasticity may be enhanced in autobiographical (emotional and familiar) contexts. These findings should now be further extended with an increased number of patients to further validate the hypothesis of the beneficial effect of music on cognitive recovery. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  7. Montreal Cognitive Assessment Performance in Patients with Parkinson’s Disease with “Normal” Global Cognition According to Mini-Mental State Examination Score

    Science.gov (United States)

    Nazem, Sarra; Siderowf, Andrew D.; Duda, John E.; Have, Tom Ten; Colcher, Amy; Horn, Stacy S.; Moberg, Paul J.; Wilkinson, Jayne R.; Hurtig, Howard I.; Stern, Matthew B.; Weintraub, Daniel

    2009-01-01

    OBJECTIVES To examine Montreal Cognitive Assessment (MoCA) performance in patients with Parkinson’s disease (PD) with “normal” global cognition according to Mini-Mental State Examination (MMSE) score. DESIGN A cross-sectional comparison of the MoCA and the MMSE. SETTING Two movement disorders centers at the University of Pennsylvania and the Philadelphia Veterans Affairs Medical Center. PARTICIPANTS A convenience sample of 131 patients with idiopathic PD who were screened for cognitive and psychiatric complications. MEASUREMENTS Subjects were administered the MoCA and MMSE, and only subjects defined as having a normal age- and education-adjusted MMSE score were included in the analyses (N = 100). As previously recommended in patients without PD, a MoCA score less than 26 was used to indicate the presence of at least mild cognitive impairment (MCI). RESULTS Mean MMSE and MoCA scores ± standard deviation were 28.8 ± 1.1 and 24.9 ± 3.1, respectively. More than half (52.0%) of subjects with normal MMSE scores had cognitive impairment according to their MoCA score. Impairments were seen in numerous cognitive domains, including memory, visuospatial and executive abilities, attention, and language. Predictors of cognitive impairment on the MoCA using univariate analyses were male sex, older age, lower educational level, and greater disease severity; older age was the only predictor in a multivariate model. CONCLUSION Approximately half of patients with PD with a normal MMSE score have cognitive impairment based on the recommended MoCA cutoff score. These results suggest that MCI is common in PD and that the MoCA is a more sensitive instrument than the MMSE for its detection. PMID:19170786

  8. 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

  9. Parameter and state estimation of experimental chaotic systems using synchronization

    Science.gov (United States)

    Quinn, John C.; Bryant, Paul H.; Creveling, Daniel R.; Klein, Sallee R.; Abarbanel, Henry D. I.

    2009-07-01

    We examine the use of synchronization as a mechanism for extracting parameter and state information from experimental systems. We focus on important aspects of this problem that have received little attention previously and we explore them using experiments and simulations with the chaotic Colpitts oscillator as an example system. We explore the impact of model imperfection on the ability to extract valid information from an experimental system. We compare two optimization methods: an initial value method and a constrained method. Each of these involves coupling the model equations to the experimental data in order to regularize the chaotic motions on the synchronization manifold. We explore both time-dependent and time-independent coupling and discuss the use of periodic impulse coupling. We also examine both optimized and fixed (or manually adjusted) coupling. For the case of an optimized time-dependent coupling function u(t) we find a robust structure which includes sharp peaks and intervals where it is zero. This structure shows a strong correlation with the location in phase space and appears to depend on noise, imperfections of the model, and the Lyapunov direction vectors. For time-independent coupling we find the counterintuitive result that often the optimal rms error in fitting the model to the data initially increases with coupling strength. Comparison of this result with that obtained using simulated data may provide one measure of model imperfection. The constrained method with time-dependent coupling appears to have benefits in synchronizing long data sets with minimal impact, while the initial value method with time-independent coupling tends to be substantially faster, more flexible, and easier to use. We also describe a method of coupling which is useful for sparse experimental data sets. Our use of the Colpitts oscillator allows us to explore in detail the case of a system with one positive Lyapunov exponent. The methods we explored are easily

  10. State of Charge and State of Health Estimation of AGM VRLA Batteries by Employing a Dual Extended Kalman Filter and an ARX Model for Online Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Ngoc-Tham Tran

    2017-01-01

    Full Text Available State of charge (SOC and state of health (SOH are key issues for the application of batteries, especially the absorbent glass mat valve regulated lead-acid (AGM VRLA type batteries used in the idle stop start systems (ISSs that are popularly integrated into conventional engine-based vehicles. This is due to the fact that SOC and SOH estimation accuracy is crucial for optimizing battery energy utilization, ensuring safety and extending battery life cycles. The dual extended Kalman filter (DEKF, which provides an elegant and powerful solution, is widely applied in SOC and SOH estimation based on a battery parameter model. However, the battery parameters are strongly dependent on operation conditions such as the SOC, current rate and temperature. In addition, battery parameters change significantly over the life cycle of a battery. As a result, many experimental pretests investigating the effects of the internal and external conditions of a battery on its parameters are required, since the accuracy of state estimation depends on the quality of the information regarding battery parameter changes. In this paper, a novel method for SOC and SOH estimation that combines a DEKF algorithm, which considers hysteresis and diffusion effects, and an auto regressive exogenous (ARX model for online parameters estimation is proposed. The DEKF provides precise information concerning the battery open circuit voltage (OCV to the ARX model. Meanwhile, the ARX model continues monitoring parameter variations and supplies information on them to the DEKF. In this way, the estimation accuracy can be maintained despite the changing parameters of a battery. Moreover, online parameter estimation from the ARX model can save the time and effort used for parameter pretests. The validation of the proposed algorithm is given by simulation and experimental results.

  11. Using the Folstein Mini Mental State Exam (MMSE) to explore methodological issues in cognitive aging research.

    Science.gov (United States)

    Monroe, Todd; Carter, Michael

    2012-09-01

    Cognitive scales are used frequently in geriatric research and practice. These instruments are constructed with underlying assumptions that are a part of their validation process. A common measurement scale used in older adults is the Folstein Mini Mental State Exam (MMSE). The MMSE was designed to screen for cognitive impairment and is used often in geriatric research. This paper has three aims. Aim one was to explore four potential threats to validity in the use of the MMSE: (1) administering the exam without meeting the underlying assumptions, (2) not reporting that the underlying assumptions were assessed prior to test administration, (3) use of variable and inconsistent cut-off scores for the determination of presence of cognitive impairment, and (4) failure to adjust the scores based on the demographic characteristics of the tested subject. Aim two was to conduct a literature search to determine if the assumptions of (1) education level assessment, (2) sensory assessment, and (3) language fluency were being met and clearly reported in published research using the MMSE. Aim three was to provide recommendations to minimalize threats to validity in research studies that use cognitive scales, such as the MMSE. We found inconsistencies in published work in reporting whether or not subjects meet the assumptions that underlie a reliable and valid MMSE score. These inconsistencies can pose threats to the reliability of exam results. Fourteen of the 50 studies reviewed reported inclusion of all three of these assumptions. Inconsistencies in reporting the inclusion of the underlying assumptions for a reliable score could mean that subjects were not appropriate to be tested by use of the MMSE or that an appropriate test administration of the MMSE was not clearly reported. Thus, the research literature could have threats to both validity and reliability based on misuse of or improper reported use of the MMSE. Six recommendations are provided to minimalize these threats

  12. Using the Oxford Cognitive Screen to Detect Cognitive Impairment in Stroke Patients: A Comparison with the Mini-Mental State Examination

    Directory of Open Access Journals (Sweden)

    Mauro Mancuso

    2018-02-01

    Full Text Available BackgroundThe Oxford Cognitive Screen (OCS was recently developed with the aim of describing the cognitive deficits after stroke. The scale consists of 10 tasks encompassing five cognitive domains: attention and executive function, language, memory, number processing, and praxis. OCS was devised to be inclusive and un-confounded by aphasia and neglect. As such, it may have a greater potential to be informative on stroke cognitive deficits of widely used instruments, such as the Mini-Mental State Examination (MMSE or the Montreal Cognitive Assessment, which were originally devised for demented patients.ObjectiveThe present study compared the OCS with the MMSE with regards to their ability to detect cognitive impairments post-stroke. We further aimed to examine performance on the OCS as a function of subtypes of cerebral infarction and clinical severity.Methods325 first stroke patients were consecutively enrolled in the study over a 9-month period. The OCS and MMSE, as well as the Bamford classification and NIHSS, were given according to standard procedures.ResultsAbout a third of patients (35.3% had a performance lower than the cutoff (<22 on the MMSE, whereas 91.6% were impaired in at least one OCS domain, indicating higher incidences of impairment for the OCS. More than 80% of patients showed an impairment in two or more cognitive domains of the OCS. Using the MMSE as a standard of clinical practice, the comparative sensitivity of OCS was 100%. Out of the 208 patients with normal MMSE performance 180 showed impaired performance in at least one domain of the OCS. The discrepancy between OCS and MMSE was particularly strong for patients with milder strokes. As for subtypes of cerebral infarction, fewer patients demonstrated widespread impairments in the OCS in the Posterior Circulation Infarcts category than in the other categories.ConclusionOverall, the results showed a much higher incidence of cognitive impairment with the OCS than with the

  13. Direct estimation of elements of quantum states algebra and entanglement detection via linear contractions

    International Nuclear Information System (INIS)

    Horodecki, Pawel

    2003-01-01

    Possibility of some nonlinear-like operations in quantum mechanics are studied. Some general formula for real linear maps are derived. With the results we show how to perform physically separability tests based on any linear contraction (on product states) that either is real or Hermitian. We also show how to estimate either product or linear combinations of quantum states without knowledge about the states themselves. This can be viewed as a sort of quantum computing on quantum states algebra

  14. 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...

  15. Equations for estimating stand establishment, release, and thinning costs in the Lake States.

    Science.gov (United States)

    Jeffrey T. Olson; Allen L. Lundgren; Dietmar Rose

    1978-01-01

    Equations for estimating project costs for certain silvicultural treatments in the Lake States have been developed from project records of public forests. Treatments include machine site preparation, hand planting, aerial spraying, prescribed burning, manual release, and thinning.

  16. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2008

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2008 by period of entry, region and country of...

  17. DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING

    Data.gov (United States)

    National Aeronautics and Space Administration — DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING SUBHASISH MOHANTY*, ADITI CHATTOPADHYAY, JOHN N. RAJADAS, AND CLYDE...

  18. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2007

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2007 by period of entry, region and country of...

  19. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2012

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the size of the unauthorized immigrant population residing in the United States as of January 2012 by period of entry, region and...

  20. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2009

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2009 by period of entry, region and country of...

  1. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2006

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2006 by period of entry, region and country of...

  2. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2011

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the size of the unauthorized immigrant population residing in the United States as of January 2011 by period of entry, region and...

  3. State Estimation of International Space Station Centrifuge Rotor With Incomplete Knowledge of Disturbance Inputs

    National Research Council Canada - National Science Library

    Sullivan, Michael J

    2005-01-01

    This thesis develops a state estimation algorithm for the Centrifuge Rotor (CR) system where only relative measurements are available with limited knowledge of both rotor imbalance disturbances and International Space Station (ISS...

  4. Estimates of the Lawful Permanent Resident Population in the United States: January 2013

    Data.gov (United States)

    Department of Homeland Security — This report presents estimates of the lawful permanent resident (LPR) population living in the United States on January 1, 2013. The LPR population includes persons...

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

    KAUST Repository

    El Gharamti, Mohamad; Hoteit, Ibrahim; Valstar, Johan R.

    2013-01-01

    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

  6. 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.

  7. Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2010

    Data.gov (United States)

    Department of Homeland Security — This report provides estimates of the size of the unauthorized immigrant population residing in the United States as of January 2010 by period of entry, region and...

  8. Estimates of the Lawful Permanent Resident Population in the United States: January 2014

    Data.gov (United States)

    Department of Homeland Security — This report presents estimates of the lawful permanent resident (LPR) population living in the United States on January 1, 2014. The LPR population includes persons...

  9. H∞ state estimation for discrete-time memristive recurrent neural networks with stochastic time-delays

    Science.gov (United States)

    Liu, Hongjian; Wang, Zidong; Shen, Bo; Alsaadi, Fuad E.

    2016-07-01

    This paper deals with the robust H∞ state estimation problem for a class of memristive recurrent neural networks with stochastic time-delays. The stochastic time-delays under consideration are governed by a Bernoulli-distributed stochastic sequence. The purpose of the addressed problem is to design the robust state estimator such that the dynamics of the estimation error is exponentially stable in the mean square, and the prescribed ? performance constraint is met. By utilizing the difference inclusion theory and choosing a proper Lyapunov-Krasovskii functional, the existence condition of the desired estimator is derived. Based on it, the explicit expression of the estimator gain is given in terms of the solution to a linear matrix inequality. Finally, a numerical example is employed to demonstrate the effectiveness and applicability of the proposed estimation approach.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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...

  15. Sea state estimation from an advancing ship – A comparative study using sea trial data

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Stredulinsky, David C.

    2012-01-01

    of a traditional wave rider buoy. The paper studies the ‘wave buoy analogy’, and a large set of full-scale motion measurements is considered. It is shown that the wave buoy analogy gives fairly accurate estimates of integrated sea state parameters when compared to corresponding estimates from real wave rider buoys...

  16. Estimation and asymptotic theory for transition probabilities in Markov Renewal Multi–state models

    NARCIS (Netherlands)

    Spitoni, C.; Verduijn, M.; Putter, H.

    2012-01-01

    In this paper we discuss estimation of transition probabilities for semi–Markov multi–state models. Non–parametric and semi–parametric estimators of the transition probabilities for a large class of models (forward going models) are proposed. Large sample theory is derived using the functional

  17. Examining Cognitive Status of Elderly Iranians: Farsi Version of the Modified Mini-Mental State Examination.

    Science.gov (United States)

    Gharaeipour, Manouchehr; Andrew, Melissa K

    2013-02-27

    The Modified Mini-Mental State Examination (3MS) is an expanded and modified version of the Mini-Mental State Examination (MMSE). Research demonstrates that the reliability, validity, specificity, and sensitivity of the 3MS are superior to that of the MMSE in detecting cognitive impairment. The Farsi version of the 3MS (F-3MS) was examined as a screening tool for dementia among elderly Iranians. The F-3MS and the Clock Drawing Test (CDT) were administered to 58 patients with dementia and 145 control subjects with normal cognition, aged 60 to 85 years. The difference between groups on the mean total scores of the F-3MS was statistically significant (dementia = 60.65 ± 9.89, control = 80.73 ± 8.26; df = 201, t = 14.75, p validity of the F-3MS. The F-3MS can be used as a valid and reliable measure for dementia screening among elderly Iranians.

  18. Motor cognitive processing speed estimation among the primary schoolchildren by deriving prediction formula: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Vencita Priyanka Aranha

    2017-01-01

    Full Text Available Objectives: Motor cognitive processing speed (MCPS is often reported in terms of reaction time. In spite of being a significant indicator of function, behavior, and performance, MCPS is rarely used in clinics and schools to identify kids with slowed motor cognitive processing. The reason behind this is the lack of availability of convenient formula to estimate MCPS. Thereby, the aim of this study is to estimate the MCPS in the primary schoolchildren. Materials and Methods: Two hundred and four primary schoolchildren, aged 6–12 years, were recruited by the cluster sampling method for this cross-sectional study. MCPS was estimated by the ruler drop method (RDM. By this method, a metallic stainless steel ruler was suspended vertically such that 5 cm graduation of the lower was aligned between the web space of the child's hand, and the child was asked to catch the moving ruler as quickly as possible, once released from the examiner's hand. Distance the ruler traveled was recorded and converted into time, which is the MCPS. Multiple regression analysis of variables was performed to determine the influence of independent variables on MCPS. Results: Mean MCPS of the entire sample of 204 primary schoolchildren is 230.01 ms ± 26.5 standard deviation (95% confidence interval; 226.4–233.7 ms that ranged from 162.9 to 321.6 ms. By stepwise regression analysis, we derived the regression equation, MCPS (ms = 279.625–5.495 × age, with 41.3% (R = 0.413 predictability and 17.1% (R2 = 0.171 and adjusted R2 = 0.166 variability. Conclusion: MCPS prediction formula through RDM in the primary schoolchildren has been established.

  19. A Method for Determining Pseudo-measurement State Values for Topology Observability of State Estimation in Power Systems

    Science.gov (United States)

    Urano, Shoichi; Mori, Hiroyuki

    This paper proposes a new technique for determining of state values in power systems. Recently, it is useful for carrying out state estimation with data of PMU (Phasor Measurement Unit). The authors have developed a method for determining state values with artificial neural network (ANN) considering topology observability in power systems. ANN has advantage to approximate nonlinear functions with high precision. The method evaluates pseudo-measurement state values of the data which are lost in power systems. The method is successfully applied to the IEEE 14-bus system.

  20. 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.

  1. 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.

  2. Application of a Channel Estimation Algorithm to Spectrum Sensing in a Cognitive Radio Context

    Directory of Open Access Journals (Sweden)

    Vincent Savaux

    2014-01-01

    Full Text Available This paper deals with spectrum sensing in an orthogonal frequency division multiplexing (OFDM context, allowing an opportunistic user to detect a vacant spectrum resource in a licensed band. The proposed method is based on an iterative algorithm used for the joint estimation of noise variance and frequency selective channel. It can be seen as a second-order detector, since it is performed by means of the minimum mean square error criterion. The main advantage of the proposed algorithm is its capability to perform spectrum sensing, noise variance estimation, and channel estimation in the presence of a signal. Furthermore, the sensing duration is limited to only one OFDM symbol. We theoretically show the convergence of the algorithm, and we derive its analytical detection and false alarm probabilities. Furthermore, we show that the detector is very efficient, even for low SNR values, and is robust against a channel uncertainty.

  3. Cognitive and default-mode resting state networks: do male and female brains "rest" differently?

    Science.gov (United States)

    Weissman-Fogel, Irit; Moayedi, Massieh; Taylor, Keri S; Pope, Geoff; Davis, Karen D

    2010-11-01

    Variability in human behavior related to sex is supported by neuroimaging studies showing differences in brain activation patterns during cognitive task performance. An emerging field is examining the human connectome, including networks of brain regions that are not only temporally-correlated during different task conditions, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual task performance and behavior under certain conditions. Therefore, our aim was to determine whether sex differences exist during a task-free resting state for two networks associated with cognitive task performance (executive control network (ECN), salience network (SN)) and the default mode network (DMN). Forty-nine healthy subjects (26 females, 23 males) underwent a 5-min task-free fMRI scan in a 3T MRI. An independent components analysis (ICA) was performed to identify the best-fit IC for each network based on specific spatial nodes defined in previous studies. To determine the consistency of these networks across subjects we performed self-organizing group-level ICA analyses. There were no significant differences between sexes in the functional connectivity of the brain areas within the ECN, SN, or the DMN. These important findings highlight the robustness of intrinsic connectivity of these resting state networks and their similarity between sexes. Furthermore, our findings suggest that resting state fMRI studies do not need to be controlled for sex. © 2010 Wiley-Liss, Inc.

  4. Identifying the most efficient items from the Mini-Mental State Examination for cognitive function assessment in older Taiwanese patients.

    Science.gov (United States)

    Lou, Meei-Fang; Dai, Yu-Tzu; Huang, Guey-Shiun; Yu, Po-Jui

    2007-03-01

    The purpose of the study was to identify the most efficient items from the Mini-Mental State Examination for assessment of cognitive function. The Mini-Mental State Examination is the most frequently used cognitive screening instrument. However, the Mini-Mental State Examination has been criticized for insensitivity to mild cognitive dysfunction, limited memory assessment and variability in level of difficulty of the individual items. This study used secondary data analysis. Item response theory two-parameter model was used to analyse the data from the admission assessment of mental status by the Mini-Mental State Examination for 801 patients. By using item response analysis, 16 items were selected from the original 30-item Mini-Mental State Examination. The 16 items included mainly the measures of orientation, recall and attention and calculation. The internal consistency of the 16-item Mini-Mental State Examination was 0.84. The proposed new cut-off point for the 16-item Mini-Mental State Examination was 11. The correct classification rate was 0.94, the sensitivity was 100% and the specificity was 97.4%, when compared with the original 30-item Mini-Mental State Examination from the cut-off point of 24. This new cut-off point was determined for the purpose of over-identifying patients at risk so as to ensure early detection of and prevention from the onset of cognitive disturbance. Only a few items are needed to describe the subject's cognitive status. Using item response theory analysis, the study found that the Mini-Mental State Examination could be simplified. Deleting the items with less variation makes this assessment tool not only shorter, easier to administer and less strenuous for respondents, but also enables one to maintain validity as a cognitive function test for clinical setting.

  5. 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,

  6. 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.

  7. 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.

  8. 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.

  9. Consequences of Learned Helplessness and Recognition of the State of Cognitive Exhaustion in Persons with Mild Intellectual Disability.

    Science.gov (United States)

    Gacek, Michał; Smoleń, Tomasz; Pilecka, Władysława

    2017-01-01

    Persons with intellectual disability are a group at risk of being exposed to overly demanding problem-solving situations, which may produce learned helplessness . The research was based on the informational model of learned helplessness. The consequences of exposure to an unsolvable task and the ability to recognize the symptoms of cognitive exhaustion were tested in 120 students with mild intellectual disability. After the exposure to the unsolvable task, persons in the experimental group obtained lower results than the control group in the escape/avoidance learning task, but a similar result was found in the divergent thinking fluency task. Also, participants in the experimental group had difficulties recognizing the symptoms of the cognitive exhaustion state. After a week's time, the difference in escape/avoidance learning performance was still observed. The results indicate that exposure to unsolvable tasks may negatively influence the cognitive performance in persons with intellectual disability, although those persons may not identify the cognitive state related to lowered performance.

  10. 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.

  11. Robust stability and ℋ ∞ -estimation for uncertain discrete systems with state-delay

    Directory of Open Access Journals (Sweden)

    Mahmoud Magdi S.

    2001-01-01

    Full Text Available In this paper, we investigate the problems of robust stability and ℋ ∞ -estimation for a class of linear discrete-time systems with time-varying norm-bounded parameter uncertainty and unknown state-delay. We provide complete results for robust stability with prescribed performance measure and establish a version of the discrete Bounded Real Lemma. Then, we design a linear estimator such that the estimation error dynamics is robustly stable with a guaranteed ℋ ∞ -performance irrespective of the parameteric uncertainties and unknown state delays. A numerical example is worked out to illustrate the developed theory.

  12. 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....

  13. 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.

  14. 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.

  15. The effects of healthy aging, amnestic mild cognitive impairment, and Alzheimer's disease on recollection, familiarity and false recognition, estimated by an associative process-dissociation recognition procedure.

    Science.gov (United States)

    Pitarque, Alfonso; Meléndez, Juan C; Sales, Alicia; Mayordomo, Teresa; Satorres, Encar; Escudero, Joaquín; Algarabel, Salvador

    2016-10-01

    Given the uneven experimental results in the literature regarding whether or not familiarity declines with healthy aging and cognitive impairment, we compare four samples (healthy young people, healthy older people, older people with amnestic mild cognitive impairment - aMCI -, and older people with Alzheimer's disease - AD -) on an associative recognition task, which, following the logic of the process-dissociation procedure, allowed us to obtain corrected estimates of recollection, familiarity and false recognition. The results show that familiarity does not decline with healthy aging, but it does with cognitive impairment, whereas false recognition increases with healthy aging, but declines significantly with cognitive impairment. These results support the idea that the deficits detected in recollection, familiarity, or false recognition in older people could be used as early prodromal markers of cognitive impairment. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. 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

  17. Affective problems and decline in cognitive state in older adults: a systematic review and meta-analysis.

    Science.gov (United States)

    John, A; Patel, U; Rusted, J; Richards, M; Gaysina, D

    2018-05-24

    Evidence suggests that affective problems, such as depression and anxiety, increase risk for late-life dementia. However, the extent to which affective problems influence cognitive decline, even many years prior to clinical diagnosis of dementia, is not clear. The present study systematically reviews and synthesises the evidence for the association between affective problems and decline in cognitive state (i.e., decline in non-specific cognitive function) in older adults. An electronic search of PubMed, PsycInfo, Cochrane, and ScienceDirect was conducted to identify studies of the association between depression and anxiety separately and decline in cognitive state. Key inclusion criteria were prospective, longitudinal designs with a minimum follow-up period of 1 year. Data extraction and methodological quality assessment using the STROBE checklist were conducted independently by two raters. A total of 34 studies (n = 71 244) met eligibility criteria, with 32 studies measuring depression (n = 68 793), and five measuring anxiety (n = 4698). A multi-level meta-analysis revealed that depression assessed as a binary predictor (OR 1.36, 95% CI 1.05-1.76, p = 0.02) or a continuous predictor (B = -0.008, 95% CI -0.015 to -0.002, p = 0.012; OR 0.992, 95% CI 0.985-0.998) was significantly associated with decline in cognitive state. The number of anxiety studies was insufficient for meta-analysis, and they are described in a narrative review. Results of the present study improve current understanding of the temporal nature of the association between affective problems and decline in cognitive state. They also suggest that cognitive function may need to be monitored closely in individuals with affective disorders, as these individuals may be at particular risk of greater cognitive decline.

  18. 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...

  19. 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

  20. Branch current state estimation of three phase distribution networks suitable for paralellization

    NARCIS (Netherlands)

    Blaauwbroek, N.; Nguyen, H.P.; Gibescu, M.; Slootweg, J.G.

    2017-01-01

    The evolution of distribution networks from passive to active distribution systems puts new requirements on the monitoring and control capabilities of these systems. The development of state estimation algorithms to gain insight in the actual system state of a distribution network has resulted in a

  1. Modeling of HVDC in Dynamic State Estimation Using Unscented Kalman Filter Method

    DEFF Research Database (Denmark)

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

    2016-01-01

    HVDC transmission is an integral part of various power system networks. This article presents an Unscented Kalman Filter dynamic state estimator algorithm that considers the presence of HVDC links. The AC - DC power flow analysis, which is implemented as power flow solver for Dynamic State...

  2. 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.

  3. 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.

  4. 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.

  5. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    Science.gov (United States)

    Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

    2013-09-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

  6. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    International Nuclear Information System (INIS)

    Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A

    2013-01-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)

  7. State estimation for Markov-type genetic regulatory networks with delays and uncertain mode transition rates

    International Nuclear Information System (INIS)

    Liang Jinling; Lam, James; Wang Zidong

    2009-01-01

    This Letter is concerned with the robust state estimation problem for uncertain time-delay Markovian jumping genetic regulatory networks (GRNs) with SUM logic, where the uncertainties enter into both the network parameters and the mode transition rate. The nonlinear functions describing the feedback regulation are assumed to satisfy the sector-like conditions. The main purpose of the problem addressed is to design a linear estimator to approximate the true concentrations of the mRNA and protein through available measurement outputs. By resorting to the Lyapunov functional method and some stochastic analysis tools, it is shown that if a set of linear matrix inequalities (LMIs) is feasible, the desired state estimator, that can ensure the estimation error dynamics to be globally robustly asymptotically stable in the mean square, exists. The obtained LMI conditions are dependent on both the lower and the upper bounds of the delays. An illustrative example is presented to demonstrate the feasibility of the proposed estimation schemes.

  8. Research on State-of-Charge (SOC) estimation using current integration based on temperature compensation

    Science.gov (United States)

    Yin, J.; Shen, Y.; Liu, X. T.; Zeng, G. J.; Liu, D. C.

    2017-11-01

    The traditional current integral method for the state-of-charge (SOC) estimation has an unusable estimation accuracy because of the current measuring error. This paper proposed a closed-loop temperature compensation method to improve the SOC estimation accuracy of current integral method by eliminating temperature drift. Through circuit simulation result in Multisim, the stability of current measuring accuracy is improved by more than 10 times. In a designed 70 charge-discharge experimental circle, the SOC estimation error with temperature compensation had 30 times less than error in normal situation without compensation.

  9. Contingency Estimation of States for Unmanned Aerial Vehicle using a Spherical Simplex Unscented Filter

    DEFF Research Database (Denmark)

    Hahn, Tobias; Hansen, Søren; Blanke, Mogens

    2012-01-01

    Aiming at survival from contingency situations for unmanned aerial vehicles, a square root spherical simplex unscented Kalman filter is applied for state and parameter estimation and a rough model is used for state prediction when essential measurements are lost. Processing real flight data, rece...... efficient square root implementation of the filter algorithm. A case of loss of GPS signal demonstrates the use of the state estimates to obtain return of the UAV to close to it’s home base where safe recovery is possible....

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

    Directory of Open Access Journals (Sweden)

    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.

  11. 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.

  12. Metric qualities of the cognitive behavioral assessment for outcome evaluation to estimate psychological treatment effects.

    Science.gov (United States)

    Bertolotti, Giorgio; Michielin, Paolo; Vidotto, Giulio; Sanavio, Ezio; Bottesi, Gioia; Bettinardi, Ornella; Zotti, Anna Maria

    2015-01-01

    Cognitive behavioral assessment for outcome evaluation was developed to evaluate psychological treatment interventions, especially for counseling and psychotherapy. It is made up of 80 items and five scales: anxiety, well-being, perception of positive change, depression, and psychological distress. The aim of the study was to present the metric qualities and to show validity and reliability of the five constructs of the questionnaire both in nonclinical and clinical subjects. Four steps were completed to assess reliability and factor structure: criterion-related and concurrent validity, responsiveness, and convergent-divergent validity. A nonclinical group of 269 subjects was enrolled, as was a clinical group comprising 168 adults undergoing psychotherapy and psychological counseling provided by the Italian public health service. Cronbach's alphas were between 0.80 and 0.91 for the clinical sample and between 0.74 and 0.91 in the nonclinical one. We observed an excellent structural validity for the five interrelated dimensions. The clinical group showed higher scores in the anxiety, depression, and psychological distress scales, as well as lower scores in well-being and perception of positive change scales than those observed in the nonclinical group. Responsiveness was large for the anxiety, well-being, and depression scales; the psychological distress and perception of positive change scales showed a moderate effect. The questionnaire showed excellent psychometric properties, thus demonstrating that the questionnaire is a good evaluative instrument, with which to assess pre- and post-treatment outcomes.

  13. [Effectiveness of the Mini-Mental State for detection of cognitive impairment in primary care].

    Science.gov (United States)

    Carnero Pardo, Cristóbal; Cruz Orduña, Isabel; Espejo Martínez, Beatriz; Cárdenas Viedma, Salvador; Torrero García, Pedro; Olazarán Rodríguez, Javier

    2013-10-01

    To evaluate the diagnostic accuracy (DA) of the Mini-Mental State (MMS) for the detection of cognitive impairment (CI) in Primary Care (PC) and to determine the best conditions of use for that purpose. Pooled analysis of two prospective, double blind, studies on the evaluation of diagnostic tools with complete verification that were conducted in Madrid and Granada (Spain). The MMS was administered in PC and the final cognitive diagnosis (gold standard) was made in Specialized Care. Subjects with cognitive complaints or suspected of having CI were consecutively recruited in the PC clinic. The DA of the MMS was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best cut-off point was selected according to the ratio of cases correctly classified (RCC) and to the kappa index. Direct (MMSd) and age- and education-adjusted (MMSa) total scores were analyzed separately. In the total sample of 360 subjects (214 CI), the DA of the MMSd was significantly superior to that of the MMSa (0.84±0.02 vs 0.82±0.02, p≤.001). The yield obtained by the best cut-off point of the MMSd (22/23) was modest (RCC 0.77, kappa 0.52±0.05) and was not improved by any MMSa cut-off point. The DA of the MMS for detection of CI in PC was modest and did not improve with adjustment of the score by age and education. The best cut-off point was 22/23, inferior to the usually recommended cut-off. Copyright © 2013 Elsevier España, S.L. All rights reserved.

  14. 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.

  15. Enhancing interferometer phase estimation, sensing sensitivity, and resolution using robust entangled states

    Science.gov (United States)

    Smith, James F.

    2017-11-01

    With the goal of designing interferometers and interferometer sensors, e.g., LADARs with enhanced sensitivity, resolution, and phase estimation, states using quantum entanglement are discussed. These states include N00N states, plain M and M states (PMMSs), and linear combinations of M and M states (LCMMS). Closed form expressions for the optimal detection operators; visibility, a measure of the state's robustness to loss and noise; a resolution measure; and phase estimate error, are provided in closed form. The optimal resolution for the maximum visibility and minimum phase error are found. For the visibility, comparisons between PMMSs, LCMMS, and N00N states are provided. For the minimum phase error, comparisons between LCMMS, PMMSs, N00N states, separate photon states (SPSs), the shot noise limit (SNL), and the Heisenberg limit (HL) are provided. A representative collection of computational results illustrating the superiority of LCMMS when compared to PMMSs and N00N states is given. It is found that for a resolution 12 times the classical result LCMMS has visibility 11 times that of N00N states and 4 times that of PMMSs. For the same case, the minimum phase error for LCMMS is 10.7 times smaller than that of PMMS and 29.7 times smaller than that of N00N states.

  16. Internal States and Behavioral Decision-Making: Toward an Integration of Emotion and Cognition.

    Science.gov (United States)

    Kennedy, Ann; Asahina, Kenta; Hoopfer, Eric; Inagaki, Hidehiko; Jung, Yonil; Lee, Hyosang; Remedios, Ryan; Anderson, David J

    2014-01-01

    Social interactions, such as an aggressive encounter between two conspecific males or a mating encounter between a male and a female, typically progress from an initial appetitive or motivational phase, to a final consummatory phase. This progression involves both changes in the intensity of the animals' internal state of arousal or motivation and sequential changes in their behavior. How are these internal states, and their escalating intensity, encoded in the brain? Does this escalation drive the progression from the appetitive/motivational to the consummatory phase of a social interaction and, if so, how are appropriate behaviors chosen during this progression? Recent work on social behaviors in flies and mice suggests possible ways in which changes in internal state intensity during a social encounter may be encoded and coupled to appropriate behavioral decisions at appropriate phases of the interaction. These studies may have relevance to understanding how emotion states influence cognitive behavioral decisions at higher levels of brain function. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

  17. 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.

  18. 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.

  19. Unconditional and Conditional Standards Using Cognitive Function Curves for the Modified Mini-Mental State Exam: Cross-Sectional and Longitudinal Analyses in Older Chinese Adults in Singapore.

    Science.gov (United States)

    Cheung, Yin Bun; Xu, Ying; Feng, Lei; Feng, Liang; Nyunt, Ma Shwe Zin; Chong, Mei Sian; Lim, Wee Shiong; Lee, Tih Shih; Yap, Philip; Yap, Keng Bee; Ng, Tze Pin

    2015-09-01

    The conventional practice of assessing cognitive status and monitoring change over time in older adults using normative values of the Mini-Mental State Exam (MMSE) based on age bands is imprecise. Moreover, population-based normative data on changes in MMSE score over time are scarce and crude because they do not include age- and education-specific norms. This study aims to develop unconditional standards for assessing current cognitive status and conditional standards that take prior MMSE score into account for assessing longitudinal change, with percentile curves as smooth functions of age. Cross-sectional and longitudinal data of a modified version of the MMSE for 2,026 older Chinese adults from the Singapore Longitudinal Aging Study, aged 55-84, in Singapore were used to estimate quantile regression coefficients and create unconditional standards and conditional standards. We presented MMSE percentile curves as a smooth function of age in education strata, for unconditional and conditional standards, based on quantile regression coefficient estimates. We found the 5th and 10th percentiles were more strongly associated with age and education than were higher percentiles. Model diagnostics demonstrated the accuracy of the standards. The development and use of unconditional and conditional standards should facilitate cognitive assessment in clinical practice and deserve further studies. Copyright © 2015 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  20. Multimodality Inferring of Human Cognitive States Based on Integration of Neuro-Fuzzy Network and Information Fusion Techniques

    Directory of Open Access Journals (Sweden)

    P. Bhattacharya

    2007-11-01

    Full Text Available To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human's operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressions or cues, the recent trend to infer the human state is to consider multimodality features of the human operator. In this paper, we present a method for multimodality inferring of human cognitive states by integrating neuro-fuzzy network and information fusion techniques. To demonstrate the effectiveness of this method, we take the driver fatigue detection as an example. The proposed method has, in particular, the following new features. First, human expressions are classified into four categories: (i casual or contextual feature, (ii contact feature, (iii contactless feature, and (iv performance feature. Second, the fuzzy neural network technique, in particular Takagi-Sugeno-Kang (TSK model, is employed to cope with uncertain behaviors. Third, the sensor fusion technique, in particular ordered weighted aggregation (OWA, is integrated with the TSK model in such a way that cues are taken as inputs to the TSK model, and then the outputs of the TSK are fused by the OWA which gives outputs corresponding to particular cognitive states under interest (e.g., fatigue. We call this method TSK-OWA. Validation of the TSK-OWA, performed in the Northeastern University vehicle drive simulator, has shown that the proposed method is promising to be a general tool for human cognitive state inferring and a special tool for the driver fatigue detection.

  1. Changes in thalamus connectivity in mild cognitive impairment: Evidence from resting state fMRI

    International Nuclear Information System (INIS)

    Wang Zhiqun; Jia Xiuqin; Liang Peipeng; Qi Zhigang; Yang Yanhui; Zhou Weidong; Li Kuncheng

    2012-01-01

    Purpose: The subcortical region such as thalamus was believed to have close relationship with many cerebral cortexes which made it especially interesting in the study of functional connectivity. Here, we used resting state functional MRI (fMRI) to examine changes in thalamus connectivity in mild cognitive impairment (MCI), which presented a neuro-disconnection syndrome. Materials and methods: Data from 14 patients and 14 healthy age-matched controls were analyzed. Thalamus connectivity was investigated by examination of the correlation between low frequency fMRI signal fluctuations in the thalamus and those in all other brain regions. Results: We found that functional connectivity between the left thalamus and a set of regions was decreased in MCI; these regions are: bilateral cuneus, middle occipital gyrus (MOG), superior frontal gyrus (SFG), medial prefrontal cortex (MPFC), precuneus, inferior frontal gyrus (IFG) and precentral gyrus (PreCG). There are also some regions showed reduced connectivity to right thalamus; these regions are bilateral cuneus, MOG, fusiform gyrus (FG), MPFC, paracentral lobe (PCL), precuneus, superior parietal lobe (SPL) and IFG. We also found increased functional connectivity between the left thalamus and the right thalamus in MCI. Conclusion: The decreased connectivity between the thalamus and the other brain regions might indicate reduced integrity of thalamus-related cortical networks in MCI. Furthermore, the increased connectivity between the left and right thalamus suggest compensation for the loss of cognitive function. Briefly, impairment and compensation of thalamus connectivity coexist in the MCI patients.

  2. Cognitive Deficits in Healthy Elderly Population With "Normal" Scores on the Mini-Mental State Examination.

    Science.gov (United States)

    Votruba, Kristen L; Persad, Carol; Giordani, Bruno

    2016-05-01

    This study investigated whether healthy older adults with Mini-Mental State Examination (MMSE) scores above 23 exhibit cognitive impairment on neuropsychological tests. Participants completed the MMSE and a neuropsychological battery including tests of 10 domains. Results were compared to published normative data. On neuropsychological testing, participants performed well on measures of naming and recall but showed mild to moderate impairment in working memory and processing speed and marked impairment in inhibition, sustained attention, and executive functioning. Almost everyone (91%) scored at least 1 standard deviation (SD) below the mean in at least 1 domain. The median number of domains in which individuals scored below 1 SD was 3.0 of 10.0, whereas over 21% scored below 1 SD in 5 domains or more. With the strictest of definitions for impairment, 20% of this population scored below 2.0 SDs below the norm in at least 2 domains, a necessary condition for a diagnosis of dementia. The finding that cognitive impairment, particularly in attention and executive functioning, is found in healthy older persons who perform well on the MMSE has clinical and research implications in terms of emphasizing normal variability in performance and early identification of possible impairment. © The Author(s) 2016.

  3. Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment.

    Science.gov (United States)

    Yi, Li-Ye; Liang, Xia; Liu, Da-Ming; Sun, Bo; Ying, Sun; Yang, Dong-Bo; Li, Qing-Bin; Jiang, Chuan-Lu; Han, Ying

    2015-10-01

    Neuroimaging studies have demonstrated both structural and functional abnormalities in widespread brain regions in patients with subcortical vascular mild cognitive impairment (svMCI). However, whether and how these changes alter functional brain network organization remains largely unknown. We recruited 21 patients with svMCI and 26 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging scans. Graph theory-based network analyses were used to investigate alterations in the topological organization of functional brain networks. Compared with the HC individuals, the patients with svMCI showed disrupted global network topology with significantly increased path length and modularity. Modular structure was also impaired in the svMCI patients with a notable rearrangement of the executive control module, where the parietal regions were split out and grouped as a separate module. The svMCI patients also revealed deficits in the intra- and/or intermodule connectivity of several brain regions. Specifically, the within-module degree was decreased in the middle cingulate gyrus while it was increased in the left anterior insula, medial prefrontal cortex and cuneus. Additionally, increased intermodule connectivity was observed in the inferior and superior parietal gyrus, which was associated with worse cognitive performance in the svMCI patients. Together, our results indicate that svMCI patients exhibit dysregulation of the topological organization of functional brain networks, which has important implications for understanding the pathophysiological mechanism of svMCI. © 2015 John Wiley & Sons Ltd.

  4. Cognitive two-way relay beamforming: Design with resilience to channel state uncertainties

    KAUST Repository

    Ubaidulla, P.

    2016-07-26

    In this paper, we propose a robust distributed relay beamformer design for cognitive radio network operating under uncertainties in the available channel state information. The cognitive network consists of a pair of transceivers and a set of non-regenerative two-way relays that assist the communication between the transceiver pair. The secondary nodes share the spectrum with a licensed primary user node while ensuring that the interference to the primary receiver is maintained below a certain threshold. The proposed robust design maximizes the worst-case signal-to-interference-plus-noise ratio at the secondary transceivers while satisfying constraints on the interference to the primary user and on the total relay transmit power. Though the robust design problem is not a convex problem in its original form, we show that it can be reformulated as a convex optimization problem, which can be solved efficiently. Numerical results are provided and illustrate the merits of the proposed design for various operating conditions and parameters. © 2016 IEEE.

  5. Adaptive Kalman filter based state of charge estimation algorithm for lithium-ion battery

    International Nuclear Information System (INIS)

    Zheng Hong; Liu Xu; Wei Min

    2015-01-01

    In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded. (paper)

  6. The reliability of assigning individuals to cognitive states using the Mini Mental-State Examination: a population-based prospective cohort study

    OpenAIRE

    Marioni, Riccardo E.; Chatfield, Mark; Brayne, Carol; Matthews, Fiona E.; Med Res Council

    2011-01-01

    Abstract Background Previous investigations of test re-test reliability of the Mini-Mental State Examination (MMSE) have used correlations and statistics such as Cronbach's α to assess consistency. In practice, the MMSE is usually used to group individuals into cognitive states. The reliability of this grouping (state based approach) has not been fully explored. Methods MMSE data were collected on a subset of 2,275 older participants (≥ 65 years) from the population-based Medical Research Cou...

  7. 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.

  8. The reliability of assigning individuals to cognitive states using the Mini Mental-State Examination: a population-based prospective cohort study

    Directory of Open Access Journals (Sweden)

    Brayne Carol

    2011-09-01

    Full Text Available Abstract Background Previous investigations of test re-test reliability of the Mini-Mental State Examination (MMSE have used correlations and statistics such as Cronbach's α to assess consistency. In practice, the MMSE is usually used to group individuals into cognitive states. The reliability of this grouping (state based approach has not been fully explored. Methods MMSE data were collected on a subset of 2,275 older participants (≥ 65 years from the population-based Medical Research Council Cognitive Function and Ageing Study. Two measurements taken approximately two months apart were used to investigate three state-based categorisations. Descriptive statistics were used to determine how many people remained in the same cognitive group or went up or down groups. Weighted logistic regression was used to identify predictive characteristics of those who moved group. Results The proportion of people who remained in the same MMSE group at screen and follow-up assessment ranged from 58% to 78%. The proportion of individuals who went up one or more groups was roughly equal to the proportion that went down one or more groups; most of the change occurred when measurements were close to the cut-points. There was no consistently significant predictor for changing cognitive group. Conclusion A state-based approach to analysing the reliability of the MMSE provided similar results to correlation analyses. State-based models of cognitive change or individual trajectory models using raw scores need multiple waves to help overcome natural variation in MMSE scores and to help identify true cognitive change.

  9. 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.

  10. NATIONAL STATE VARIATION OF GERMAN PHRASEOLOGY. ANTROPOCENTRIC, COGNITIVE AND CORPUS-BASED APPROACHE

    Directory of Open Access Journals (Sweden)

    О.Y. Ostapovych

    2015-09-01

    Full Text Available The article deals with the elaboration of the modern theoretical concept in study of the variation of German phraseology abroad Germany. It is based on the synthesis of the theory of equal-righted pluricentrism and the hypothesis of double linguistic additivity with the new achievements of the cognitive linguistics. As a result the notions of the «non-predominant national state linguistic variant» different from the regional, normatively non-codified and dialectal variation, cluster variant idiomatic thesaurus, national communicative area in the sphere of phraseology have been introduced. The empirical reality of the categories of «national phraseological system/microsystem», «pluricentric archisystem», «correlation hierarchy», «phraseological world picture», «phraseological concept» has also been falsified.

  11. The new science of moral cognition: the state of the art

    Directory of Open Access Journals (Sweden)

    Antonio Olivera La Rosa

    2014-10-01

    Full Text Available The need for multidisciplinary approaches to the scientific study of human nature is a widely supported academic claim. This assumption has proved to be especially successful in the field of moral psychology. Although studies of moral topics have been ubiquitous in both humanities and social sciences, it is not until the integration of different scientific disciplines in the convergent science of moral psychology that the study of morality seems to start its flourishing age. Thus, in the last ten years, a growing body of research from cognitive sciences, experimental philosophy, primatology, clinical and developmental psychology, economy and anthropology have made possible a "new era" on the study of morality. In this paper, we review the most striking findings that constitute the "state of the art' of moral psychology, with the aim to facilitate a better understanding of how the mind functions in the moral domain.

  12. Time to talk about work-hour impact on anesthesiologists: The effects of sleep deprivation on Profile of Mood States and cognitive tasks.

    Science.gov (United States)

    Saadat, Haleh; Bissonnette, Bruno; Tumin, Dmitry; Thung, Arlyne; Rice, Julie; Barry, N'Diris; Tobias, Joseph

    2016-01-01

    A physician's fatigue raises significant concerns regarding personal and patient safety. Effects of sleep deprivation on clinical performance and the quality of patient care are major considerations of today's health care environment. To evaluate the impact of partial sleep deprivation after a 17-h overnight call (3 pm-7 am) on the mood status and cognitive skills of anesthesiologists in an academic clinical hospital setting, as compared to these parameters during regular working hours. Taking circadian rhythm into account, the following measures were assessed in 21 pediatric anesthesiologists at two time points over the course of the study; (i) between 7 and 8 am on a regular non call day, and (ii) between 7 and 8 am after a 17-h in-house call (3 pm-7 am). Six mood states were assessed using the Profile of Mood States. A Total Mood Disturbance (TMD) score was obtained as the sum of all mood scores minus vigor. The total score provides a global estimate of affective state. Simple cognitive tests were similarly administered to assess cognitive skills. A two-tailed paired t-test was used to compare data between regular and post call days. A P sleep deprivation affects the total mood status of anesthesiologists and impacts their cognitive skills. These findings are particularly relevant in a context of increased work expectation, particularly on clinical performance in our modern medical system. Such observations suggest that there may be changes that impact the safety of our patients and the quality of health care that is provided. © 2015 John Wiley & Sons Ltd.

  13. Soft Sensor of Vehicle State Estimation Based on the Kernel Principal Component and Improved Neural Network

    Directory of Open Access Journals (Sweden)

    Haorui Liu

    2016-01-01

    Full Text Available In the car control systems, it is hard to measure some key vehicle states directly and accurately when running on the road and the cost of the measurement is high as well. To address these problems, a vehicle state estimation method based on the kernel principal component analysis and the improved Elman neural network is proposed. Combining with nonlinear vehicle model of three degrees of freedom (3 DOF, longitudinal, lateral, and yaw motion, this paper applies the method to the soft sensor of the vehicle states. The simulation results of the double lane change tested by Matlab/SIMULINK cosimulation prove the KPCA-IENN algorithm (kernel principal component algorithm and improved Elman neural network to be quick and precise when tracking the vehicle states within the nonlinear area. This algorithm method can meet the software performance requirements of the vehicle states estimation in precision, tracking speed, noise suppression, and other aspects.

  14. 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.

  15. 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.

  16. Distinguishing cognitive state with multifractal complexity of hippocampal interspike interval sequences

    Directory of Open Access Journals (Sweden)

    Dustin eFetterhoff

    2015-09-01

    Full Text Available Fractality, represented as self-similar repeating patterns, is ubiquitous in nature and the brain. Dynamic patterns of hippocampal spike trains are known to exhibit multifractal properties during working memory processing; however, it is unclear whether the multifractal properties inherent to hippocampal spike trains reflect active cognitive processing. To examine this possibility, hippocampal neuronal ensembles were recorded from rats before, during and after a spatial working memory task following administration of tetrahydrocannabinol (THC, a memory-impairing component of cannabis. Multifractal detrended fluctuation analysis was performed on hippocampal interspike interval sequences to determine characteristics of monofractal long-range temporal correlations (LRTCs, quantified by the Hurst exponent, and the degree/magnitude of multifractal complexity, quantified by the width of the singularity spectrum. Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses. Conversely, LRTCs are largest during resting state recordings, therefore reflecting different information compared to multifractality. In order to deepen conceptual understanding of multifractal complexity and LRTCs, these measures were compared to classical methods using hippocampal frequency content and firing variability measures. These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality. Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological and pathological states.

  17. Optimization of automation: I. Estimation method of cognitive automation rates reflecting the effects of automation on human operators in nuclear power plants

    International Nuclear Information System (INIS)

    Lee, Seung Min; Kim, Jong Hyun; Seong, Poong Hyun

    2014-01-01

    Highlights: • We propose an estimation method of the automation rate by taking the advantages of automation as the estimation measures. • We conduct the experiments to examine the validity of the suggested method. • The higher the cognitive automation rate is, the greater the decreased rate of the working time will be. • The usefulness of the suggested estimation method is proved by statistical analyses. - Abstract: Since automation was introduced in various industrial fields, the concept of the automation rate has been used to indicate the inclusion proportion of automation among all work processes or facilities. Expressions of the inclusion proportion of automation are predictable, as is the ability to express the degree of the enhancement of human performance. However, many researchers have found that a high automation rate does not guarantee high performance. Therefore, to reflect the effects of automation on human performance, this paper proposes a new estimation method of the automation rate that considers the effects of automation on human operators in nuclear power plants (NPPs). Automation in NPPs can be divided into two types: system automation and cognitive automation. Some general descriptions and characteristics of each type of automation are provided, and the advantages of automation are investigated. The advantages of each type of automation are used as measures of the estimation method of the automation rate. One advantage was found to be a reduction in the number of tasks, and another was a reduction in human cognitive task loads. The system and the cognitive automation rate were proposed as quantitative measures by taking advantage of the aforementioned benefits. To quantify the required human cognitive task loads and thus suggest the cognitive automation rate, Conant’s information-theory-based model was applied. The validity of the suggested method, especially as regards the cognitive automation rate, was proven by conducting

  18. Resting-state networks associated with cognitive processing show more age-related decline than those associated with emotional processing.

    Science.gov (United States)

    Nashiro, Kaoru; Sakaki, Michiko; Braskie, Meredith N; Mather, Mara

    2017-06-01

    Correlations in activity across disparate brain regions during rest reveal functional networks in the brain. Although previous studies largely agree that there is an age-related decline in the "default mode network," how age affects other resting-state networks, such as emotion-related networks, is still controversial. Here we used a dual-regression approach to investigate age-related alterations in resting-state networks. The results revealed age-related disruptions in functional connectivity in all 5 identified cognitive networks, namely the default mode network, cognitive-auditory, cognitive-speech (or speech-related somatosensory), and right and left frontoparietal networks, whereas such age effects were not observed in the 3 identified emotion networks. In addition, we observed age-related decline in functional connectivity in 3 visual and 3 motor/visuospatial networks. Older adults showed greater functional connectivity in regions outside 4 out of the 5 identified cognitive networks, consistent with the dedifferentiation effect previously observed in task-based functional magnetic resonance imaging studies. Both reduced within-network connectivity and increased out-of-network connectivity were correlated with poor cognitive performance, providing potential biomarkers for cognitive aging. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Exploring resting-state EEG brain oscillatory activity in relation to cognitive functioning in multiple sclerosis.

    Science.gov (United States)

    Keune, Philipp M; Hansen, Sascha; Weber, Emily; Zapf, Franziska; Habich, Juliane; Muenssinger, Jana; Wolf, Sebastian; Schönenberg, Michael; Oschmann, Patrick

    2017-09-01

    Neurophysiologic monitoring parameters related to cognition in Multiple Sclerosis (MS) are sparse. Previous work reported an association between magnetoencephalographic (MEG) alpha-1 activity and information processing speed. While this remains to be replicated by more available electroencephalographic (EEG) methods, also other established EEG markers, e.g. the slow-wave/fast-wave ratio (theta/beta ratio), remain to be explored in this context. Performance on standard tests addressing information processing speed and attention (Symbol-Digit Modalities Test, SDMT; Test of Attention Performance, TAP) was examined in relation to resting-state EEG alpha-1 and alpha-2 activity and the theta/beta ratio in 25MS patients. Increased global alpha-1 and alpha-2 activity and an increased frontal theta/beta ratio (pronounced slow-wave relative to fast-wave activity) were associated with lower SDMT processing speed. In an exploratory analysis, clinically impaired attention was associated with a significantly increased frontal theta/beta ratio whereas alpha power did not show sensitivity to clinical impairment. EEG global alpha power and the frontal theta/beta ratio were both associated with attention. The theta/beta ratio involved potential clinical sensitivity. Resting-state EEG recordings can be obtained during the routine clinical process. The examined resting-state measures may represent feasible monitoring parameters in MS. This notion should be explored in future intervention studies. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  20. 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

  1. The Modified Telephone Interview for Cognitive Status is More Predictive of Memory Abilities Than the Mini-Mental State Examination.

    Science.gov (United States)

    Duff, Kevin; Tometich, Danielle; Dennett, Kathryn

    2015-09-01

    Although not as popular as the Mini-Mental State Examination (MMSE), the modified Telephone Interview for Cognitive Status (mTICS) has some distinct advantages when screening cognitive functioning in older adults. The current study compared these 2 cognitive screening measures in their ability to predict performance on a memory composite (ie, delayed recall of verbal and visual information) in a cohort of 121 community-dwelling older adults, both at baseline and after 1 year. Both the MMSE and the mTICS significantly correlated with the memory composite at baseline (r's of .41 and .62, respectively) and at 1 year (r's of .36 and .50, respectively). At baseline, stepwise linear regression indicated that the mTICS and gender best predicted the memory composite score (R (2) = .45, P similar. Despite its lesser popularity, the mTICS may be a more attractive option when screening for cognitive abilities in this age range. © The Author(s) 2015.

  2. The cumulative load of depressive illness is associated with cognitive function in the remitted state of unipolar depressive disorder

    DEFF Research Database (Denmark)

    Hasselbalch, BJ; Knorr, U; Hasselbalch, S G

    2013-01-01

    OBJECTIVE: To investigate whether the cumulative number, duration and subtypes (severity and presence of psychotic features) of previous episodes of depression in patients with unipolar depressive disorder in a remitted state are associated with decreased global cognitive function. METHODS: Via...... with the Cambridge Cognitive Examination (CAMCOG), which provides a composite measure of global cognitive function. RESULTS: A total of 88 patients and 50 controls accepted our invitation to participate, fulfilled the selection criteria and were included in the study. The cumulative duration of depressive episodes...... episodes with psychotic features, respectively. CONCLUSION: Our findings suggest that cognitive dysfunction is associated with the cumulative duration of depressive episodes, and that, in particular, depressive episodes with psychotic features in the course of illness may be a significant predictor...

  3. Notes From the Field: Secondary Task Precision for Cognitive Load Estimation During Virtual Reality Surgical Simulation Training.

    Science.gov (United States)

    Rasmussen, Sebastian R; Konge, Lars; Mikkelsen, Peter T; Sørensen, Mads S; Andersen, Steven A W

    2016-03-01

    Cognitive load (CL) theory suggests that working memory can be overloaded in complex learning tasks such as surgical technical skills training, which can impair learning. Valid and feasible methods for estimating the CL in specific learning contexts are necessary before the efficacy of CL-lowering instructional interventions can be established. This study aims to explore secondary task precision for the estimation of CL in virtual reality (VR) surgical simulation and also investigate the effects of CL-modifying factors such as simulator-integrated tutoring and repeated practice. Twenty-four participants were randomized for visual assistance by a simulator-integrated tutor function during the first 5 of 12 repeated mastoidectomy procedures on a VR temporal bone simulator. Secondary task precision was found to be significantly lower during simulation compared with nonsimulation baseline, p impact on secondary task precision. This finding suggests that even though considerable changes in CL are reflected in secondary task precision, it lacks sensitivity. In contrast, secondary task reaction time could be more sensitive, but requires substantial postprocessing of data. Therefore, future studies on the effect of CL modifying interventions should weigh the pros and cons of the various secondary task measurements. © The Author(s) 2015.

  4. State Estimation of International Space Station Centrifuge Rotor With Incomplete Knowledge of Disturbance Inputs

    Science.gov (United States)

    Sullivan, Michael J.

    2005-01-01

    This thesis develops a state estimation algorithm for the Centrifuge Rotor (CR) system where only relative measurements are available with limited knowledge of both rotor imbalance disturbances and International Space Station (ISS) thruster disturbances. A Kalman filter is applied to a plant model augmented with sinusoidal disturbance states used to model both the effect of the rotor imbalance and the 155 thrusters on the CR relative motion measurement. The sinusoidal disturbance states compensate for the lack of the availability of plant inputs for use in the Kalman filter. Testing confirms that complete disturbance modeling is necessary to ensure reliable estimation. Further testing goes on to show that increased estimator operational bandwidth can be achieved through the expansion of the disturbance model within the filter dynamics. In addition, Monte Carlo analysis shows the varying levels of robustness against defined plant/filter uncertainty variations.

  5. 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.

  6. 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.

  7. 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...

  8. 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

  9. Estimation of Unobserved Inflation Expectations in India using State-Space Model

    OpenAIRE

    Chattopadhyay, Siddhartha; Sahu, Sohini; Jha, Saakshi

    2016-01-01

    Inflation expectations is an important marker for monetary policy makers. India being a new entrant to the group of countries that pursue inflation targeting as its monetary policy objective, estimating the inflation expectation is of paramount importance. This paper estimates the unobserved inflation expectations in India between 1993:Q1 to 2016:Q1 from the Fisher equation relation using the state space approach (Kalman Filter). We find that our results match well with the inflation forecast...

  10. Optimal quantum state estimation with use of the no-signaling principle

    International Nuclear Information System (INIS)

    Han, Yeong-Deok; Bae, Joonwoo; Wang Xiangbin; Hwang, Won-Young

    2010-01-01

    A simple derivation of the optimal state estimation of a quantum bit was obtained by using the no-signaling principle. In particular, the no-signaling principle determines a unique form of the guessing probability independent of figures of merit, such as the fidelity or information gain. This proves that the optimal estimation for a quantum bit can be achieved by the same measurement for almost all figures of merit.

  11. State and Kinetic Parameters Estimation of Bio-Ethanol Production with Immobilized Cells

    OpenAIRE

    Mihaylova, Iva; Popova, Silviya; Kostov, Georgi; Ignatova, Maya; Lubenova, Velislava; Naydenova, Vessela; Pircheva, Desislava; Angelov, Mihail

    2013-01-01

    In this paper, state and kinetic parameters estimation based on extended Kalman filter (EKF) is proposed. Experimental data from alcoholic fermentation process with immobilized cells is used. The measurements of glucose and ethanol concentration are used as on-line measurements for observers design and biomass concentration is used for results verification. Biomass, substrate and product concentrations inside immobilized compounds are estimated using the proposed algorithm. Monitoring of the ...

  12. 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.

  13. Intelligence and education as predictors of cognitive state in late life: a 50-year follow-up.

    Science.gov (United States)

    Plassman, B L; Welsh, K A; Helms, M; Brandt, J; Page, W F; Breitner, J C

    1995-08-01

    We evaluated the relation of education and intelligence in early adult life to cognitive function in a group of elderly male twins. The Army General Classification Test (AGCT) was administered to US armed forces inductees in the early 1940s. Fifty years later, as part of a study of dementia in twins, we tested the cognitive status of 930 of these men using the modified Telephone Interview for Cognitive Status (TICS-m). TICS-m scores obtained in later life were correlated with AGCT scores (r = 0.457) and with years of education (r = 0.408). Thus, in univariate analyses, the AGCT score accounted for 20.6% and education accounted for 16.7% of variance in cognitive status. However, these two effects were not fully independent. A multivariable model using AGCT score, education, and the interaction of the two variables as predictors of the TICS-m score explained 24.8% of the variance, a slightly but significantly greater proportion than was explained by either factor alone. In a separate analysis based on 604 pairs of twins who took the AGCT, heritability of intelligence (estimated by AGCT score) was 0.503. Although this study does not address the issue of education and premorbid IQ as risk factors for dementia, the findings suggest that basic cognitive abilities in late life are related to cognitive performance measures from early adult life (ie, education and IQ).

  14. State of charge estimation for lithium-ion pouch batteries based on stress measurement

    International Nuclear Information System (INIS)

    Dai, Haifeng; Yu, Chenchen; Wei, Xuezhe; Sun, Zechang

    2017-01-01

    State of charge (SOC) estimation is one of the important tasks of battery management system (BMS). Being different from other researches, a novel method of SOC estimation for pouch lithium-ion battery cells based on stress measurement is proposed. With a comprehensive experimental study, we find that, the stress of the battery during charge/discharge is composed of the static stress and the dynamic stress. The static stress, which is the measured stress in equilibrium state, corresponds to SOC, this phenomenon facilitates the design of our stress-based SOC estimation. The dynamic stress, on the other hand, is influenced by multiple factors including charge accumulation or depletion, current and historical operation, thus a multiple regression model of the dynamic stress is established. Based on the relationship between static stress and SOC, as well as the dynamic stress modeling, the SOC estimation method is founded. Experimental results show that the stress-based method performs well with a good accuracy, and this method offers a novel perspective for SOC estimation. - Highlights: • A State of Charge estimator based on stress measurement is proposed. • The stress during charge and discharge is investigated with comprehensive experiments. • Effects of SOC, current, and operation history on battery stress are well studied. • A multiple regression model of the dynamic stress is established.

  15. 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.

  16. 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.

  17. 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.

  18. Towards a near infrared spectroscopy-based estimation of operator attentional state.

    Directory of Open Access Journals (Sweden)

    Gérard Derosière

    Full Text Available Given the critical risks to public health and safety that can involve lapses in attention (e.g., through implication in workplace accidents, researchers have sought to develop cognitive-state tracking technologies, capable of alerting individuals engaged in cognitively demanding tasks of potentially dangerous decrements in their levels of attention. The purpose of the present study was to address this issue through an investigation of the reliability of optical measures of cortical correlates of attention in conjunction with machine learning techniques to distinguish between states of full attention and states characterized by reduced attention capacity during a sustained attention task. Seven subjects engaged in a 30 minutes duration sustained attention reaction time task with near infrared spectroscopy (NIRS monitoring over the prefrontal and the right parietal areas. NIRS signals from the first 10 minutes of the task were considered as characterizing the 'full attention' class, while the NIRS signals from the last 10 minutes of the task were considered as characterizing the 'attention decrement' class. A two-class support vector machine algorithm was exploited to distinguish between the two levels of attention using appropriate NIRS-derived signal features. Attention decrement occurred during the task as revealed by the significant increase in reaction time in the last 10 compared to the first 10 minutes of the task (p<.05. The results demonstrate relatively good classification accuracy, ranging from 65 to 90%. The highest classification accuracy results were obtained when exploiting the oxyhemoglobin signals (i.e., from 77 to 89%, depending on the cortical area considered rather than the deoxyhemoglobin signals (i.e., from 65 to 66%. Moreover, the classification accuracy increased to 90% when using signals from the right parietal area rather than from the prefrontal cortex. The results support the feasibility of developing cognitive tracking

  19. Three screening methods for cognitive dysfunction using the Mini-Mental State Examination and Korean Dementia Screening Questionnaire.

    Science.gov (United States)

    Choi, Seong Hye; Park, Moon Ho

    2016-02-01

    To screen for and determine cognitive dysfunction, cognitive tests and/or informant reports are commonly used. However, these cognitive tests and informant reports are not always available. The present study investigated three screening methods using the Mini-Mental State Examination (MMSE) as the cognitive test, and the Korean dementia screening questionnaire (KDSQ) as the informant report. Participants were recruited from the Korea Clinical Research Center for Dementia of South Korea, and included 2861 patients with Alzheimer's disease (dementia), 3519 patients with mild cognitive impairment and 1375 controls with no cognitive dysfunction. Three screening methods were tested: (i) MMSE alone (MMSE(cut-off) ); (ii) a conventional combination of MMSE and KDSQ (MMSE+KDSQ(cut-off) ); and (iii) a decision tree with MMSE and KDSQ (MMSE+KDSQ(decision tree) ). For discriminating any cognitive dysfunction from controls, MMSE+KDSQ(cut-off) had the highest area under the receiver operating characteristic curve (0.784). For discriminating dementia from controls, MMSE+KDSQ(cut-off) had the highest area under the receiver operating characteristic curve (0.899). For discriminating mild cognitive impairment from controls, MMSE(cut-off) had the highest area under the receiver operating characteristic curve (0.683). MMSE+KDSQ(decision tree) showed the highest sensitivity for all discriminations. For overall classification accuracy, MMSE+KDSQ(decision tree) had the highest value (70.0%). These three methods had different advantageous properties for screening and staging cognitive dysfunction. As there might be different availability across clinical settings, these three methods can be selected and used according to situational needs. © 2015 Japan Geriatrics Society.

  20. 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.

  1. State of Charge Estimation for Lithium-Ion Battery with a Temperature-Compensated Model

    Directory of Open Access Journals (Sweden)

    Shichun Yang

    2017-10-01

    Full Text Available Accurate estimation of the state of charge (SOC of batteries is crucial in a battery management system. Many studies on battery SOC estimation have been investigated recently. Temperature is an important factor that affects the SOC estimation accuracy while it is still not adequately addressed at present. This paper proposes a SOC estimator based on a new temperature-compensated model with extended Kalman Filter (EKF. The open circuit voltage (OCV, capacity, and resistance and capacitance (RC parameters in the estimator are temperature dependent so that the estimator can maintain high accuracy at various temperatures. The estimation accuracy decreases when applied in high current continuous discharge, because the equivalent polarization resistance decreases as the discharge current increases. Therefore, a polarization resistance correction coefficient is proposed to tackle this problem. The estimator also demonstrates a good performance in dynamic operating conditions. However, the equivalent circuit model shows huge uncertainty in the low SOC region, so measurement noise variation is proposed to improve the estimation accuracy there.

  2. 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...

  3. Experimental study on the plant state estimation for the condition-based maintenance

    International Nuclear Information System (INIS)

    Harada, J. I.; Takahashi, M.; Kitamura, M.; Wakabayashi, T.

    2006-01-01

    A framework of maintenance support system based on the plant state estimation using diverse methods has been proposed and the validity of the plant state estimation methods has been experimentally evaluated. The focus has been set on the construction of the BN for the objective system with the scale and complexity as same as real world systems. Another focus has been set on the other functions for maintenance support system such as signal processing tool and similarity matching. The validity of the proposed inference method has been confirmed through numerical experiments. (authors)

  4. 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

  5. Optimal State Estimation for Discrete-Time Markov Jump Systems with Missing Observations

    Directory of Open Access Journals (Sweden)

    Qing Sun

    2014-01-01

    Full Text Available This paper is concerned with the optimal linear estimation for a class of direct-time Markov jump systems with missing observations. An observer-based approach of fault detection and isolation (FDI is investigated as a detection mechanic of fault case. For systems with known information, a conditional prediction of observations is applied and fault observations are replaced and isolated; then, an FDI linear minimum mean square error estimation (LMMSE can be developed by comprehensive utilizing of the correct information offered by systems. A recursive equation of filtering based on the geometric arguments can be obtained. Meanwhile, a stability of the state estimator will be guaranteed under appropriate assumption.

  6. Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Zhongyue Zou

    2014-08-01

    Full Text Available Four model-based State of Charge (SOC estimation methods for lithium-ion (Li-ion batteries are studied and evaluated in this paper. Different from existing literatures, this work evaluates different aspects of the SOC estimation, such as the estimation error distribution, the estimation rise time, the estimation time consumption, etc. The equivalent model of the battery is introduced and the state function of the model is deduced. The four model-based SOC estimation methods are analyzed first. Simulations and experiments are then established to evaluate the four methods. The urban dynamometer driving schedule (UDDS current profiles are applied to simulate the drive situations of an electrified vehicle, and a genetic algorithm is utilized to identify the model parameters to find the optimal parameters of the model of the Li-ion battery. The simulations with and without disturbance are carried out and the results are analyzed. A battery test workbench is established and a Li-ion battery is applied to test the hardware in a loop experiment. Experimental results are plotted and analyzed according to the four aspects to evaluate the four model-based SOC estimation methods.

  7. 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.

  8. Cognitive event-related potentials in comatose and post-comatose states.

    Science.gov (United States)

    Vanhaudenhuyse, Audrey; Laureys, Steven; Perrin, Fabien

    2008-01-01

    We review the interest of cognitive event-related potentials (ERPs) in comatose, vegetative, or minimally conscious patients. Auditory cognitive ERPs are useful to investigate residual cognitive functions, such as echoic memory (MMN), acoustical and semantic discrimination (P300), and incongruent language detection (N400). While early ERPs (such as the absence of cortical responses on somatosensory-evoked potentials) predict bad outcome, cognitive ERPs (MMN and P300) are indicative of recovery of consciousness. In coma-survivors, cognitive potentials are more frequently obtained when using stimuli that are more ecologic or have an emotional content (such as the patient's own name) than when using classical sine tones.

  9. 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

  10. 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.

  11. 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

  12. Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models.

    Science.gov (United States)

    Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

    2016-01-01

    Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization.

  13. PMU Placement Based on Heuristic Methods, when Solving the Problem of EPS State Estimation

    OpenAIRE

    I. N. Kolosok; E. S. Korkina; A. M. Glazunova

    2014-01-01

    Creation of satellite communication systems gave rise to a new generation of measurement equipment – Phasor Measurement Unit (PMU). Integrated into the measurement system WAMS, the PMU sensors provide a real picture of state of energy power system (EPS). The issues of PMU placement when solving the problem of EPS state estimation (SE) are discussed in many papers. PMU placement is a complex combinatorial problem, and there is not any analytical function to optimize its variables. Therefore,...

  14. On-line computer control of a nuclear reactor using optimal control and state estimation methods

    International Nuclear Information System (INIS)

    Tye, C.

    1980-01-01

    This paper describes the experimental implementation of a nuclear reactor control system using combined optimal state feedback based on the Quadratic Regulator and state estimation using Kalman filtering techniques. The results obtained from the experiments indicate that a reactor control loop designed using this approach has improved stability margins, greater speed of response and noise filtering properties compared with a conventional reactor control loop. 11 refs

  15. Reciprocal Estimation of Pedestrian Location and Motion State toward a Smartphone Geo-Context Computing Solution

    Directory of Open Access Journals (Sweden)

    Jingbin Liu

    2015-06-01

    Full Text Available The rapid advance in mobile communications has made information and services ubiquitously accessible. Location and context information have become essential for the effectiveness of services in the era of mobility. This paper proposes the concept of geo-context that is defined as an integral synthesis of geographical location, human motion state and mobility context. A geo-context computing solution consists of a positioning engine, a motion state recognition engine, and a context inference component. In the geo-context concept, the human motion states and mobility context are associated with the geographical location where they occur. A hybrid geo-context computing solution is implemented that runs on a smartphone, and it utilizes measurements of multiple sensors and signals of opportunity that are available within a smartphone. Pedestrian location and motion states are estimated jointly under the framework of hidden Markov models, and they are used in a reciprocal manner to improve their estimation performance of one another. It is demonstrated that pedestrian location estimation has better accuracy when its motion state is known, and in turn, the performance of motion state recognition can be improved with increasing reliability when the location is given. The geo-context inference is implemented simply with the expert system principle, and more sophisticated approaches will be developed.

  16. 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.

  17. Distribution-based estimates of minimum clinically important difference in cognition, arm function and lower body function after slow release-fampridine treatment of patients with multiple sclerosis

    DEFF Research Database (Denmark)

    Jensen, H B; Mamoei, Sepehr; Ravnborg, M.

    2016-01-01

    OBJECTIVE: To provide distribution-based estimates of the minimal clinical important difference (MCID) after slow release fampridine treatment on cognition and functional capacity in people with MS (PwMS). METHOD: MCID values were determined after SR-Fampridine treatment in 105 PwMS. Testing...

  18. 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

  19. 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.

  20. Motor, affective and cognitive empathy in adolescence : Interrelations between facial electromyography and self-reported trait and state measures

    NARCIS (Netherlands)

    Van der Graaff, Jolien; Meeus, Wim; de Wied, Minet; van Boxtel, Anton; van Lier, Pol A C; Koot, Hans M.; Branje, Susan J. T.

    2016-01-01

    This study examined interrelations of trait and state empathy in an adolescent sample. Self-reported affective trait empathy and cognitive trait empathy were assessed during a home visit. During a test session at the university, motor empathy (facial electromyography), and self-reported affective

  1. Generalizability of the Disease State Index Prediction Model for Identifying Patients Progressing from Mild Cognitive Impairment to Alzheimer's Disease

    NARCIS (Netherlands)

    Hall, A.; Munoz-Ruiz, M.; Mattila, J.; Koikkalainen, J.; Tsolaki, M.; Mecocci, P.; Kloszewska, I.; Vellas, B.; Lovestone, S.; Visser, P.J.; Lotjonen, J.; Soininen, H.

    2015-01-01

    Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. Objectives: We evaluated how well the DSI generalizes across

  2. A Test of Attention Control Theory in Public Speaking: Cognitive Load Influences the Relationship between State Anxiety and Verbal Production

    Science.gov (United States)

    King, Paul E.; Finn, Amber N.

    2017-01-01

    This study investigated the relationship between public-speaking state anxiety (PSA) and verbal communication performance when delivering a speech. In Study 1, participants delivered an extemporaneous five-minute classroom speech behind a lectern, and in Study 2, to increase cognitive load, participants delivered an extemporaneous five-minute…

  3. The cumulative load of depressive illness is associated with cognitive function in the remitted state of unipolar depressive disorder

    DEFF Research Database (Denmark)

    Hasselbalch, Jacob; Knorr, U; Hasselbalch, S G

    2013-01-01

    OBJECTIVE: To investigate whether the cumulative number, duration and subtypes (severity and presence of psychotic features) of previous episodes of depression in patients with unipolar depressive disorder in a remitted state are associated with decreased global cognitive function. METHODS: Via t...

  4. Relationships among Career and Life Stress, Negative Career thoughts, and Career Decision State: A Cognitive Information Processing Perspective

    Science.gov (United States)

    Bullock-Yowell, Emily; Peterson, Gary W.; Reardon, Robert C.; Leierer, Stephen J.; Reed, Corey A.

    2011-01-01

    According to cognitive information processing theory, career thoughts mediate the relationship between career and life stress and the ensuing career decision state. Using a sample of 232 college students and structural equation modeling, this study found that an increase in career and life stress was associated with an increase in negative career…

  5. 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.

  6. 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.

  7. Estimation of hand index for male industrial workers of Haryana State

    African Journals Online (AJOL)

    Hand index derived from measured hand dimensions can be used to estimate differences related to sex, age and race in forensic and legal sciences. It has been calculated as percentage of hand breadth over the hand length; which suggests that the male industrial workers population of state belong to mesocheir group of ...

  8. Application of Joint Parameter Identification and State Estimation to a Fault-Tolerant Robot System

    DEFF Research Database (Denmark)

    Sun, Zhen; Yang, Zhenyu

    2011-01-01

    The joint parameter identification and state estimation technique is applied to develop a fault-tolerant space robot system. The potential faults in the considered system are abrupt parametric faults, which indicate that some system parameters will immediately deviate from their nominal values...

  9. 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.

  10. State Estimation for Linear Systems Driven Simultaneously by Wiener and Poisson Processes.

    Science.gov (United States)

    1978-12-01

    The state estimation problem of linear stochastic systems driven simultaneously by Wiener and Poisson processes is considered, especially the case...where the incident intensities of the Poisson processes are low and the system is observed in an additive white Gaussian noise. The minimum mean squared

  11. Wheeled vehicle deceleration as estimation parameter of adaptive brake control system state

    Directory of Open Access Journals (Sweden)

    Turenko A.

    2012-06-01

    Full Text Available The method of stability estimation of adaptive control system with signal adjustment based on Lyapunov’s direct method that allows to take into account the nonstationarity of the basic system and non-linearity in the form of limitation on control action restriction as well as error control is stated.

  12. Power system observability and dynamic state estimation for stability monitoring using synchrophasor measurements

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Kai; Qi, Junjian; Kang, Wei

    2016-08-01

    Growing penetration of intermittent resources such as renewable generations increases the risk of instability in a power grid. This paper introduces the concept of observability and its computational algorithms for a power grid monitored by the wide-area measurement system (WAMS) based on synchrophasors, e.g. phasor measurement units (PMUs). The goal is to estimate real-time states of generators, especially for potentially unstable trajectories, the information that is critical for the detection of rotor angle instability of the grid. The paper studies the number and siting of synchrophasors in a power grid so that the state of the system can be accurately estimated in the presence of instability. An unscented Kalman filter (UKF) is adopted as a tool to estimate the dynamic states that are not directly measured by synchrophasors. The theory and its computational algorithms are illustrated in detail by using a 9-bus 3-generator power system model and then tested on a 140-bus 48-generator Northeast Power Coordinating Council power grid model. Case studies on those two systems demonstrate the performance of the proposed approach using a limited number of synchrophasors for dynamic state estimation for stability assessment and its robustness against moderate inaccuracies in model parameters.

  13. State and parameter estimation in a nuclear fuel pin using the extended Kalman filter

    International Nuclear Information System (INIS)

    Feeley, J.J.

    1979-03-01

    The Kalman filter is a powerful tool for the design and analysis of stochastic systems. The general nature of the method permits such diverse applications as on-line state estimation in optimal control systems, as well as state and parameter estimation applications in data analysis and system identification. However, while there have been a large number of Kalman filter applications in the aerospace industry, there have been relatively few in the nuclear industry. The report describes some initial efforts made at the Idaho National Engineering Laboratory to gain experience with the methods of Kalman filtering and to test their applicability to nuclear engineering problems. Two specific cases were considered: first, a real-time state estimation problem using a hybrid computer where the process was simulated on the analog portion of the computer, and the Kalman filter was programmed on the digital portion; second, a system identification problem where a digital extended Kalman filter program was used to estimate states and parameters in a nuclear fuel pin using data generated both by actual experiments and computer simulations. The report contains a derivation of the Kalman filter equations, a development of the mathematical model of the nuclear fuel pin, a description of the computer programs used in the analysis, and a discussion of the results obtained

  14. 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.

  15. Comparisons of Means for Estimating Sea States from an Advancing Large Container Ship

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Andersen, Ingrid Marie Vincent; Koning, Jos

    2013-01-01

    to ship-wave interactions in a seaway. In the paper, sea state estimates are produced by three means: the wave buoy analogy, relying on shipboard response measurements, a wave radar system, and a system providing the instantaneous wave height. The presented results show that for the given data, recorded...

  16. Estimates of Annual Soil Loss Rates in the State of São Paulo, Brazil

    Directory of Open Access Journals (Sweden)

    Grasiela de Oliveira Rodrigues Medeiros

    Full Text Available ABSTRACT: Soil is a natural resource that has been affected by human pressures beyond its renewal capacity. For this reason, large agricultural areas that were productive have been abandoned due to soil degradation, mainly caused by the erosion process. The objective of this study was to apply the Universal Soil Loss Equation to generate more recent estimates of soil loss rates for the state of São Paulo using a database with information from medium resolution (30 m. The results showed that many areas of the state have high (critical levels of soil degradation due to the predominance of consolidated human activities, especially in growing sugarcane and pasture use. The average estimated rate of soil loss is 30 Mg ha-1 yr-1 and 59 % of the area of the state (except for water bodies and urban areas had estimated rates above 12 Mg ha-1 yr-1, considered as the average tolerance limit in the literature. The average rates of soil loss in areas with annual agricultural crops, semi-perennial agricultural crops (sugarcane, and permanent agricultural crops were 118, 78, and 38 Mg ha-1 yr-1 respectively. The state of São Paulo requires attention to conservation of soil resources, since most soils led to estimates beyond the tolerance limit.

  17. Improved Stewart platform state estimation using inertial and actuator position measurements

    NARCIS (Netherlands)

    MiletoviC, I.; Pool, D.M.; Stroosma, O.; van Paassen, M.M.; Chu, Q.

    2017-01-01

    Accurate and reliable estimation of the kinematic state of a six degrees-of-freedom Stewart platform is a problem of interest in various engineering disciplines. Particularly so in the area of flight simulation, where the Stewart platform is in widespread use for the generation of motion similar

  18. The Wegner Estimate and the Integrated Density of States for some ...

    Indian Academy of Sciences (India)

    The integrated density of states (IDS) for random operators is an important function describing many physical characteristics of a random system. Properties of the IDS are derived from the Wegner estimate that describes the influence of finite-volume perturbations on a background system. In this paper, we present a simple ...

  19. Joint Parametric Fault Diagnosis and State Estimation Using KF-ML Method

    DEFF Research Database (Denmark)

    Sun, Zhen; Yang, Zhenyu

    2014-01-01

    The paper proposes a new method for a kind of parametric fault online diagnosis with state estimation jointly. The considered fault affects not only the deterministic part of the system but also the random circumstance. The proposed method first applies Kalman Filter (KF) and Maximum Likelihood (...

  20. Burden of Severe Pneumonia, Pneumococcal Pneumonia and Pneumonia Deaths in Indian States: Modelling Based Estimates.

    Science.gov (United States)

    Farooqui, Habib; Jit, Mark; Heymann, David L; Zodpey, Sanjay

    2015-01-01

    The burden of severe pneumonia in terms of morbidity and mortality is unknown in India especially at sub-national level. In this context, we aimed to estimate the number of severe pneumonia episodes, pneumococcal pneumonia episodes and pneumonia deaths in children younger than 5 years in 2010. We adapted and parameterized a mathematical model based on the epidemiological concept of potential impact fraction developed CHERG for this analysis. The key parameters that determine the distribution of severe pneumonia episode across Indian states were state-specific under-5 population, state-specific prevalence of selected definite pneumonia risk factors and meta-estimates of relative risks for each of these risk factors. We applied the incidence estimates and attributable fraction of risk factors to population estimates for 2010 of each Indian state. We then estimated the number of pneumococcal pneumonia cases by applying the vaccine probe methodology to an existing trial. We estimated mortality due to severe pneumonia and pneumococcal pneumonia by combining incidence estimates with case fatality ratios from multi-centric hospital-based studies. Our results suggest that in 2010, 3.6 million (3.3-3.9 million) episodes of severe pneumonia and 0.35 million (0.31-0.40 million) all cause pneumonia deaths occurred in children younger than 5 years in India. The states that merit special mention include Uttar Pradesh where 18.1% children reside but contribute 24% of pneumonia cases and 26% pneumonia deaths, Bihar (11.3% children, 16% cases, 22% deaths) Madhya Pradesh (6.6% children, 9% cases, 12% deaths), and Rajasthan (6.6% children, 8% cases, 11% deaths). Further, we estimated that 0.56 million (0.49-0.64 million) severe episodes of pneumococcal pneumonia and 105 thousand (92-119 thousand) pneumococcal deaths occurred in India. The top contributors to India's pneumococcal pneumonia burden were Uttar Pradesh, Bihar, Madhya Pradesh and Rajasthan in that order. Our results

  1. Burden of Severe Pneumonia, Pneumococcal Pneumonia and Pneumonia Deaths in Indian States: Modelling Based Estimates.

    Directory of Open Access Journals (Sweden)

    Habib Farooqui

    Full Text Available The burden of severe pneumonia in terms of morbidity and mortality is unknown in India especially at sub-national level. In this context, we aimed to estimate the number of severe pneumonia episodes, pneumococcal pneumonia episodes and pneumonia deaths in children younger than 5 years in 2010. We adapted and parameterized a mathematical model based on the epidemiological concept of potential impact fraction developed CHERG for this analysis. The key parameters that determine the distribution of severe pneumonia episode across Indian states were state-specific under-5 population, state-specific prevalence of selected definite pneumonia risk factors and meta-estimates of relative risks for each of these risk factors. We applied the incidence estimates and attributable fraction of risk factors to population estimates for 2010 of each Indian state. We then estimated the number of pneumococcal pneumonia cases by applying the vaccine probe methodology to an existing trial. We estimated mortality due to severe pneumonia and pneumococcal pneumonia by combining incidence estimates with case fatality ratios from multi-centric hospital-based studies. Our results suggest that in 2010, 3.6 million (3.3-3.9 million episodes of severe pneumonia and 0.35 million (0.31-0.40 million all cause pneumonia deaths occurred in children younger than 5 years in India. The states that merit special mention include Uttar Pradesh where 18.1% children reside but contribute 24% of pneumonia cases and 26% pneumonia deaths, Bihar (11.3% children, 16% cases, 22% deaths Madhya Pradesh (6.6% children, 9% cases, 12% deaths, and Rajasthan (6.6% children, 8% cases, 11% deaths. Further, we estimated that 0.56 million (0.49-0.64 million severe episodes of pneumococcal pneumonia and 105 thousand (92-119 thousand pneumococcal deaths occurred in India. The top contributors to India's pneumococcal pneumonia burden were Uttar Pradesh, Bihar, Madhya Pradesh and Rajasthan in that order. Our

  2. Burden of Severe Pneumonia, Pneumococcal Pneumonia and Pneumonia Deaths in Indian States: Modelling Based Estimates

    Science.gov (United States)

    Farooqui, Habib; Jit, Mark; Heymann, David L.; Zodpey, Sanjay

    2015-01-01

    The burden of severe pneumonia in terms of morbidity and mortality is unknown in India especially at sub-national level. In this context, we aimed to estimate the number of severe pneumonia episodes, pneumococcal pneumonia episodes and pneumonia deaths in children younger than 5 years in 2010. We adapted and parameterized a mathematical model based on the epidemiological concept of potential impact fraction developed CHERG for this analysis. The key parameters that determine the distribution of severe pneumonia episode across Indian states were state-specific under-5 population, state-specific prevalence of selected definite pneumonia risk factors and meta-estimates of relative risks for each of these risk factors. We applied the incidence estimates and attributable fraction of risk factors to population estimates for 2010 of each Indian state. We then estimated the number of pneumococcal pneumonia cases by applying the vaccine probe methodology to an existing trial. We estimated mortality due to severe pneumonia and pneumococcal pneumonia by combining incidence estimates with case fatality ratios from multi-centric hospital-based studies. Our results suggest that in 2010, 3.6 million (3.3–3.9 million) episodes of severe pneumonia and 0.35 million (0.31–0.40 million) all cause pneumonia deaths occurred in children younger than 5 years in India. The states that merit special mention include Uttar Pradesh where 18.1% children reside but contribute 24% of pneumonia cases and 26% pneumonia deaths, Bihar (11.3% children, 16% cases, 22% deaths) Madhya Pradesh (6.6% children, 9% cases, 12% deaths), and Rajasthan (6.6% children, 8% cases, 11% deaths). Further, we estimated that 0.56 million (0.49–0.64 million) severe episodes of pneumococcal pneumonia and 105 thousand (92–119 thousand) pneumococcal deaths occurred in India. The top contributors to India’s pneumococcal pneumonia burden were Uttar Pradesh, Bihar, Madhya Pradesh and Rajasthan in that order. Our

  3. Estimation of Nonlinear Functions of State Vector for Linear Systems with Time-Delays and Uncertainties

    Directory of Open Access Journals (Sweden)

    Il Young Song

    2015-01-01

    Full Text Available This paper focuses on estimation of a nonlinear function of state vector (NFS in discrete-time linear systems with time-delays and model uncertainties. The NFS represents a multivariate nonlinear function of state variables, which can indicate useful information of a target system for control. The optimal nonlinear estimator of an NFS (in mean square sense represents a function of the receding horizon estimate and its error covariance. The proposed receding horizon filter represents the standard Kalman filter with time-delays and special initial horizon conditions described by the Lyapunov-like equations. In general case to calculate an optimal estimator of an NFS we propose using the unscented transformation. Important class of polynomial NFS is considered in detail. In the case of polynomial NFS an optimal estimator has a closed-form computational procedure. The subsequent application of the proposed receding horizon filter and nonlinear estimator to a linear stochastic system with time-delays and uncertainties demonstrates their effectiveness.

  4. Comparative Study Between Internal Ohmic Resistance and Capacity for Battery State of Health Estimation

    Directory of Open Access Journals (Sweden)

    M. Nisvo Ramadan

    2015-12-01

    Full Text Available In order to avoid battery failure, a battery management system (BMS is necessary. Battery state of charge (SOC and state of health (SOH are part of information provided by a BMS. This research analyzes methods to estimate SOH based lithium polymer battery on change of its internal resistance and its capacity. Recursive least square (RLS algorithm was used to estimate internal ohmic resistance while coloumb counting was used to predict the change in the battery capacity. For the estimation algorithm, the battery terminal voltage and current are set as the input variables. Some tests including static capacity test, pulse test, pulse variation test and before charge-discharge test have been conducted to obtain the required data. After comparing the two methods, the obtained results show that SOH estimation based on coloumb counting provides better accuracy than SOH estimation based on internal ohmic resistance. However, the SOH estimation based on internal ohmic resistance is faster and more reliable for real application

  5. Composing problem solvers for simulation experimentation: a case study on steady state estimation.

    Science.gov (United States)

    Leye, Stefan; Ewald, Roland; Uhrmacher, Adelinde M

    2014-01-01

    Simulation experiments involve various sub-tasks, e.g., parameter optimization, simulation execution, or output data analysis. Many algorithms can be applied to such tasks, but their performance depends on the given problem. Steady state estimation in systems biology is a typical example for this: several estimators have been proposed, each with its own (dis-)advantages. Experimenters, therefore, must choose from the available options, even though they may not be aware of the consequences. To support those users, we propose a general scheme to aggregate such algorithms to so-called synthetic problem solvers, which exploit algorithm differences to improve overall performance. Our approach subsumes various aggregation mechanisms, supports automatic configuration from training data (e.g., via ensemble learning or portfolio selection), and extends the plugin system of the open source modeling and simulation framework James II. We show the benefits of our approach by applying it to steady state estimation for cell-biological models.

  6. 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)

  7. Estimation of time- and state-dependent delays and other parameters in functional differential equations

    Science.gov (United States)

    Murphy, K. A.

    1990-01-01

    A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

  8. Least mean square fourth based microgrid state estimation algorithm using the internet of things technology.

    Science.gov (United States)

    Rana, Md Masud

    2017-01-01

    This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.

  9. Least mean square fourth based microgrid state estimation algorithm using the internet of things technology.

    Directory of Open Access Journals (Sweden)

    Md Masud Rana

    Full Text Available This paper proposes an innovative internet of things (IoT based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.

  10. 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...

  11. 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

  12. Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

    Science.gov (United States)

    El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

    2016-02-01

    Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate

  13. Real-time muscle state estimation from EMG signals during isometric contractions using Kalman filters.

    Science.gov (United States)

    Menegaldo, Luciano L

    2017-12-01

    State-space control of myoelectric devices and real-time visualization of muscle forces in virtual rehabilitation require measuring or estimating muscle dynamic states: neuromuscular activation, tendon force and muscle length. This paper investigates whether regular (KF) and extended Kalman filters (eKF), derived directly from Hill-type muscle mechanics equations, can be used as real-time muscle state estimators for isometric contractions using raw electromyography signals (EMG) as the only available measurement. The estimators' amplitude error, computational cost, filtering lags and smoothness are compared with usual EMG-driven analysis, performed offline, by integrating the nonlinear Hill-type muscle model differential equations (offline simulations-OS). EMG activity of the three triceps surae components (soleus, gastrocnemius medialis and gastrocnemius lateralis), in three torque levels, was collected for ten subjects. The actualization interval (AI) between two updates of the KF and eKF was also varied. The results show that computational costs are significantly reduced (70x for KF and 17[Formula: see text] for eKF). The filtering lags presented sharp linear relationships with the AI (0-300 ms), depending on the state and activation level. Under maximum excitation, amplitude errors varied in the range 10-24% for activation, 5-8% for tendon force and 1.4-1.8% for muscle length, reducing linearly with the excitation level. Smoothness, measured by the ratio between the average standard variations of KF/eKF and OS estimations, was greatly reduced for activation but converged exponentially to 1 for the other states by increasing AI. Compared to regular KF, extended KF does not seem to improve estimation accuracy significantly. Depending on the particular application requirements, the most appropriate KF actualization interval can be selected.

  14. 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.

  15. OCCIPITAL SOURCES OF RESTING STATE ALPHA RHYTHMS ARE RELATED TO LOCAL GRAY MATTER DENSITY IN SUBJECTS WITH AMNESIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DISEASE

    Science.gov (United States)

    Claudio, Babiloni; Claudio, Del Percio; Marina, Boccardi; Roberta, Lizio; Susanna, Lopez; Filippo, Carducci; Nicola, Marzano; Andrea, Soricelli; Raffaele, Ferri; Ivano, Triggiani Antonio; Annapaola, Prestia; Serenella, Salinari; Rasser Paul, E; Erol, Basar; Francesco, Famà; Flavio, Nobili; Görsev, Yener; Durusu, Emek-Savaş Derya; Gesualdo, Loreto; Ciro, Mundi; Thompson Paul, M; Rossini Paolo, M.; Frisoni Giovanni, B

    2014-01-01

    Occipital sources of resting state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Here we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging (MRI). Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density (GMD), estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8–10.5 Hz) and alpha 2 (10.5–13 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic tomography (LORETA). Results showed a positive correlation between occipital GMD and amplitude of occipital alpha 1 sources in Nold, MCI and AD subjects as a whole group (r=0.3, p=0.000004, N=235). Furthermore, there was a positive correlation between amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Evaluation (MMSE) score across all subjects (r=0.38, p=0.000001, N=235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the Receiver Operating Characteristic (ROC) curve: 0.81). These results suggest that the amplitude of occipital sources of resting state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathological aging. PMID:25442118

  16. Improving Google Flu Trends estimates for the United States through transformation.

    Directory of Open Access Journals (Sweden)

    Leah J Martin

    Full Text Available Google Flu Trends (GFT uses Internet search queries in an effort to provide early warning of increases in influenza-like illness (ILI. In the United States, GFT estimates the percentage of physician visits related to ILI (%ILINet reported by the Centers for Disease Control and Prevention (CDC. However, during the 2012-13 influenza season, GFT overestimated %ILINet by an appreciable amount and estimated the peak in incidence three weeks late. Using data from 2010-14, we investigated the relationship between GFT estimates (%GFT and %ILINet. Based on the relationship between the relative change in %GFT and the relative change in %ILINet, we transformed %GFT estimates to better correspond with %ILINet values. In 2010-13, our transformed %GFT estimates were within ± 10% of %ILINet values for 17 of the 29 weeks that %ILINet was above the seasonal baseline value determined by the CDC; in contrast, the original %GFT estimates were within ± 10% of %ILINet values for only two of these 29 weeks. Relative to the %ILINet peak in 2012-13, the peak in our transformed %GFT estimates was 2% lower and one week later, whereas the peak in the original %GFT estimates was 74% higher and three weeks later. The same transformation improved %GFT estimates using the recalibrated 2013 GFT model in early 2013-14. Our transformed %GFT estimates can be calculated approximately one week before %ILINet values are reported by the CDC and the transformation equation was stable over the time period investigated (2010-13. We anticipate our results will facilitate future use of GFT.

  17. Estimate of the area occupied by reforestation programs in Rio de Janeiro state

    Directory of Open Access Journals (Sweden)

    Hugo Barbosa Amorim

    2012-03-01

    Full Text Available This study was based on a preliminary survey and inventory of existing reforestation programs in Rio de Janeiro state, through geoprocessing techniques and collection of field data. The reforested area was found to occupy 18,426.96 ha, which amounts to 0.42% of the territory of the state. Much of reforestation programs consists of eucalyptus (98%, followed by pine plantations (0.8%, and the remainder is distributed among 10 other species. The Médio Paraíba region was found to contribute the most to the reforested area of the state (46.6%. The estimated volume of eucalyptus timber was nearly two million cubic meters. This study helped crystallize the ongoing perception among those militating in the forestry sector of Rio de Janeiro state that the planted area and stock of reforestation timber is still incipient in the state.

  18. Estimating tag loss of the Atlantic Horseshoe crab, Limulus polyphemus, using a multi-state model

    Science.gov (United States)

    Butler, Catherine Alyssa; McGowan, Conor P.; Grand, James B.; Smith, David

    2012-01-01

    The Atlantic Horseshoe crab, Limulus polyphemus, is a valuable resource along the Mid-Atlantic coast which has, in recent years, experienced new management paradigms due to increased concern about this species role in the environment. While current management actions are underway, many acknowledge the need for improved and updated parameter estimates to reduce the uncertainty within the management models. Specifically, updated and improved estimates of demographic parameters such as adult crab survival in the regional population of interest, Delaware Bay, could greatly enhance these models and improve management decisions. There is however, some concern that difficulties in tag resighting or complete loss of tags could be occurring. As apparent from the assumptions of a Jolly-Seber model, loss of tags can result in a biased estimate and underestimate a survival rate. Given that uncertainty, as a first step towards estimating an unbiased estimate of adult survival, we first took steps to estimate the rate of tag loss. Using data from a double tag mark-resight study conducted in Delaware Bay and Program MARK, we designed a multi-state model to allow for the estimation of mortality of each tag separately and simultaneously.

  19. An adaptive state of charge estimation approach for lithium-ion series-connected battery system

    Science.gov (United States)

    Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael

    2018-07-01

    Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.

  20. Economic productivity by age and sex: 2007 estimates for the United States.

    Science.gov (United States)

    Grosse, Scott D; Krueger, Kurt V; Mvundura, Mercy

    2009-07-01

    Human capital estimates of labor productivity are often used to estimate the economic impact of diseases and injuries that cause incapacitation or death. Estimates of average hourly, annual, and lifetime economic productivity, both market and household, were calculated in 2007 US dollars for 5-year age groups for men, women, and both sexes in the United States. Data from the American Time Use Survey were used to estimate hours of paid work and household services and hourly and annual earnings and household productivity. Present values of discounted lifetime earnings were calculated for each age group using the 2004 US life tables and a discount rate of 3% per year and assuming future productivity growth of 1% per year. The estimates of hours and productivity were calculated using the time diaries of 72,922 persons included in the American Time Use Survey for the years 2003 to 2007. The present value of lifetime productivity is approximately $1.2 million in 2007 dollars for children under 5 years of age. For adults in their 20s and 30s, it is approximately $1.6 million and then it declines with increasing age. Productivity estimates are higher for males than for females, more for market productivity than for total productivity. Changes in hours of paid employment and household services can affect economic productivity by age and sex. This is the first publication to include estimates of household services based on contemporary time use data for the US population.

  1. A framework for estimating health state utility values within a discrete choice experiment: modeling risky choices.

    Science.gov (United States)

    Robinson, Angela; Spencer, Anne; Moffatt, Peter

    2015-04-01

    There has been recent interest in using the discrete choice experiment (DCE) method to derive health state utilities for use in quality-adjusted life year (QALY) calculations, but challenges remain. We set out to develop a risk-based DCE approach to derive utility values for health states that allowed 1) utility values to be anchored directly to normal health and death and 2) worse than dead health states to be assessed in the same manner as better than dead states. Furthermore, we set out to estimate alternative models of risky choice within a DCE model. A survey was designed that incorporated a risk-based DCE and a "modified" standard gamble (SG). Health state utility values were elicited for 3 EQ-5D health states assuming "standard" expected utility (EU) preferences. The DCE model was then generalized to allow for rank-dependent expected utility (RDU) preferences, thereby allowing for probability weighting. A convenience sample of 60 students was recruited and data collected in small groups. Under the assumption of "standard" EU preferences, the utility values derived within the DCE corresponded fairly closely to the mean results from the modified SG. Under the assumption of RDU preferences, the utility values estimated are somewhat lower than under the assumption of standard EU, suggesting that the latter may be biased upward. Applying the correct model of risky choice is important whether a modified SG or a risk-based DCE is deployed. It is, however, possible to estimate a probability weighting function within a DCE and estimate "unbiased" utility values directly, which is not possible within a modified SG. We conclude by setting out the relative strengths and weaknesses of the 2 approaches in this context. © The Author(s) 2014.

  2. Bridging cognitive screening tests in neurologic disorders: A crosswalk between the short Montreal Cognitive Assessment and Mini-Mental State Examination.

    Science.gov (United States)

    Roalf, David R; Moore, Tyler M; Mechanic-Hamilton, Dawn; Wolk, David A; Arnold, Steven E; Weintraub, Daniel A; Moberg, Paul J

    2017-08-01

    To provide a crosswalk between the recently proposed short Montreal Cognitive Assessment (s-MoCA) and Mini-Mental State Examination (MMSE) within a clinical cohort. A total of 791 participants, with and without neurologic conditions, received both the MMSE and the MoCA at the same visit. s-MoCA scores were calculated and equipercentile equating was used to create a crosswalk between the s-MoCA and MMSE. As expected, s-MoCA scores were highly correlated (Pearson r = 0.82, P < .001) with MMSE scores. s-MoCA scores correctly classified 85% of healthy older adults and 91% of individuals with neurologic conditions that impair cognition. In addition, we provide an easy to use table that enables the conversion of s-MoCA score to MMSE score. The s-MoCA is quick to administer, provides high sensitivity and specificity for cognitive impairment, and now can be compared directly with the MMSE. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  3. An approach for estimating item sensitivity to within-person change over time: An illustration using the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog).

    Science.gov (United States)

    Dowling, N Maritza; Bolt, Daniel M; Deng, Sien

    2016-12-01

    When assessments are primarily used to measure change over time, it is important to evaluate items according to their sensitivity to change, specifically. Items that demonstrate good sensitivity to between-person differences at baseline may not show good sensitivity to change over time, and vice versa. In this study, we applied a longitudinal factor model of change to a widely used cognitive test designed to assess global cognitive status in dementia, and contrasted the relative sensitivity of items to change. Statistically nested models were estimated introducing distinct latent factors related to initial status differences between test-takers and within-person latent change across successive time points of measurement. Models were estimated using all available longitudinal item-level data from the Alzheimer's Disease Assessment Scale-Cognitive subscale, including participants representing the full-spectrum of disease status who were enrolled in the multisite Alzheimer's Disease Neuroimaging Initiative. Five of the 13 Alzheimer's Disease Assessment Scale-Cognitive items demonstrated noticeably higher loadings with respect to sensitivity to change. Attending to performance change on only these 5 items yielded a clearer picture of cognitive decline more consistent with theoretical expectations in comparison to the full 13-item scale. Items that show good psychometric properties in cross-sectional studies are not necessarily the best items at measuring change over time, such as cognitive decline. Applications of the methodological approach described and illustrated in this study can advance our understanding regarding the types of items that best detect fine-grained early pathological changes in cognition. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  4. 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...

  5. A novel approach of battery pack state of health estimation using artificial intelligence optimization algorithm

    Science.gov (United States)

    Zhang, Xu; Wang, Yujie; Liu, Chang; Chen, Zonghai

    2018-02-01

    An accurate battery pack state of health (SOH) estimation is important to characterize the dynamic responses of battery pack and ensure the battery work with safety and reliability. However, the different performances in battery discharge/charge characteristics and working conditions in battery pack make the battery pack SOH estimation difficult. In this paper, the battery pack SOH is defined as the change of battery pack maximum energy storage. It contains all the cells' information including battery capacity, the relationship between state of charge (SOC) and open circuit voltage (OCV), and battery inconsistency. To predict the battery pack SOH, the method of particle swarm optimization-genetic algorithm is applied in battery pack model parameters identification. Based on the results, a particle filter is employed in battery SOC and OCV estimation to avoid the noise influence occurring in battery terminal voltage measurement and current drift. Moreover, a recursive least square method is used to update cells' capacity. Finally, the proposed method is verified by the profiles of New European Driving Cycle and dynamic test profiles. The experimental results indicate that the proposed method can estimate the battery states with high accuracy for actual operation. In addition, the factors affecting the change of SOH is analyzed.

  6. A state-space model for estimating detailed movements and home range from acoustic receiver data

    DEFF Research Database (Denmark)

    Pedersen, Martin Wæver; Weng, Kevin

    2013-01-01

    We present a state-space model for acoustic receiver data to estimate detailed movement and home range of individual fish while accounting for spatial bias. An integral part of the approach is the detection function, which models the probability of logging tag transmissions as a function of dista......We present a state-space model for acoustic receiver data to estimate detailed movement and home range of individual fish while accounting for spatial bias. An integral part of the approach is the detection function, which models the probability of logging tag transmissions as a function...... that the location error scales log-linearly with detection range and movement speed. This result can be used as guideline for designing network layout when species movement capacity and acoustic environment are known or can be estimated prior to network deployment. Finally, as an example, the state-space model...... is used to estimate home range and movement of a reef fish in the Pacific Ocean....

  7. Estimating the State of Aerodynamic Flows in the Presence of Modeling Errors

    Science.gov (United States)

    da Silva, Andre F. C.; Colonius, Tim

    2017-11-01

    The ensemble Kalman filter (EnKF) has been proven to be successful in fields such as meteorology, in which high-dimensional nonlinear systems render classical estimation techniques impractical. When the model used to forecast state evolution misrepresents important aspects of the true dynamics, estimator performance may degrade. In this work, parametrization and state augmentation are used to track misspecified boundary conditions (e.g., free stream perturbations). The resolution error is modeled as a Gaussian-distributed random variable with the mean (bias) and variance to be determined. The dynamics of the flow past a NACA 0009 airfoil at high angles of attack and moderate Reynolds number is represented by a Navier-Stokes equations solver with immersed boundaries capabilities. The pressure distribution on the airfoil or the velocity field in the wake, both randomized by synthetic noise, are sampled as measurement data and incorporated into the estimated state and bias following Kalman's analysis scheme. Insights about how to specify the modeling error covariance matrix and its impact on the estimator performance are conveyed. This work has been supported in part by a Grant from AFOSR (FA9550-14-1-0328) with Dr. Douglas Smith as program manager, and by a Science without Borders scholarship from the Ministry of Education of Brazil (Capes Foundation - BEX 12966/13-4).

  8. State and parameter estimation of the heat shock response system using Kalman and particle filters.

    Science.gov (United States)

    Liu, Xin; Niranjan, Mahesan

    2012-06-01

    Traditional models of systems biology describe dynamic biological phenomena as solutions to ordinary differential equations, which, when parameters in them are set to correct values, faithfully mimic observations. Often parameter values are tweaked by hand until desired results are achieved, or computed from biochemical experiments carried out in vitro. Of interest in this article, is the use of probabilistic modelling tools with which parameters and unobserved variables, modelled as hidden states, can be estimated from limited noisy observations of parts of a dynamical system. Here we focus on sequential filtering methods and take a detailed look at the capabilities of three members of this family: (i) extended Kalman filter (EKF), (ii) unscented Kalman filter (UKF) and (iii) the particle filter, in estimating parameters and unobserved states of cellular response to sudden temperature elevation of the bacterium Escherichia coli. While previous literature has studied this system with the EKF, we show that parameter estimation is only possible with this method when the initial guesses are sufficiently close to the true values. The same turns out to be true for the UKF. In this thorough empirical exploration, we show that the non-parametric method of particle filtering is able to reliably estimate parameters and states, converging from initial distributions relatively far away from the underlying true values. Software implementation of the three filters on this problem can be freely downloaded from http://users.ecs.soton.ac.uk/mn/HeatShock

  9. 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...

  10. Estimates of the Size and Characteristics of the Resident Nonimmigrant Population in the United States: January 2011

    Data.gov (United States)

    Department of Homeland Security — This report presents estimates of the size and characteristics of the resident nonimmigrant population in the United States. The estimates are daily averages for the...

  11. Parameter and state estimation in a Neisseria meningitidis model: A study case of Niger

    Science.gov (United States)

    Bowong, S.; Mountaga, L.; Bah, A.; Tewa, J. J.; Kurths, J.

    2016-12-01

    Neisseria meningitidis (Nm) is a major cause of bacterial meningitidis outbreaks in Africa and the Middle East. The availability of yearly reported meningitis cases in the African meningitis belt offers the opportunity to analyze the transmission dynamics and the impact of control strategies. In this paper, we propose a method for the estimation of state variables that are not accessible to measurements and an unknown parameter in a Nm model. We suppose that the yearly number of Nm induced mortality and the total population are known inputs, which can be obtained from data, and the yearly number of new Nm cases is the model output. We also suppose that the Nm transmission rate is an unknown parameter. We first show how the recruitment rate into the population can be estimated using real data of the total population and Nm induced mortality. Then, we use an auxiliary system called observer whose solutions converge exponentially to those of the original model. This observer does not use the unknown infection transmission rate but only uses the known inputs and the model output. This allows us to estimate unmeasured state variables such as the number of carriers that play an important role in the transmission of the infection and the total number of infected individuals within a human community. Finally, we also provide a simple method to estimate the unknown Nm transmission rate. In order to validate the estimation results, numerical simulations are conducted using real data of Niger.

  12. Novel methods for estimating lithium-ion battery state of energy and maximum available energy

    International Nuclear Information System (INIS)

    Zheng, Linfeng; Zhu, Jianguo; Wang, Guoxiu; He, Tingting; Wei, Yiying

    2016-01-01

    Highlights: • Study on temperature, current, aging dependencies of maximum available energy. • Study on the various factors dependencies of relationships between SOE and SOC. • A quantitative relationship between SOE and SOC is proposed for SOE estimation. • Estimate maximum available energy by means of moving-window energy-integral. • The robustness and feasibility of the proposed approaches are systematic evaluated. - Abstract: The battery state of energy (SOE) allows a direct determination of the ratio between the remaining and maximum available energy of a battery, which is critical for energy optimization and management in energy storage systems. In this paper, the ambient temperature, battery discharge/charge current rate and cell aging level dependencies of battery maximum available energy and SOE are comprehensively analyzed. An explicit quantitative relationship between SOE and state of charge (SOC) for LiMn_2O_4 battery cells is proposed for SOE estimation, and a moving-window energy-integral technique is incorporated to estimate battery maximum available energy. Experimental results show that the proposed approaches can estimate battery maximum available energy and SOE with high precision. The robustness of the proposed approaches against various operation conditions and cell aging levels is systematically evaluated.

  13. Online Kinematic and Dynamic-State Estimation for Constrained Multibody Systems Based on IMUs

    Directory of Open Access Journals (Sweden)

    José Luis Torres-Moreno

    2016-03-01

    Full Text Available This article addresses the problems of online estimations of kinematic and dynamic states of a mechanism from a sequence of noisy measurements. In particular, we focus on a planar four-bar linkage equipped with inertial measurement units (IMUs. Firstly, we describe how the position, velocity, and acceleration of all parts of the mechanism can be derived from IMU signals by means of multibody kinematics. Next, we propose the novel idea of integrating the generic multibody dynamic equations into two variants of Kalman filtering, i.e., the extended Kalman filter (EKF and the unscented Kalman filter (UKF, in a way that enables us to handle closed-loop, constrained mechanisms, whose state space variables are not independent and would normally prevent the direct use of such estimators. The proposal in this work is to apply those estimators over the manifolds of allowed positions and velocities, by means of estimating a subset of independent coordinates only. The proposed techniques are experimentally validated on a testbed equipped with encoders as a means of establishing the ground-truth. Estimators are run online in real-time, a feature not matched by any previous procedure of those reported in the literature on multibody dynamics.

  14. Online Kinematic and Dynamic-State Estimation for Constrained Multibody Systems Based on IMUs

    Science.gov (United States)

    Torres-Moreno, José Luis; Blanco-Claraco, José Luis; Giménez-Fernández, Antonio; Sanjurjo, Emilio; Naya, Miguel Ángel

    2016-01-01

    This article addresses the problems of online estimations of kinematic and dynamic states of a mechanism from a sequence of noisy measurements. In particular, we focus on a planar four-bar linkage equipped with inertial measurement units (IMUs). Firstly, we describe how the position, velocity, and acceleration of all parts of the mechanism can be derived from IMU signals by means of multibody kinematics. Next, we propose the novel idea of integrating the generic multibody dynamic equations into two variants of Kalman filtering, i.e., the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), in a way that enables us to handle closed-loop, constrained mechanisms, whose state space variables are not independent and would normally prevent the direct use of such estimators. The proposal in this work is to apply those estimators over the manifolds of allowed positions and velocities, by means of estimating a subset of independent coordinates only. The proposed techniques are experimentally validated on a testbed equipped with encoders as a means of establishing the ground-truth. Estimators are run online in real-time, a feature not matched by any previous procedure of those reported in the literature on multibody dynamics. PMID:26959027

  15. State, Parameter, and Unknown Input Estimation Problems in Active Automotive Safety Applications

    Science.gov (United States)

    Phanomchoeng, Gridsada

    A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is

  16. 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.

  17. The modular modality frame model: continuous body state estimation and plausibility-weighted information fusion.

    Science.gov (United States)

    Ehrenfeld, Stephan; Butz, Martin V

    2013-02-01

    Humans show admirable capabilities in movement planning and execution. They can perform complex tasks in various contexts, using the available sensory information very effectively. Body models and continuous body state estimations appear necessary to realize such capabilities. We introduce the Modular Modality Frame (MMF) model, which maintains a highly distributed, modularized body model continuously updating, modularized probabilistic body state estimations over time. Modularization is realized with respect to modality frames, that is, sensory modalities in particular frames of reference and with respect to particular body parts. We evaluate MMF performance on a simulated, nine degree of freedom arm in 3D space. The results show that MMF is able to maintain accurate body state estimations despite high sensor and motor noise. Moreover, by comparing the sensory information available in different modality frames, MMF can identify faulty sensory measurements on the fly. In the near future, applications to lightweight robot control should be pursued. Moreover, MMF may be enhanced with neural encodings by introducing neural population codes and learning techniques. Finally, more dexterous goal-directed behavior should be realized by exploiting the available redundant state representations.

  18. A Review of Sea State Estimation Procedures Based on Measured Vessel Responses

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2016-01-01

    for shipboard SSE using measured vessel responses, resembling the concept of traditional wave rider buoys. Moreover, newly developed ideas for shipboard sea state estimation are introduced. The presented material is all based on the author’s personal experience, developed within extensive work on the subject......The operation of ships requires careful monitoring of therelated costs while, at the same time, ensuring a high level of safety. A ship’s performance with respect to safety and fuel efficiency may be compromised by the encountered waves. Consequently, it is important to estimate the surrounding...

  19. STATE ESTIMATION IN ALCOHOLIC CONTINUOUS FERMENTATION OF ZYMOMONAS MOBILIS USING RECURSIVE BAYESIAN FILTERING: A SIMULATION APPROACH

    Directory of Open Access Journals (Sweden)

    Olga Lucia Quintero

    2008-05-01

    Full Text Available This work presents a state estimator for a continuous bioprocess. To this aim, the Non Linear Filtering theory based on the recursive application of Bayes rule and Monte Carlo techniques is used. Recursive Bayesian Filters Sampling Importance Resampling (SIR is employed, including different kinds of resampling. Generally, bio-processes have strong non-linear and non-Gaussian characteristics, and this tool becomes attractive. The estimator behavior and performance are illustrated with the continuous process of alcoholic fermentation of Zymomonas mobilis. Not too many applications with this tool have been reported in the biotechnological area.

  20. Event-triggered sensor data transmission policy for receding horizon recursive state estimation

    Directory of Open Access Journals (Sweden)

    Yunji Li

    2017-06-01

    Full Text Available We consider a sensor data transmission policy for receding horizon recursive state estimation in a networked linear system. A good tradeoff between estimation error and communication rate could be achieved according to a transmission strategy, which decides the transfer time of the data packet. Here we give this transmission policy through proving the upper bound of system performance. Moreover, the lower bound of system performance is further analyzed in detail. A numerical example is given to verify the potential and effectiveness of the theoretical results.