Device-independent entanglement certification of all entangled states

OpenAIRE

Bowles, Joseph; Šupić, Ivan; Cavalcanti, Daniel; Acín, Antonio

2018-01-01

We present a method to certify the entanglement of all bipartite entangled quantum states in a device-independent way. This is achieved by placing the state in a quantum network and constructing a correlation inequality based on an entanglement witness for the state. Our method is device-independent, in the sense that entanglement can be certified from the observed statistics alone, under minimal assumptions on the underlying physics. Conceptually, our results borrow ideas from the field of s...

SOLID-STATE STORAGE DEVICE WITH PROGRAMMABLE PHYSICAL STORAGE ACCESS

DEFF Research Database (Denmark)

2017-01-01

a storage device action request, and the storage device evaluating a first rule of the one or more rules by determining if the received request fulfills request conditions comprised in the first rule, and in the affirmative the storage device performing request actions comprised in the first rule......Embodiments of the present invention includes a method of operating a solid-state storage device, comprising a storage device controller in the storage device receiving a set of one or more rules, each rule comprising (i) one or more request conditions to be evaluated for a storage device action...... request received from a host computer, and (ii) one or more request actions to be performed on a physical address space of a non-volatile storage unit in the solid-state storage device in case the one or more request conditions are fulfilled; the method further comprises: the storage device receiving...

Radiation sensitive solid state devices

International Nuclear Information System (INIS)

Shannon, J.M.; Ralph, J.E.

1975-01-01

A solid state radiation sensitive device is described employing JFETs as the sensitive elements. Two terminal construction is achieved by using a common conductor to capacitively couple to the JFET gate and to one of the source and drain connections. (auth)

Device-independent randomness generation from several Bell estimators

Science.gov (United States)

Nieto-Silleras, Olmo; Bamps, Cédric; Silman, Jonathan; Pironio, Stefano

2018-02-01

Device-independent randomness generation and quantum key distribution protocols rely on a fundamental relation between the non-locality of quantum theory and its random character. This relation is usually expressed in terms of a trade-off between the probability of guessing correctly the outcomes of measurements performed on quantum systems and the amount of violation of a given Bell inequality. However, a more accurate assessment of the randomness produced in Bell experiments can be obtained if the value of several Bell expressions is simultaneously taken into account, or if the full set of probabilities characterizing the behavior of the device is considered. We introduce protocols for device-independent randomness generation secure against classical side information, that rely on the estimation of an arbitrary number of Bell expressions or even directly on the experimental frequencies of measurement outcomes. Asymptotically, this results in an optimal generation of randomness from experimental data (as measured by the min-entropy), without having to assume beforehand that the devices violate a specific Bell inequality.

Reexamination of optimal quantum state estimation of pure states

International Nuclear Information System (INIS)

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

2005-01-01

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

Introduction to quantum-state estimation

CERN Document Server

Teo, Yong Siah

2016-01-01

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

State Estimation for Tensegrity Robots

Science.gov (United States)

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

2016-01-01

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

Head mounted device for point-of-gaze estimation in three dimensions

DEFF Research Database (Denmark)

Hansen, Dan Witzner; Lidegaard, Morten; Krüger, Norbert

2014-01-01

This paper presents a fully calibrated extended geometric approach for gaze estimation in three dimensions (3D). The methodology is based on a geometric approach utilising a fully calibrated binocular setup constructed as a head-mounted system. The approach is based on utilisation of two ordinary...... in the horizontal and vertical dimensions regarding fixations. However, even though the workspace is limited, the fact that the system is designed as a head-mounted device, the workspace volume is relatively positioned to the pose of the device. Hence gaze can be estimated in 3D with relatively free head...

Mobile device use while driving--United States and seven European countries, 2011.

Science.gov (United States)

2013-03-15

Road traffic crashes are a global public health problem, contributing to an estimated 1.3 million deaths annually. Known risk factors for road traffic crashes and related injuries and deaths include speed, alcohol, nonuse of restraints, and nonuse of helmets. More recently, driver distraction has become an emerging concern. To assess the prevalence of mobile device use while driving in Belgium, France, Germany, the Netherlands, Portugal, Spain, the United Kingdom (UK), and the United States, CDC analyzed data from the 2011 EuroPNStyles and HealthStyles surveys. Prevalence estimates for self-reported talking on a cell phone while driving and reading or sending text or e-mail messages while driving were calculated. This report describes the results of that analysis, which indicated that, among drivers ages 18-64 years, the prevalence of talking on a cell phone while driving at least once in the past 30 days ranged from 21% in the UK to 69% in the United States, and the prevalence of drivers who had read or sent text or e-mail messages while driving at least once in the past 30 days ranged from 15% in Spain to 31% in Portugal and the United States. Lessons learned from successful road safety efforts aimed at reducing other risky driving behaviors, such as seat belt nonuse and alcohol-impaired driving, could be helpful to the United States and other countries in addressing this issue. Strategies such as legislation combined with high-visibility enforcement and public education campaigns deserve further research to determine their effectiveness in reducing mobile device use while driving. Additionally, the role of emerging vehicle and mobile communication technologies in reducing distracted driving-related crashes should be explored.

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...

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.

State Alcohol-Impaired-Driving Estimates

Science.gov (United States)

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

Bad Data Detection and Identification for State Estimation

DEFF Research Database (Denmark)

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

2017-01-01

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

State estimation for a hexapod robot

CSIR Research Space (South Africa)

Lubbe, Estelle

2015-09-01

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

State energy data report 1994: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-10-01

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

State energy data report 1994: Consumption estimates

International Nuclear Information System (INIS)

1996-10-01

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

State energy data report 1995 - consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-01

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

Development of realtime cognitive state estimator

International Nuclear Information System (INIS)

Takahashi, Makoto; Kitamura, Masashi; Yoshikaea, Hidekazu

2004-01-01

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

UAV State Estimation Modeling Techniques in AHRS

Science.gov (United States)

Razali, Shikin; Zhahir, Amzari

2017-11-01

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

Study on scalable Coulombic degradation for estimating the lifetime of organic light-emitting devices

International Nuclear Information System (INIS)

Zhang Wenwen; Hou Xun; Wu Zhaoxin; Liang Shixiong; Jiao Bo; Zhang Xinwen; Wang Dawei; Chen Zhijian; Gong Qihuang

2011-01-01

The luminance decays of organic light-emitting diodes (OLEDs) are investigated with initial luminance of 1000 to 20 000 cd m -2 through a scalable Coulombic degradation and a stretched exponential decay. We found that the estimated lifetime by scalable Coulombic degradation deviates from the experimental results when the OLEDs work with high initial luminance. By measuring the temperature of the device during degradation, we found that the higher device temperatures will lead to instabilities of organic materials in devices, which is expected to result in the difference between the experimental results and estimation using the scalable Coulombic degradation.

The Total Deviation Index estimated by Tolerance Intervals to evaluate the concordance of measurement devices

Directory of Open Access Journals (Sweden)

Ascaso Carlos

2010-04-01

Full Text Available Abstract Background In an agreement assay, it is of interest to evaluate the degree of agreement between the different methods (devices, instruments or observers used to measure the same characteristic. We propose in this study a technical simplification for inference about the total deviation index (TDI estimate to assess agreement between two devices of normally-distributed measurements and describe its utility to evaluate inter- and intra-rater agreement if more than one reading per subject is available for each device. Methods We propose to estimate the TDI by constructing a probability interval of the difference in paired measurements between devices, and thereafter, we derive a tolerance interval (TI procedure as a natural way to make inferences about probability limit estimates. We also describe how the proposed method can be used to compute bounds of the coverage probability. Results The approach is illustrated in a real case example where the agreement between two instruments, a handle mercury sphygmomanometer device and an OMRON 711 automatic device, is assessed in a sample of 384 subjects where measures of systolic blood pressure were taken twice by each device. A simulation study procedure is implemented to evaluate and compare the accuracy of the approach to two already established methods, showing that the TI approximation produces accurate empirical confidence levels which are reasonably close to the nominal confidence level. Conclusions The method proposed is straightforward since the TDI estimate is derived directly from a probability interval of a normally-distributed variable in its original scale, without further transformations. Thereafter, a natural way of making inferences about this estimate is to derive the appropriate TI. Constructions of TI based on normal populations are implemented in most standard statistical packages, thus making it simpler for any practitioner to implement our proposal to assess agreement.

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.

Association of HeartMate II left ventricular assist device flow estimate with thermodilution cardiac output.

Science.gov (United States)

Hasin, Tal; Huebner, Marianne; Li, Zhuo; Brown, Daniel; Stulak, John M; Boilson, Barry A; Joyce, Lyle; Pereira, Naveen L; Kushwaha, Sudhir S; Park, Soon J

2014-01-01

Cardiac output (CO) assessment is important in treating patients with heart failure. Durable left ventricular assist devices (LVADs) provide essentially all CO. In currently used LVADs, estimated device flow is generated by a computerized algorithm. However, LVAD flow estimate may be inaccurate in tracking true CO. We correlated LVAD (HeartMate II) flow with thermodilution CO during postoperative care (day 2-10 after implant) in 81 patients (5,616 paired measurements). Left ventricular assist device flow and CO correlated with a low correlation coefficient (r = 0.42). Left ventricular assist device readings were lower than CO measurements by approximately 0.36 L/min, trending for larger difference with higher values. Left ventricular assist device flow measurements showed less temporal variability compared with CO. Grouping for simultaneous measured blood pressure (BP device flow generally trends with measured CO, but large variability exists, hence flow measures should not be assumed to equal with CO. Clinicians should take into account variables such as high CO, BP, and opening of the aortic valve when interpreting LVAD flow readout. Direct flow sensors incorporated in the LVAD system may allow for better estimation.

Self-learning estimation of quantum states

International Nuclear Information System (INIS)

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

2002-01-01

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

State Energy Data Report, 1991: Consumption estimates

International Nuclear Information System (INIS)

1993-05-01

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

A DNA-based nanomechanical device with three robust states

OpenAIRE

Chakraborty, Banani; Sha, Ruojie; Seeman, Nadrian C.

2008-01-01

DNA has been used to build a variety of devices, ranging from those that are controlled by DNA structural transitions to those that are controlled by the addition of specific DNA strands. These sequence-dependent devices fulfill the promise of DNA in nanotechnology because a variety of devices in the same physical environment can be controlled individually. Many such devices have been reported, but most of them contain one or two structurally robust end states, in addition to a floppy interme...

Simulation of devices mobility to estimate wireless channel quality metrics in 5G networks

Science.gov (United States)

Orlov, Yu.; Fedorov, S.; Samuylov, A.; Gaidamaka, Yu.; Molchanov, D.

2017-07-01

The problem of channel quality estimation for devices in a wireless 5G network is formulated. As a performance metrics of interest we choose the signal-to-interference-plus-noise ratio, which depends essentially on the distance between the communicating devices. A model with a plurality of moving devices in a bounded three-dimensional space and a simulation algorithm to determine the distances between the devices for a given motion model are devised.

Molecular electronics with single molecules in solid-state devices

DEFF Research Database (Denmark)

Moth-Poulsen, Kasper; Bjørnholm, Thomas

2009-01-01

The ultimate aim of molecular electronics is to understand and master single-molecule devices. Based on the latest results on electron transport in single molecules in solid-state devices, we focus here on new insights into the influence of metal electrodes on the energy spectrum of the molecule...

An Empirical State Error Covariance Matrix for Batch State Estimation

Science.gov (United States)

Frisbee, Joseph H., Jr.

2011-01-01

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

A new device to noninvasively estimate the intraocular pressure produced during ocular compression

Directory of Open Access Journals (Sweden)

Korenfeld MS

2016-01-01

Full Text Available Michael S Korenfeld,1,2 David K Dueker3 1Comprehensive Eye Care, Ltd., 2Department of Ophthalmology and Visual Sciences, Washington University, Washington, MO, USA; 3Hamad Medical Corporation, Doha, Qatar Purpose: To describe a noninvasive instrument that estimates intraocular pressure during episodes of external globe compression and to demonstrate the accuracy and reliability of this device by comparing it to the intraocular pressures simultaneously and manometrically measured in cannulated eyes. Methods: A thin fluid-filled bladder was constructed from flexible and inelastic plastic sheeting and was connected to a pressure transducer with high pressure tubing. The output of the pressure transducer was sent to an amplifier and recorded. This device was validated by measuring induced pressure in the fluid-filled bladder while digital pressure was applied to one surface, and the other surface was placed directly against a human cadaver eye or in vivo pig eye. The human cadaver and in vivo pig eyes were each cannulated to provide a manometric intraocular pressure control. Results: The measurements obtained with the newly described device were within ~5% of simultaneously measured manometric intraocular pressures in both a human cadaver and in vivo pig eye model for a pressure range of ~15–100 mmHg. Conclusion: This novel noninvasive device is useful for estimating the intraocular pressure transients induced during any form of external globe compression; this is a clinical setting where no other devices can be used to estimate intraocular pressure. Keywords: glaucoma, intraocular pressure, tonometer, ocular compression

The investigation and implementation of real-time face pose and direction estimation on mobile computing devices

Science.gov (United States)

Fu, Deqian; Gao, Lisheng; Jhang, Seong Tae

2012-04-01

The mobile computing device has many limitations, such as relative small user interface and slow computing speed. Usually, augmented reality requires face pose estimation can be used as a HCI and entertainment tool. As far as the realtime implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to face different constraints while leaving enough face pose estimation accuracy. The proposed face pose estimation method met this objective. Experimental results running on a testing Android mobile device delivered satisfactory performing results in the real-time and accurately.

State estimation for large-scale wastewater treatment plants.

Science.gov (United States)

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

2013-09-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2000-06-01

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

Estimation of Body Composition Depends on Applied Device in Patients Undergoing Major Abdominal Surgery

NARCIS (Netherlands)

Haverkort, E.B.; Binnekade, J.M.; van Bokhorst-de van der Schueren, M.A.E.; Gouma, D.J.; de Haan, R.J.

2015-01-01

Background: Bioelectrical impedance analysis (BIA) is a method used to estimate body compartments such as fat-free mass (FFM) and fat mass (FM). Two BIA devices, a single-frequency BIA (SF-BIA) device and a bioimpedance spectroscopy (BIS) approach, were compared to evaluate their reliability and to

Estimation of body composition depends on applied device in patients undergoing major abdominal surgery

NARCIS (Netherlands)

Haverkort, Elizabeth B.; Binnekade, Jan M.; de van der Schueren, Marian A. E.; Gouma, Dirk J.; de Haan, Rob J.

2015-01-01

Bioelectrical impedance analysis (BIA) is a method used to estimate body compartments such as fat-free mass (FFM) and fat mass (FM). Two BIA devices, a single-frequency BIA (SF-BIA) device and a bioimpedance spectroscopy (BIS) approach, were compared to evaluate their reliability and to study

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.

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.

Linear Covariance Analysis and Epoch State Estimators

Science.gov (United States)

Markley, F. Landis; Carpenter, J. Russell

2014-01-01

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

State energy data report 1996: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-02-01

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

State energy data report 1996: Consumption estimates

International Nuclear Information System (INIS)

1999-02-01

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

New developments in state estimation for Nonlinear Systems

DEFF Research Database (Denmark)

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

2000-01-01

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

On state estimation in electric drives

International Nuclear Information System (INIS)

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

2010-01-01

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

State-Level Estimates of Cancer-Related Absenteeism Costs

Science.gov (United States)

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

2016-01-01

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

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.

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

Medical Device Regulation: A Comparison of the United States and the European Union.

Science.gov (United States)

Maak, Travis G; Wylie, James D

2016-08-01

Medical device regulation is a controversial topic in both the United States and the European Union. Many physicians and innovators in the United States cite a restrictive US FDA regulatory process as the reason for earlier and more rapid clinical advances in Europe. The FDA approval process mandates that a device be proved efficacious compared with a control or be substantially equivalent to a predicate device, whereas the European Union approval process mandates that the device perform its intended function. Stringent, peer-reviewed safety data have not been reported. However, after recent high-profile device failures, political pressure in both the United States and the European Union has favored more restrictive approval processes. Substantial reforms of the European Union process within the next 5 to 10 years will result in a more stringent approach to device regulation, similar to that of the FDA. Changes in the FDA regulatory process have been suggested but are not imminent.

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.

Estimation of the energy efficiency of cryogenic filled tank use in different systems and devices

International Nuclear Information System (INIS)

Blagin, E.V.; Dovgyallo, A.I.; Nekrasova, S.O.; Sarmin, D.V.; Uglanov, D.A.

2016-01-01

Highlights: • The cryogenic fueling tank is a device for storage and gasification of working fluid. • Potential energy of pressure can be converted to electricity by circuit of turbines. • It is possible to compensate up to 8% of energy consumed for liquefaction. - Abstract: This article presents a device for storage and gasification of cryogenic working fluid. This device is called cryogenic fueling tank. Working fluid pressure increases during the gasification and potential energy of this pressure can be used in different ways. The ways of integrating the cryogenic fueling tank into existing energy plants are described in this article. The estimation of the cryogenic fueling tank application in the gasification facility as well as in the onboard power system was carried out. This estimation shows that application of such tank as well as a circuit of turbines allows generating up to near 8% of energy which was consumed during gas liquefaction. The estimation of the additionally generated electric energy value was also carried out for each of the cases.

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.

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%.

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....

State-of-the-art technologies of gallium oxide power devices

Science.gov (United States)

Higashiwaki, Masataka; Kuramata, Akito; Murakami, Hisashi; Kumagai, Yoshinao

2017-08-01

Gallium oxide (Ga2 O3 ) has gained increased attention for power devices due to its superior material properties and the availability of economical device-quality native substrates. This review illustrates recent advances in Ga2 O3 device technologies, beginning with an overview of the social circumstances that motivate the development of new-generation switching devices. Following an introduction to the material properties of Ga2 O3 from the viewpoint of power electronics, growth technologies of Ga2 O3 bulk single crystals and epitaxial thin films are discussed. The fabrication and performance of state-of-the-art Ga2 O3 transistors and diodes are then described. We conclude by identifying the directions and challenges of Ga2 O3 power device development in the near future.

Weighty data: importance information influences estimated weight of digital information storage devices.

Directory of Open Access Journals (Sweden)

Iris eSchneider

2015-01-01

Full Text Available Previous work has suggested that perceived importance of an object influences estimates of its weight. Specifically, important books were estimated to be heavier than non-important books. However, the experimental set-up of these studies may have suffered from a potential confound and findings may be confined to books only. Addressing this, we investigate the effect of importance on weight estimates by examining whether the importance of information stored on a data storage device (USB-stick or portable hard drive can alter weight estimates. Results show that people thinking a USB-stick holds important tax information (vs. expired vs. no information estimate it to be heavier (Experiment 1 compared to people who do not. Similarly, people who are told a portable hard-drive holds personally relevant information (vs. irrelevant, also estimate the drive to be heavier (Experiment 2a and 2b. The current work shows that importance influences weight perceptions beyond specific objects.

Effect of Smart Meter Measurements Data On Distribution State Estimation

DEFF Research Database (Denmark)

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

2018-01-01

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

Optimal state estimation theory applied to safeguards accounting

International Nuclear Information System (INIS)

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

1977-01-01

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

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.

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

Preliminary Load Estimations for DEXA Wave Energy Device - Hanstholm, Denmark

DEFF Research Database (Denmark)

Kofoed, Jens Peter

by DEXA Wave Energy ApS, in regular and irregular wave states, as described in Assessment of Wave Energy Devices. Best Practice as used in Denmark (Frigaard et al., 2008). The length scale of the model was 1:20 compared to a full scale device suitable fro the Danish part of the North Sea, according...... to DEXA Wave Energy ApS. The tests were carried out at Dept. of Civil Engineering, Aalborg University (AAU) in the 3D deep water wave tank. The displacement and force applied to a power take off system, provided by DEXA Wave Energy ApS, were measured and used for calculation of power available...... to the power take-off....

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.

Molecular electronics with single molecules in solid-state devices.

Science.gov (United States)

Moth-Poulsen, Kasper; Bjørnholm, Thomas

2009-09-01

The ultimate aim of molecular electronics is to understand and master single-molecule devices. Based on the latest results on electron transport in single molecules in solid-state devices, we focus here on new insights into the influence of metal electrodes on the energy spectrum of the molecule, and on how the electron transport properties of the molecule depend on the strength of the electronic coupling between it and the electrodes. A variety of phenomena are observed depending on whether this coupling is weak, intermediate or strong.

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,.

Topological interface states and effects for next generation of innovative devices

International Nuclear Information System (INIS)

Kantser, Valeriu; Carlig, Sergiu

2013-01-01

Topological insulators (TI) have opened a gateway to search new quantum electronic phase of the condensed matter as well as to pave new platform of modern technology. This stems mainly on their unique surface states that are protected by time-reversal symmetry, show the Dirac cones connecting the inverted conduction and valence bands and exhibit unique spin-momentum locking property. Increasing the surface state contribution in proportion to the bulk of material is critical to investigate the surface states and for future innovative device applications. The way to achieve this is to configure topological insulators into nanostructures, which at the same time in combination with others materials significantly enlarge the variety of new states and phenomena. This article reviews the recent progress made in topological insulator nano heterostructures electronic states investigation. The state of art of different new scenario of engineering topologically interface states in the TI heterostructures are revealed, in particular by using polarization fields and antiferromagnetic ordering. Some of new proposals for innovative electronic devices are discussed. (authors)

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.

Current state of low energy EB devices and its application technology

International Nuclear Information System (INIS)

Kinoshita, Shinobu

2000-01-01

This paper introduced the current state of low energy type EB (electron beam) devices with an acceleration voltage of 300 kV or below and specific application examples. As for EB devices, it introduced the ultra-compact new EB device (microbeam LV), experimental devices, and the pilot/production devices which have been recently developed by the manufacturer to which the author belongs. As the applications of low energy EB devices, it specifically introduced curing, graft polymerization, crosslinking, and sterilization/disinfection with soft electrons: (1) examples of EB curing; antistatic agents in antibacterial/antifungal property imparting processing, hard coat, printing and topcoat, high gloss/pattern transfer processing, and metal vapor deposition film, (2) example of graft polymerization; barrier imparting films, and (3) examples of crosslinking; shrinking films/tubes and foamed sheets. (A.O.)

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...

Final report of the NRC-Agreement State Working Group to evaluate control and accountability of licensed devices

International Nuclear Information System (INIS)

1996-10-01

US NRC staff acknowledged that licensees were having problems maintaining control over and accountability for devices containing radioactive material. In June 1995, NRC approved the staff's suggestion to form a joint NRC-Agreement State Working Group to evaluate the problem and propose solutions. The staff indicated that the Working Group was necessary to address the concerns from a national perspective, allow for a broad level of Agreement State input, and to reflect their experience. Agreement State participation in the process was essential since some Agreement States have implemented effective programs for oversight of device users. This report includes the 5 recommendations proposed by the Working Group to increase regulatory oversight, increase control and accountability of devices, ensure proper disposal, and ensure disposal of orphaned devices. Specifically, the Working Group recommends that: (1) NRC and Agreement States increase regulatory oversight for users of certain devices; (2) NRC and Agreement State impose penalties on persons losing devices; (3) NRC and Agreement States ensure proper disposal of orphaned devices; (4) NRC encourage States to implement similar oversight programs for users of Naturally-Occurring or Accelerator- Produced Material; and (5) NRC encourage non-licensed stakeholders to take appropriate actions, such as instituting programs for material identification

Final report of the NRC-Agreement State Working Group to evaluate control and accountability of licensed devices

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-10-01

US NRC staff acknowledged that licensees were having problems maintaining control over and accountability for devices containing radioactive material. In June 1995, NRC approved the staff`s suggestion to form a joint NRC-Agreement State Working Group to evaluate the problem and propose solutions. The staff indicated that the Working Group was necessary to address the concerns from a national perspective, allow for a broad level of Agreement State input, and to reflect their experience. Agreement State participation in the process was essential since some Agreement States have implemented effective programs for oversight of device users. This report includes the 5 recommendations proposed by the Working Group to increase regulatory oversight, increase control and accountability of devices, ensure proper disposal, and ensure disposal of orphaned devices. Specifically, the Working Group recommends that: (1) NRC and Agreement States increase regulatory oversight for users of certain devices; (2) NRC and Agreement State impose penalties on persons losing devices; (3) NRC and Agreement States ensure proper disposal of orphaned devices; (4) NRC encourage States to implement similar oversight programs for users of Naturally-Occurring or Accelerator- Produced Material; and (5) NRC encourage non-licensed stakeholders to take appropriate actions, such as instituting programs for material identification.

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.

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.

Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

Science.gov (United States)

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

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)

Lessons learned: from dye-sensitized solar cells to all-solid-state hybrid devices.

Science.gov (United States)

Docampo, Pablo; Guldin, Stefan; Leijtens, Tomas; Noel, Nakita K; Steiner, Ullrich; Snaith, Henry J

2014-06-25

The field of solution-processed photovoltaic cells is currently in its second spring. The dye-sensitized solar cell is a widely studied and longstanding candidate for future energy generation. Recently, inorganic absorber-based devices have reached new record efficiencies, with the benefits of all-solid-state devices. In this rapidly changing environment, this review sheds light on recent developments in all-solid-state solar cells in terms of electrode architecture, alternative sensitizers, and hole-transporting materials. These concepts are of general applicability to many next-generation device platforms. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles

Directory of Open Access Journals (Sweden)

Hong Zhang

2015-12-01

Full Text Available Estimating the residual capacity or state-of-charge (SoC of commercial batteries on-line without destroying them or interrupting the power supply, is quite a challenging task for electric vehicle (EV designers. Many Coulomb counting-based methods have been used to calculate the remaining capacity in EV batteries or other portable devices. The main disadvantages of these methods are the cumulative error and the time-varying Coulombic efficiency, which are greatly influenced by the operating state (SoC, temperature and current. To deal with this problem, we propose a lossy counting-based Coulomb counting method for estimating the available capacity or SoC. The initial capacity of the tested battery is obtained from the open circuit voltage (OCV. The charging/discharging efficiencies, used for compensating the Coulombic losses, are calculated by the lossy counting-based method. The measurement drift, resulting from the current sensor, is amended with the distorted Coulombic efficiency matrix. Simulations and experimental results show that the proposed method is both effective and convenient.

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.

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.

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...

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

Applied solid state science advances in materials and device research

CERN Document Server

Wolfe, Raymond

2013-01-01

Applied Solid State Science: Advances in Materials and Device Research, Volume 4 covers articles on single crystal compound semiconductors and complex polycrystalline materials. The book discusses narrow gap semiconductors and solid state batteries. The text then describes the advantages of hot-pressed microcrystalline compacts of oxygen-octahedra ferroelectrics over single crystal materials, as well as heterostructure junction lasers. Solid state physicists, materials scientists, electrical engineers, and graduate students studying the subjects being discussed will find the book invaluable.

Applied solid state science advances in materials and device research

CERN Document Server

Wolfe, Raymond

2013-01-01

Applied Solid State Science: Advances in Materials and Device Research, Volume 1 presents articles about junction electroluminescence; metal-insulator-semiconductor (MIS) physics; ion implantation in semiconductors; and electron transport through insulating thin films. The book describes the basic physics of carrier injection; energy transfer and recombination mechanisms; state of the art efficiencies; and future prospects for light emitting diodes. The text then discusses solid state spectroscopy, which is the pair spectra observed in gallium phosphide photoluminescence. The extensive studies

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.

Thermal Loading and Lifetime Estimation for Power Device Considering Mission Profiles in Wind Power Converter

DEFF Research Database (Denmark)

Ma, Ke; Liserre, Marco; Blaabjerg, Frede

2015-01-01

for the reliability improvement and also for cost reduction of wind power technology. Unfortunately, the existing lifetime estimation methods for the power electronic converter are not yet suitable in the wind power application, because the comprehensive mission profiles are not well specified and included......As a key component in the wind turbine system, the power electronic converter and its power semiconductors suffer from complicated power loadings related to environment, and are proven to have high failure rates. Therefore, correct lifetime estimation of wind power converter is crucial...... devices, more detailed information of the lifetime-related performance in wind power converter can be obtained. Some experimental results are also included to validate the thermal behavior of power device under different mission profiles....

A novel electro-thermal model for wide bandgap semiconductor based devices

DEFF Research Database (Denmark)

Sintamarean, Nicolae Christian; Blaabjerg, Frede; Wang, Huai

2013-01-01

This paper propose a novel Electro-Thermal Model for the new generation of power electronics WBG-devices (by considering the SiC MOSFET-CMF20120D from CREE), which is able to estimate the device junction and case temperature. The Device-Model estimates the voltage drop and the switching energies...... by considering the device current, the off-state blocking voltage and junction temperature variation. Moreover, the proposed Thermal-Model is able to consider the thermal coupling within the MOSFET and its freewheeling diode, integrated into the same package, and the influence of the ambient temperature...... variation. The importance of temperature loop feedback in the estimation accuracy of device junction and case temperature is studied. Furthermore, the Safe Operating Area (SOA) of the SiC MOSFET is determined for 2L-VSI applications which are using sinusoidal PWM. Thus, by considering the heatsink thermal...

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.

Gain dynamics of quantum dot devices for dual-state operation

Energy Technology Data Exchange (ETDEWEB)

Kaptan, Y., E-mail: yuecel.kaptan@physik.tu-berlin.de; Herzog, B.; Kolarczik, M.; Owschimikow, N.; Woggon, U. [Institut für Optik und Atomare Physik, Technische Universität Berlin, Berlin (Germany); Schmeckebier, H.; Arsenijević, D.; Bimberg, D. [Institut für Festkörperphysik, Technische Universität Berlin, Berlin (Germany); Mikhelashvili, V.; Eisenstein, G. [Technion Institute of Technology, Faculty of Electrical Engineering, Haifa (Israel)

2014-06-30

Ground state gain dynamics of In(Ga)As-quantum dot excited state lasers are investigated via single-color ultrafast pump-probe spectroscopy below and above lasing threshold. Two-color pump-probe experiments are used to localize lasing and non-lasing quantum dots within the inhomogeneously broadened ground state. Single-color results yield similar gain recovery rates of the ground state for lasing and non-lasing quantum dots decreasing from 6 ps to 2 ps with increasing injection current. We find that ground state gain dynamics are influenced solely by the injection current and unaffected by laser operation of the excited state. This independence is promising for dual-state operation schemes in quantum dot based optoelectronic devices.

Study on the photoresponse of amorphous In-Ga-Zn-O and zinc oxynitride semiconductor devices by the extraction of sub-gap-state distribution and device simulation.

Science.gov (United States)

Jang, Jun Tae; Park, Jozeph; Ahn, Byung Du; Kim, Dong Myong; Choi, Sung-Jin; Kim, Hyun-Suk; Kim, Dae Hwan

2015-07-22

Persistent photoconduction (PPC) is a phenomenon that limits the application of oxide semiconductor thin-film transistors (TFTs) in optical sensor-embedded displays. In the present work, a study on zinc oxynitride (ZnON) semiconductor TFTs based on the combination of experimental results and device simulation is presented. Devices incorporating ZnON semiconductors exhibit negligible PPC effects compared with amorphous In-Ga-Zn-O (a-IGZO) TFTs, and the difference between the two types of materials are examined by monochromatic photonic C-V spectroscopy (MPCVS). The latter method allows the estimation of the density of subgap states in the semiconductor, which may account for the different behavior of ZnON and IGZO materials with respect to illumination and the associated PPC. In the case of a-IGZO TFTs, the oxygen flow rate during the sputter deposition of a-IGZO is found to influence the amount of PPC. Small oxygen flow rates result in pronounced PPC, and large densities of valence band tail (VBT) states are observed in the corresponding devices. This implies a dependence of PPC on the amount of oxygen vacancies (VO). On the other hand, ZnON has a smaller bandgap than a-IGZO and contains a smaller density of VBT states over the entire range of its bandgap energy. Here, the concept of activation energy window (AEW) is introduced to explain the occurrence of PPC effects by photoinduced electron doping, which is likely to be associated with the formation of peroxides in the semiconductor. The analytical methodology presented in this report accounts well for the reduction of PPC in ZnON TFTs, and provides a quantitative tool for the systematic development of phototransistors for optical sensor-embedded interactive displays.

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.

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.

Computerized cost estimation spreadsheet and cost data base for fusion devices

International Nuclear Information System (INIS)

Hamilton, W.R.; Rothe, K.E.

1985-01-01

An automated approach to performing and cataloging cost estimates has been developed at the Fusion Engineering Design Center (FEDC), wherein the cost estimate record is stored in the LOTUS 1-2-3 spreadsheet on an IBM personal computer. The cost estimation spreadsheet is based on the cost coefficient/cost algorithm approach and incorporates a detailed generic code of cost accounts for both tokamak and tandem mirror devices. Component design parameters (weight, surface area, etc.) and cost factors are input, and direct and indirect costs are calculated. The cost data base file derived from actual cost experience within the fusion community and refined to be compatible with the spreadsheet costing approach is a catalog of cost coefficients, algorithms, and component costs arranged into data modules corresponding to specific components and/or subsystems. Each data module contains engineering, equipment, and installation labor cost data for different configurations and types of the specific component or subsystem. This paper describes the assumptions, definitions, methodology, and architecture incorporated in the development of the cost estimation spreadsheet and cost data base, along with the type of input required and the output format

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

Science.gov (United States)

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

2017-10-01

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

FACTS device control strategy using PMU

Directory of Open Access Journals (Sweden)

Mohd Tauseef Khan

2016-09-01

Full Text Available The laying and commissioning of new transmission line is very difficult due to socio-economic problems, like environmental clearances, right of way, etc. Therefore, there is an emphasis on better utilization of available transmission infrastructure. FACTS devices can provide reactive power compensation, transmission capability enhancement, and voltage and stability improvement. FACTS devices operate under the command of system operator who analyses its demand by the data acquired through traditional SCADA system, state estimation algorithms and PMUs. SCADA together with PMU give accurate information about the operational state of power system. This paper proposes a scheme to automate the FACTS devices in collaboration with PMUs in a more efficient way. Highly precised data from PMUs can be fed to intelligent controllers for effective analyzing and automating the FACTS device through control command. Thus, this combination can provide real time control of reactive power, together with enhancement of power handling capability and stability improvement.

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...

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.

Tritium contaminated surface monitoring with a solid - state device

International Nuclear Information System (INIS)

Culcer, Mihai; Iliescu, Mariana; Curuia, Marian; Enache, Adrian; Stefanescu, Ioan; Ducu, Catalin; Malinovschi, Viorel

2004-01-01

The low energy of betas makes tritium difficult to detect. However, there are several methods used in tritium detection, such as liquid scintillation and ionization chambers. Tritium on or near a surface can be also detected using proportional counters and, recently, solid state devices. The paper presents our results in the design and achievement of a surface tritium monitor using a PIN photodiode as a solid state charged particle detector to count betas emitted from the surface. That method allows continuous, real-time and non-destructively measuring of tritium. (authors)

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

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...

Geometry of perturbed Gaussian states and quantum estimation

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-09-05

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

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

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...

State and parameter estimation in biotechnical batch reactors

NARCIS (Netherlands)

Keesman, K.J.

2000-01-01

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

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

Science.gov (United States)

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

2017-05-01

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

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

Science.gov (United States)

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

2017-10-11

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

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.

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.

Device evaluation and coverage policy in workers' compensation: examples from Washington State.

Science.gov (United States)

Franklin, G M; Lifka, J; Milstein, J

1998-09-25

Workers' compensation health benefits are broader than general health benefits and include payment for medical and rehabilitation costs, associated indemnity (lost time) costs, and vocational rehabilitation (return-to-work) costs. In addition, cost liability is for the life of the claim (injury), rather than for each plan year. We examined device evaluation and coverage policy in workers' compensation over a 10-year period in Washington State. Most requests for device coverage in workers' compensation relate to the diagnosis, prognosis, or treatment of chronic musculoskeletal conditions. A number of specific problems have been recognized in making device coverage decisions within workers' compensation: (1) invasive devices with a high adverse event profile and history of poor outcomes could significantly increase both indemnity and medical costs; (2) many noninvasive devices, while having a low adverse event profile, have not proved effective for managing chronic musculoskeletal conditions relevant to injured workers; (3) some devices are marketed and billed as surrogate diagnostic tests for generally accepted, and more clearly proven, standard tests; (4) quality oversight of technology use among physicians may be inadequate; and (5) insurers' access to efficacy data adequate to make timely and appropriate coverage decisions in workers' compensation is often lacking. Emerging technology may substantially increase the costs of workers' compensation without significant evidence of health benefit for injured workers. To prevent ever-rising costs, we need to increase provider education and patient education and consent, involve the state medical society in coverage policy, and collect relevant outcomes data from healthcare providers.

Loose part monitoring device

International Nuclear Information System (INIS)

Nomura, Hiroshi.

1992-01-01

The device of the present invention estimates a place where loose parts occur and structural components as the loose parts in a fluid flow channel of a reactor device, to provide information thereof to a plant operator. That is, the device of the present invention comprises (1) a plurality of detectors disposed to each of equipments constituting fluid channels, (2) an abnormal sound sensing device for sensing signals from the detectors, (3) an estimation section for estimating the place where the loose parts occur and the structural components thereof based on the signals sensed by the abnormal sound sensing section, (4) a memory section for storing data of the plant structure necessary for the estimation, and (5) a display section for displaying the result of the estimation. In such a device, the position where the loose parts collide against the plant structural component and the energy thereof are estimated. The dropping path of the loose parts is estimated from the estimation position. Parts to be loose parts in the path are listed up. The parts on the list is selected based on the estimated energy thereby enabling to determine the loose parts. (I.S.)

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 ...

Devices used by automated milking systems are similarly accurate in estimating milk yield and in collecting a representative milk sample compared with devices used by farms with conventional milk recording

NARCIS (Netherlands)

Kamphuis, Claudia; Dela Rue, B.; Turner, S.A.; Petch, S.

2015-01-01

Information on accuracy of milk-sampling devices used on farms with automated milking systems (AMS) is essential for development of milk recording protocols. The hypotheses of this study were (1) devices used by AMS units are similarly accurate in estimating milk yield and in collecting

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.

Power system static state estimation using Kalman filter algorithm

Directory of Open Access Journals (Sweden)

Saikia Anupam

2016-01-01

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

State energy data report 1992: Consumption estimates

Energy Technology Data Exchange (ETDEWEB)

1994-05-01

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

National intelligence estimates and the Failed State Index.

Science.gov (United States)

Voracek, Martin

2013-10-01

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

On Estimating Marginal Tax Rates for U.S. States

OpenAIRE

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

2011-01-01

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

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.

Use of Mobile Devices: A Case Study with Children from Kuwait and the United States

Science.gov (United States)

Dashti, Fatimah A.; Yateem, Azizah K.

2018-01-01

This study explored children's usage and understandings about mobile devices. The study included 112 children aged 3-5 years, of whom 53 children lived in Kuwait and 59 children lived in the United States. The children were interviewed about their access to and usage of mobile devices, about how they learned to use mobile devices, and the actions…

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.

Estimating the state of large spatio-temporally chaotic systems

International Nuclear Information System (INIS)

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

2004-01-01

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

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

Science.gov (United States)

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

2016-03-01

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

Estimation of Human Workload from the Auditory Steady-State Response Recorded via a Wearable Electroencephalography System during Walking

Directory of Open Access Journals (Sweden)

Yusuke Yokota

2017-06-01

Full Text Available Workload in the human brain can be a useful marker of internal brain state. However, due to technical limitations, previous workload studies have been unable to record brain activity via conventional electroencephalography (EEG and magnetoencephalography (MEG devices in mobile participants. In this study, we used a wearable EEG system to estimate workload while participants walked in a naturalistic environment. Specifically, we used the auditory steady-state response (ASSR which is an oscillatory brain activity evoked by repetitive auditory stimuli, as an estimation index of workload. Participants performed three types of N-back tasks, which were expected to command different workloads, while walking at a constant speed. We used a binaural 500 Hz pure tone with amplitude modulation at 40 Hz to evoke the ASSR. We found that the phase-locking index (PLI of ASSR activity was significantly correlated with the degree of task difficulty, even for EEG data from few electrodes. Thus, ASSR appears to be an effective indicator of workload during walking in an ecologically valid environment.

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

Science.gov (United States)

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

2016-06-01

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

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

KAUST Repository

Ting, Chee-Ming

2017-12-06

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

Battery state-of-charge estimation using approximate least squares

Science.gov (United States)

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

2015-03-01

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

Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation

Directory of Open Access Journals (Sweden)

Xi Liu

2016-09-01

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

Estimation of current constriction losses via 3D tomography reconstructions in electrochemical devices: a case study of a solid oxide cell electrode/electrolyte interface

DEFF Research Database (Denmark)

Nielsen, Jimmi; Jørgensen, Peter Stanley

2017-01-01

In the present study, the methodology for accurate estimations of the current constriction resistance in solid state electrochemical devices via 3D tomography reconstructions is developed. The methodology is used to determine the current constriction resistances at the Ni:YSZ anode/YSZ electrolyte...... of the electrolyte thickness. The obtained results on current constriction resistances from numerical calculations on a 3D reconstruction of a Ni:YSZ anode/YSZ electrolyte assembly is compared with existing models with analytical expressions. The comparison shows, that the assumptions of existing models are by far...

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

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Ibrahim M. Safwat

2017-11-01

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

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

Science.gov (United States)

Lovelace, John K.

2009-01-01

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

Spin State Estimation of Tumbling Small Bodies

Science.gov (United States)

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

2016-06-01

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

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.

Multi-party Measurement-Device-Independent Quantum Key Distribution Based on Cluster States

Science.gov (United States)

Liu, Chuanqi; Zhu, Changhua; Ma, Shuquan; Pei, Changxing

2018-03-01

We propose a novel multi-party measurement-device-independent quantum key distribution (MDI-QKD) protocol based on cluster states. A four-photon analyzer which can distinguish all the 16 cluster states serves as the measurement device for four-party MDI-QKD. Any two out of four participants can build secure keys after the analyzers obtains successful outputs and the two participants perform post-processing. We derive a security analysis for the protocol, and analyze the key rates under different values of polarization misalignment. The results show that four-party MDI-QKD is feasible over 280 km in the optical fiber channel when the key rate is about 10- 6 with the polarization misalignment parameter 0.015. Moreover, our work takes an important step toward a quantum communication network.

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

Current State and Future Perspectives of Energy Sources for Totally Implantable Cardiac Devices.

Science.gov (United States)

Bleszynski, Peter A; Luc, Jessica G Y; Schade, Peter; PhilLips, Steven J; Tchantchaleishvili, Vakhtang

There is a large population of patients with end-stage congestive heart failure who cannot be treated by means of conventional cardiac surgery, cardiac transplantation, or chronic catecholamine infusions. Implantable cardiac devices, many designated as destination therapy, have revolutionized patient care and outcomes, although infection and complications related to external power sources or routine battery exchange remain a substantial risk. Complications from repeat battery replacement, power failure, and infections ultimately endanger the original objectives of implantable biomedical device therapy - eliminating the intended patient autonomy, affecting patient quality of life and survival. We sought to review the limitations of current cardiac biomedical device energy sources and discuss the current state and trends of future potential energy sources in pursuit of a lifelong fully implantable biomedical device.

Triangular and Trapezoidal Fuzzy State Estimation with Uncertainty on Measurements

Directory of Open Access Journals (Sweden)

Mohammad Sadeghi Sarcheshmah

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Kunlin Wei

2010-05-01

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

Junction temperature estimation for an advanced active power cycling test

DEFF Research Database (Denmark)

Choi, Uimin; Blaabjerg, Frede; Jørgensen, S.

2015-01-01

estimation method using on-state VCE for an advanced active power cycling test is proposed. The concept of the advanced power cycling test is explained first. Afterwards the junction temperature estimation method using on-state VCE and current is presented. Further, the method to improve the accuracy...... of the maximum junction temperature estimation is also proposed. Finally, the validity and effectiveness of the proposed method is confirmed by experimental results.......On-state collector-emitter voltage (VCE) is a good indicator to determine the wear-out condition of power device modules. Further, it is a one of the Temperature Sensitive Electrical Parameters (TSEPs) and thus can be used for junction temperature estimation. In this paper, the junction temperature...

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

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

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.

Optical absorption and oxygen passivation of surface states in III-nitride photonic devices

Science.gov (United States)

Rousseau, Ian; Callsen, Gordon; Jacopin, Gwénolé; Carlin, Jean-François; Butté, Raphaël; Grandjean, Nicolas

2018-03-01

III-nitride surface states are expected to impact high surface-to-volume ratio devices, such as nano- and micro-wire light-emitting diodes, transistors, and photonic integrated circuits. In this work, reversible photoinduced oxygen desorption from III-nitride microdisk resonator surfaces is shown to increase optical attenuation of whispering gallery modes by 100 cm-1 at λ = 450 nm. Comparison of photoinduced oxygen desorption in unintentionally and n+-doped microdisks suggests that the spectral changes originate from the unpinning of the surface Fermi level, likely taking place at etched nonpolar III-nitride sidewalls. An oxygen-rich surface prepared by thermal annealing results in a broadband Q improvement to state-of-the-art values exceeding 1 × 104 at 2.6 eV. Such findings emphasize the importance of optically active surface states and their passivation for future nanoscale III-nitride optoelectronic and photonic devices.

The Effect of Interacting with Two Devices when Creating the Illusion of Internal State in Tangible Widgets

DEFF Research Database (Denmark)

Bech, Christoffer; Bork, Andreas Heldbjerg; Memborg, Jakob Birch

2017-01-01

This paper investigates whether the illusion of internal state in passive tangible widgets is stronger when using one touchscreen device or two devices. Passive tangible widgets are an increasingly popular way to interact with tablet games. Since the production of passive widgets is usually cheaper...... than the production of widgets with internal state, it is much more cost-efficient to induce the illusion of internal state in passive widgets than to use tangible widgets with an actual internal state. An experiment was conducted where the participants’ belief in the illusion was determined by means...

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.

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.

Dynamic state estimation techniques for large-scale electric power systems

International Nuclear Information System (INIS)

Rousseaux, P.; Pavella, M.

1991-01-01

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

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

DEFF Research Database (Denmark)

Han, Xue; You, Shi; Thordarson, Fannar

2013-01-01

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

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

Science.gov (United States)

Lovelace, John K.

2009-01-01

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

Device for forecasting reactor power-up routes

International Nuclear Information System (INIS)

Fukuzaki, Takaharu.

1980-01-01

Purpose: To improve the reliability and forecasting accuracy for a device forecasting the change of the state on line in BWR type reactors. Constitution: The present state in a nuclear reactor is estimated in a present state judging section based on measuring signals for thermal power, core flow rate, control rod density and the like from the nuclear reactor, and the estimated results are accumulated in an operation result collecting section. While on the other hand, a forecasting section forecasts the future state in the reactor based on the signals from the forecasting condition setting section. The actual result values from the collecting section and the forecasting results are compared to each other. If they are not equal, new setting signals are outputted from the setting section to perform the forecasting again. These procedures are repeated till the difference between the forecast results and the actual result values is minimized, by which accurate forecasting for the state of the reactor is made possible. (Furukawa, Y.)

Dip-Coating Process Engineering and Performance Optimization for Three-State Electrochromic Devices

Science.gov (United States)

Wu, Lu; Yang, Dejiang; Fei, Lixun; Huang, Yue; Wu, Fang; Sun, Yiling; Shi, Jiayuan; Xiang, Yong

2017-06-01

Titanium dioxide (TiO2) nanoparticles were modified onto fluorine-doped tin oxide (FTO) via dip-coating technique with different nanoparticle sizes, lifting speeds, precursor concentrations, and dipping numbers. Electrodeposition-based electrochromic device with reversible three-state optical transformation (transparent, mirror, and black) was fabricated subsequently by sandwiching a suitable amount of gel electrolyte between modified FTO electrode and flat FTO electrode. Correlation between dip-coating process engineering, morphological features of TiO2 thin films, i.e., thickness and roughness, as well as performance of electrochromic devices, i.e., optical contrast, switching time, and cycling stability, were investigated. The modified device exhibits high optical contrast of 57%, the short coloration/bleaching switching time of 6 and 20 s, and excellent cycling stability after 1500 cycles of only 27% decrement rate by adjusting dip-coating processes engineering. The results in this study will provide valuable guidance for rational design of the electrochromic device with satisfactory performance.

Electric-field enhanced performance in catalysis and solid-state devices involving gases

Science.gov (United States)

Blackburn, Bryan M.; Wachsman, Eric D.; Van Assche, IV, Frederick Martin

2015-05-19

Electrode configurations for electric-field enhanced performance in catalysis and solid-state devices involving gases are provided. According to an embodiment, electric-field electrodes can be incorporated in devices such as gas sensors and fuel cells to shape an electric field provided with respect to sensing electrodes for the gas sensors and surfaces of the fuel cells. The shaped electric fields can alter surface dynamics, system thermodynamics, reaction kinetics, and adsorption/desorption processes. In one embodiment, ring-shaped electric-field electrodes can be provided around sensing electrodes of a planar gas sensor.

Electronic interconnects and devices with topological surface states and methods for fabricating same

Science.gov (United States)

Yazdani, Ali; Ong, N. Phuan; Cava, Robert J.

2016-05-03

An interconnect is disclosed with enhanced immunity of electrical conductivity to defects. The interconnect includes a material with charge carriers having topological surface states. Also disclosed is a method for fabricating such interconnects. Also disclosed is an integrated circuit including such interconnects. Also disclosed is a gated electronic device including a material with charge carriers having topological surface states.

Electronic interconnects and devices with topological surface states and methods for fabricating same

Energy Technology Data Exchange (ETDEWEB)

Yazdani, Ali; Ong, N. Phuan; Cava, Robert J.

2017-04-04

An interconnect is disclosed with enhanced immunity of electrical conductivity to defects. The interconnect includes a material with charge carriers having topological surface states. Also disclosed is a method for fabricating such interconnects. Also disclosed is an integrated circuit including such interconnects. Also disclosed is a gated electronic device including a material with charge carriers having topological surface states.

Evolving reimbursement and pricing policies for devices in Europe and the United States should encourage greater value.

Science.gov (United States)

Sorenson, Corinna; Drummond, Michael; Burns, Lawton R

2013-04-01

Rising health care costs are an international concern, particularly in the United States, where spending on health care outpaces that of other industrialized countries. Consequently, there is growing desire in the United States and Europe to take a more value-based approach to health care, particularly with respect to the adoption and use of new health technology. This article examines medical device reimbursement and pricing policies in the United States and Europe, with a particular focus on value. Compared to the United States, Europe more formally and consistently considers value to determine which technologies to cover and at what price, especially for complex, costly devices. Both the United States and Europe have introduced policies to provide temporary coverage and reimbursement for promising technologies while additional evidence of value is generated. But additional actions are needed in both the United States and Europe to ensure wise value-based reimbursement and pricing policies for all devices, including the generation of better pre- and postmarket evidence and the development of new methods to evaluate value and link evidence of value to reimbursement.

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

Development and validation of a noncontact spectroscopic device for hemoglobin estimation at point-of-care

Science.gov (United States)

Sarkar, Probir Kumar; Pal, Sanchari; Polley, Nabarun; Aich, Rajarshi; Adhikari, Aniruddha; Halder, Animesh; Chakrabarti, Subhananda; Chakrabarti, Prantar; Pal, Samir Kumar

2017-05-01

Anemia severely and adversely affects human health and socioeconomic development. Measuring hemoglobin with the minimal involvement of human and financial resources has always been challenging. We describe a translational spectroscopic technique for noncontact hemoglobin measurement at low-resource point-of-care settings in human subjects, independent of their skin color, age, and sex, by measuring the optical spectrum of the blood flowing in the vascular bed of the bulbar conjunctiva. We developed software on the LabVIEW platform for automatic data acquisition and interpretation by nonexperts. The device is calibrated by comparing the differential absorbance of light of wavelength 576 and 600 nm with the clinical hemoglobin level of the subject. Our proposed method is consistent with the results obtained using the current gold standard, the automated hematology analyzer. The proposed noncontact optical device for hemoglobin estimation is highly efficient, inexpensive, feasible, and extremely useful in low-resource point-of-care settings. The device output correlates with the different degrees of anemia with absolute and trending accuracy similar to those of widely used invasive methods. Moreover, the device can instantaneously transmit the generated report to a medical expert through e-mail, text messaging, or mobile apps.

Plasma parameter estimations for the Large Helical Device based on the gyro-reduced Bohm scaling

International Nuclear Information System (INIS)

Okamoto, Masao; Nakajima, Noriyoshi; Sugama, Hideo.

1991-10-01

A model of gyro-reduced Bohm scaling law is incorporated into a one-dimensional transport code to predict plasma parameters for the Large Helical Device (LHD). The transport code calculations reproduce well the LHD empirical scaling law and basic parameters and profiles of the LHD plasma are calculated. The amounts of toroidal currents (bootstrap current and beam-driven current) are also estimated. (author)

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

Medical devices and the Middle East: market, regulation, and reimbursement in Gulf Cooperation Council states

Directory of Open Access Journals (Sweden)

Howard JJ

2014-11-01

Full Text Available Jason J Howard Division of Paediatric Orthopaedics, Department of Surgery, Sidra Medical and Research Center, Doha, Qatar Abstract: With some of the richest economies in the world, the Gulf Cooperation Council (GCC is undergoing rapid growth not only in its population but also in health care expenditure. Despite the GCC's abundance of hydrocarbon-based wealth, the drivers of the medical device industry in the GCC are still in flux, with gains yet to be made in areas of infrastructure, regulation, and reimbursement. However, the regional disease burden, expanding health insurance penetration, increasing privatization, and a desire to attract skilled expatriate health care providers have led to favorable conditions for the medical device market in the GCC. The purpose of this article is to investigate the current state of the GCC medical device industry, with respect to market, regulation, and reimbursement, paying special attention to the three largest medical device markets: Saudi Arabia, the United Arab Emirates, and Qatar. The GCC would seem to represent fertile ground for the development of medical technologies, especially those in line with the regional health priorities of the respective member states. Keywords: medical devices, regulation, reimbursement, Middle East 

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...

Estimation of the two-dimensional presampled modulation transfer function of digital radiography devices using one-dimensional test objects

International Nuclear Information System (INIS)

Wells, Jered R.; Dobbins, James T. III

2012-01-01

Purpose: The modulation transfer function (MTF) of medical imaging devices is commonly reported in the form of orthogonal one-dimensional (1D) measurements made near the vertical and horizontal axes with a slit or edge test device. A more complete description is found by measuring the two-dimensional (2D) MTF. Some 2D test devices have been proposed, but there are some issues associated with their use: (1) they are not generally available; (2) they may require many images; (3) the results may have diminished accuracy; and (4) their implementation may be particularly cumbersome. This current work proposes the application of commonly available 1D test devices for practical and accurate estimation of the 2D presampled MTF of digital imaging systems. Methods: Theory was developed and applied to ensure adequate fine sampling of the system line spread function for 1D test devices at orientations other than approximately vertical and horizontal. Methods were also derived and tested for slit nonuniformity correction at arbitrary angle. Techniques were validated with experimental measurements at ten angles using an edge test object and three angles using a slit test device on an indirect-detection flat-panel system [GE Revolution XQ/i (GE Healthcare, Waukesha, WI)]. The 2D MTF was estimated through a simple surface fit with interpolation based on Delaunay triangulation of the 1D edge-based MTF measurements. Validation by synthesis was also performed with simulated images from a hypothetical direct-detection flat-panel device. Results: The 2D MTF derived from physical measurements yielded an average relative precision error of 0.26% for frequencies below the cutoff (2.5 mm −1 ) and approximate circular symmetry at frequencies below 4 mm −1 . While slit analysis generally agreed with the results of edge analysis, the two showed subtle differences at frequencies above 4 mm −1 . Slit measurement near 45° revealed radial asymmetry in the MTF resulting from the square

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

KAUST Repository

El Gharamti, Mohamad

2013-10-01

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

Support vector machines for nuclear reactor state estimation

Energy Technology Data Exchange (ETDEWEB)

Zavaljevski, N.; Gross, K. C.

2000-02-14

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

Support vector machines for nuclear reactor state estimation

International Nuclear Information System (INIS)

Zavaljevski, N.; Gross, K. C.

2000-01-01

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

Method for estimating capacity and predicting remaining useful life of lithium-ion battery

International Nuclear Information System (INIS)

Hu, Chao; Jain, Gaurav; Tamirisa, Prabhakar; Gorka, Tom

2014-01-01

Highlights: • We develop an integrated method for the capacity estimation and RUL prediction. • A state projection scheme is derived for capacity estimation. • The Gauss–Hermite particle filter technique is used for the RUL prediction. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the capacity of Li-ion battery and predict the remaining useful life (RUL) throughout the whole life-time. This paper presents an integrated method for the capacity estimation and RUL prediction of Li-ion battery used in implantable medical devices. A state projection scheme from the author’s previous study is used for the capacity estimation. Then, based on the capacity estimates, the Gauss–Hermite particle filter technique is used to project the capacity fade to the end-of-service (EOS) value (or the failure limit) for the RUL prediction. Results of 10 years’ continuous cycling test on Li-ion prismatic cells in the lab suggest that the proposed method achieves good accuracy in the capacity estimation and captures the uncertainty in the RUL prediction. Post-explant weekly cycling data obtained from field cells with 4–7 implant years further verify the effectiveness of the proposed method in the capacity estimation

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.

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.

High efficiency solid-state sensitized heterojunction photovoltaic device

KAUST Repository

Wang, Mingkui

2010-06-01

The high molar extinction coefficient heteroleptic ruthenium dye, NaRu(4,4′-bis(5-(hexylthio)thiophen-2-yl)-2,2′-bipyridine) (4-carboxylic acid-4′-carboxylate-2,2′-bipyridine) (NCS) 2, exhibits certified 5% electric power conversion efficiency at AM 1.5 solar irradiation (100 mW cm-2) in a solid-state dye-sensitized solar cell using 2,2′,7,7′-tetrakis-(N,N-di-pmethoxyphenylamine)-9, 9′-spirobifluorene (spiro-MeOTAD) as the organic hole-transporting material. This demonstration elucidates a class of photovoltaic devices with potential for low-cost power generation. © 2010 Elsevier Ltd. All rights reserved.

High efficiency solid-state sensitized heterojunction photovoltaic device

KAUST Repository

Wang, Mingkui; Liu, Jingyuan; Cevey-Ha, Ngoc-Le; Moon, Soo-Jin; Liska, Paul; Humphry-Baker, Robin; Moser, Jacques-E.; Grä tzel, Carole; Wang, Peng; Zakeeruddin, Shaik M.

2010-01-01

The high molar extinction coefficient heteroleptic ruthenium dye, NaRu(4,4′-bis(5-(hexylthio)thiophen-2-yl)-2,2′-bipyridine) (4-carboxylic acid-4′-carboxylate-2,2′-bipyridine) (NCS) 2, exhibits certified 5% electric power conversion efficiency at AM 1.5 solar irradiation (100 mW cm-2) in a solid-state dye-sensitized solar cell using 2,2′,7,7′-tetrakis-(N,N-di-pmethoxyphenylamine)-9, 9′-spirobifluorene (spiro-MeOTAD) as the organic hole-transporting material. This demonstration elucidates a class of photovoltaic devices with potential for low-cost power generation. © 2010 Elsevier Ltd. All rights reserved.

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.

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

Energy performance of a micro-cogeneration device during transient and steady-state operation: Experiments and simulations

International Nuclear Information System (INIS)

Rosato, Antonio; Sibilio, Sergio

2013-01-01

Micro-cogeneration is a well-established technology and its deployment has been considered by the European Community as one of the most effective measure to save primary energy and to reduce greenhouse gas emissions. As a consequence, the estimation of the potential impact of micro-cogeneration devices is necessary to design policy and to energetically, ecologically and economically rank these systems among other potential energy saving and CO 2 -reducing measures. Even if transient behaviour can be very important when the engine is frequently started and stopped and allowed to cool-down in between, for the sake of simplicity mainly static and simplified methods are used for assessing the performance of cogeneration devices, completely neglecting the dynamic response of the units themselves. In the first part of this paper a series of experiments is illustrated and discussed in detail in order to highlight and compare the transient and stationary operation of a natural gas fuelled reciprocating internal combustion engine based cogeneration unit with 6.0 kW as nominal electric output and 11.7 kW as nominal thermal output. The measured performance of the cogeneration device is also compared with the performance of the system calculated on the basis of the efficiency values suggested by the manufacturer in order to highlight and quantify the discrepancy between the two approaches in evaluating the unit operation. Finally the experimental data are also compared with those predicted by a simulation model developed within IEA/ECBCS Annex 42 and experimentally calibrated by the authors in order to assess the model reliability for studying and predicting the performance of the system under different operating scenarios. -- Highlights: ► Transient operation of a cogeneration system has been experimentally investigated. ► Steady-state operation of a cogeneration device has been experimentally evaluated. ► Measured data have been compared with those predicted by a

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...

Bladder wall thickness and ultrasound estimated bladder weight in healthy adults with portative ultrasound device

Directory of Open Access Journals (Sweden)

Selcen Kanyilmaz

2013-01-01

Full Text Available Background: The aim of this study was to investigate bladder wall thickness (BWT and ultrasound estimated bladder weight (UEBW values in healthy population with a portative ultrasound device and their relationship with demographic parameters. Materials and Methods: The study was carried out in Neurorehabilitation Clinic of Ege University Hospital. Ninety-five subjects (48 women and 47 men aged between 18 and 56 were included in the study. BWT and UEBW were determined non-invasively with a portative ultrasound device; Bladder Scan BVM 6500 (Verathon Inc., WA, USA at a frequency of 3.7 MHz at functional bladder capacity. These values were compared by gender, and their relation was assessed with age, body mass index (BMI and parity. Results: Mean BWT was 2.0 ± 0.4 mm and UEBW was 44.6 ± 8.3 g at a mean volume of 338.0 ± 82.1 ml. Although higher results were obtained in men at higher bladder volumes, the results did not differ significantly by gender. Correlation analyses revealed statistically significant correlation between UEBW and age (r = 0.32. BWT was negatively correlated with volume (r = -0.50 and bladder surface area (r = -0.57. Also, statistically significant correlations were observed between UEBW and volume (r = 0.36, bladder surface area (r = 0.48 and BWT (r = 0.25. Conclusion: Determined values of BWT and UEBW in healthy population are estimated with portative ultrasound devices, which are future promising, for their convenient, easy, non-invasive, time-efficient hand-held use for screening.

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

2016-08-29

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

Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

KAUST Repository

Unknown author

2016-01-01

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

Estimation of Amount of Scattered Neutrons at Devices PFZ and GIT-12 by MCNP Simulations

Directory of Open Access Journals (Sweden)

Ondrej Šíla

2013-01-01

Full Text Available Our work is dedicated to pinch effect occurring during current discharge in deuterium plasma, and our results are connected with two devices – plasma focus PFZ, situated in the Faculty of Electrical Engineering, CTU, Prague, and Z-pinch GIT-12, which is situated in the Institute of High Current Electronics, Tomsk. During fusion reactions that proceed in plasma during discharge, neutrons are produced. We use neutrons as instrument for plasma diagnostics. Despite of the advantage that neutrons do not interact with electric and magnetic fields inside device, they are inevitably scattered by materials that are placed between their source and probe, and information about plasma from which they come from is distorted. For estimation of rate of neutron scattering we use MCNP code.

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.

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.

Medical devices and the Middle East: market, regulation, and reimbursement in Gulf Cooperation Council states.

Science.gov (United States)

Howard, Jason J

2014-01-01

With some of the richest economies in the world, the Gulf Cooperation Council (GCC) is undergoing rapid growth not only in its population but also in health care expenditure. Despite the GCC's abundance of hydrocarbon-based wealth, the drivers of the medical device industry in the GCC are still in flux, with gains yet to be made in areas of infrastructure, regulation, and reimbursement. However, the regional disease burden, expanding health insurance penetration, increasing privatization, and a desire to attract skilled expatriate health care providers have led to favorable conditions for the medical device market in the GCC. The purpose of this article is to investigate the current state of the GCC medical device industry, with respect to market, regulation, and reimbursement, paying special attention to the three largest medical device markets: Saudi Arabia, the United Arab Emirates, and Qatar. The GCC would seem to represent fertile ground for the development of medical technologies, especially those in line with the regional health priorities of the respective member states.

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...

Stress-induced state transitions in flexible liquid-crystal devices

International Nuclear Information System (INIS)

Ho, I-Lin; Chang, Yia-Chung

2012-01-01

This work studies the stress-strain dynamics for the transient optoelectronic characteristics of flexible liquid-crystal (LC) devices. Due to the fast response of LC directors, the configuration of the LC is assumed to be in quasi-equilibrium during the process of elastic deformations of the flexible structures. The LC medium hence can be treated effectively as a thin-film layer and can approximately follow the strain-stress mechanism in the solids. Relevant theoretical algorithms are studied in this work, and numerical results present the stress-induced state transitions in the π cell.

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

Full State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

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

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

Full State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

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

2007-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-08-01

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

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

Science.gov (United States)

Zong, Changfu; Hu, Dan; Zheng, Hongyu

2013-03-01

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

State estimation of chemical engineering systems tending to multiple solutions

Directory of Open Access Journals (Sweden)

N. P. G. Salau

2014-09-01

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

State estimation and synchronization of pendula systems over digital communication channels

Science.gov (United States)

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

2014-04-01

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

Estimated United States Transportation Energy Use 2005

Energy Technology Data Exchange (ETDEWEB)

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

2011-11-09

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

Prototype solid-state electrochromic window devices

International Nuclear Information System (INIS)

Dao, L.H.; Nguyen, M.T.

1989-01-01

This paper discusses electrochromic smart windows which are prospective devices for the control of light transmission in response to the variation of brightness of the environment. The fabrication of electrochromic windows based on cathodically coloring transition metal oxides and anodically coloring conducting polymers are described. The device consists of gel or glassy polymer electrolytes sandwiches by a pair of transparent conducting glass coated respectively with a thin film of WO 3 or MoO 3 prepared by electrodeposition, and with a thin film of ploy(aniline) derivatives obtained by electropolymerization or solution casting. The electrochromic properties of the five-layer smart window devices are presented

Automated pose estimation of objects using multiple ID devices for handling and maintenance task in nuclear fusion reactor

International Nuclear Information System (INIS)

Umetani, Tomohiro; Morioka, Jun-ichi; Tamura, Yuichi; Inoue, Kenji; Arai, Tatsuo; Mae, Yasusi

2011-01-01

This paper describes a method for the automated estimation of three-dimensional pose (position and orientation) of objects by autonomous robots, using multiple identification (ID) devices. Our goal is to estimate the object pose for assembly or maintenance tasks in a real nuclear fusion reactor system, with autonomous robots cooperating in a virtual assembly system. The method estimates the three-dimensional pose for autonomous robots. This paper discusses a method of motion generation for ID acquisition using the sensory data acquired by the measurement system attached to the robots and from the environment. Experimental results show the feasibility of the proposed method. (author)

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.

Reactor power distribution pattern judging device

International Nuclear Information System (INIS)

Ikehara, Tadashi.

1992-01-01

The judging device of the present invention comprises a power distribution readout system for intaking a power value from a fuel segment, a neural network having an experience learning function for receiving a power distribution value as an input variant, mapping it into a desirable property and self-organizing the map, and a learning date base storing a plurality of learnt samples. The read power distribution is classified depending on the similarity thereof with any one of representative learnt power distribution, and the corresponding state of the reactor core is outputted as a result of the judgement. When an error is found in the classified judging operation, erroneous cases are additionally learnt by using the experience and learning function, thereby improving the accuracy of the reactor core characteristic estimation operation. Since the device is mainly based on the neural network having a self-learning function and a pattern classification and judging function, a judging device having a human's intuitive pattern recognition performance and a pattern experience and learning performance is obtainable, thereby enabling to judge the state of the reactor core accurately. (N.H.)

Studies of solid-state electrochromic devices based on Peo/siliceous hybrids doped with lithium perchlorate

International Nuclear Information System (INIS)

Barbosa, P.C.; Silva, M.M.; Smith, M.J.; Goncalves, A.; Fortunato, E.

2007-01-01

Sol-gel hybrid organic-inorganic networks, doped with a lithium salt, have been used as electrolytes in prototype smart windows. The work described in this presentation is focused on the application of these networks as dual-function electrolyte/adhesive components in solid-state electrochromic devices. The performance of multi-layer electrochromic devices was characterized as a function of the choice of precursor used to prepare the polymer electrolyte component and the guest salt concentration. The prototype devices exhibited good open-circuit memory, coloration efficiency, optical contrast and stability

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.

An improved fuzzy Kalman filter for state estimation of nonlinear systems

International Nuclear Information System (INIS)

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

2008-01-01

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

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

DEFF Research Database (Denmark)

Mohd. Azam, Sazuan Nazrah

2017-01-01

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

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

Science.gov (United States)

Uzunoglu, B.; Hussaini, Y.

2017-12-01

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

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.

Model-based state estimator for an intelligent tire

NARCIS (Netherlands)

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

2017-01-01

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

Model-based State Estimator for an Intelligent Tire

NARCIS (Netherlands)

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

2016-01-01

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

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

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

Science.gov (United States)

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

2017-11-01

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

On state estimation and fusion with elliptical constraints

Energy Technology Data Exchange (ETDEWEB)

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

2017-11-01

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

State and Substate Estimates of Nonmedical Use of Prescription Pain Relievers

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

State Estimation for Landing Maneuver on High Performance Aircraft

Science.gov (United States)

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

2018-01-01

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

Learning to Estimate Dynamical State with Probabilistic Population Codes.

Directory of Open Access Journals (Sweden)

Joseph G Makin

2015-11-01

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

Estimates of state-level health-care expenditures associated with disability.

Science.gov (United States)

Anderson, Wayne L; Armour, Brian S; Finkelstein, Eric A; Wiener, Joshua M

2010-01-01

We estimated state-level disability-associated health-care expenditures (DAHE) for the U.S. adult population. We used a two-part model to estimate DAHE for the noninstitutionalized U.S. civilian adult population using data from the 2002-2003 Medical Expenditure Panel Survey and state-level data from the Behavioral Risk Factor Surveillance System. Administrative data for people in institutions were added to generate estimates for the total adult noninstitutionalized population. Individual-level data on total health-care expenditures along with demographic, socioeconomic, geographic, and payer characteristics were used in the models. The DAHE for all U.S. adults totaled $397.8 billion in 2006, with state expenditures ranging from $598 million in Wyoming to $40.1 billion in New York. Of the national total, the DAHE were $118.9 billion for the Medicare population, $161.1 billion for Medicaid recipients, and $117.8 billion for the privately insured and uninsured populations. For the total U.S. adult population, 26.7% of health-care expenditures were associated with disability, with proportions by state ranging from 16.9% in Hawaii to 32.8% in New York. This proportion varied greatly by payer, with 38.1% for Medicare expenditures, 68.7% for Medicaid expenditures, and 12.5% for nonpublic health-care expenditures associated with disability. DAHE vary greatly by state and are borne largely by the public sector, and particularly by Medicaid. Policy makers need to consider initiatives that will help reduce the prevalence of disabilities and disability-related health disparities, as well as improve the lives of people with disabilities.

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

Directory of Open Access Journals (Sweden)

Bo Xu

2016-06-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

DEFF Research Database (Denmark)

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

2017-01-01

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

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

KAUST Repository

Majeed, Muhammad Usman

2017-07-19

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

Practical global oceanic state estimation

Science.gov (United States)

Wunsch, Carl; Heimbach, Patrick

2007-06-01

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

Passive devices of a reactor stop: classification of the characteristics and estimation of perfection degree

International Nuclear Information System (INIS)

Portyanoj, A.G.; Serdun', E.N.; Sorokin, A.P.; Egorov, V.S.; Shkarovskij, D.A.

1998-01-01

The perspective direction in NPP safety improvement connected with development of passive devices for nuclear reactor emergency shutdown (PDRS) is discussed. More than hundred devices which can fulfil the PDRS functions are suggested nowadays. The analysis of PDRS designing status as applicable for the fast reactors in the main which are based on the physical effect used in an element sensitive to temperature is made. The complex consisting of nine general characteristics including passive character, thresholdness, forces generation, inertia, multichannel design, stability towards operational factors, safety at failures, simplicity and visualisation, development conditions, is suggested for estimation of the quality of PDRS of different types. Basing on expert assessments realized using the complex of general characteristics it is shown that the types of PDRS may be separated into following three groups: linear expansion of solid bodies and thermoelectric ones (K ≅ 0.45); magnet ones with shape memory effect, liquid volume expansion (K ≅ 0.6); fusing ones (K ≅ 0.7). The conclusion is made that PDRS on the basis of fusing devices of the sulphon type with liofobic capillary-porous working body most completely satisfy the complex of general characteristics considered

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....

Defect engineering: design tools for solid state electrochemical devices

International Nuclear Information System (INIS)

Tuller, Harry L.

2003-01-01

The interest in solid state electrochemical devices including sensors, fuel cells, batteries, oxygen permeation membranes, etc. has grown rapidly in recent years. Many of the same figures of merit apply to these different applications, the key ones being ionic conduction in solid electrolytes, mixed ionic-electronic conduction (MIEC) in electrodes and permeation membranes, and gas-solid reaction kinetics in sensors and fuel cells. Optimization of device performance often relies on the careful understanding and control of both ionic and electronic defects in the materials that make up the key device components. To date, most materials in use have been discovered serendipitously. A key focus of this paper is on the tools available to scientists and engineers to practice 'defect engineering' for the purpose of optimizing the performance of such materials. Dopants, controlled structural disorder, and interfaces are examined in relation to increasing the conductivity of solid electrolytes. The creation of defect bands is demonstrated as a means for introducing high levels of electronic conductivity into a solid electrolyte for the purpose of creating a mixed conductor and thereby a monolithic fuel cell structure. Dopants are also examined as a means of reducing losses in a high temperature resonant sensor platform. The control of microstructure, down to the nano-scale, is shown capable of inverting the predominant ionic to an electronic charge carrier and thereby markedly modifying electrical properties. Electrochemical bias and light are also discussed in terms of creating defects locally thereby providing means for micromachining a broad range of materials with precise dimensional control, low residual stress and controlled etch rates

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

Protection device for a thermonuclear device

International Nuclear Information System (INIS)

Kawashima, Shuichi.

1986-01-01

Purpose: To exactly detect the void coefficients of coolants even under high magnetic fields thereby detect the overheat of a thermonuclear device at an early stage. Constitution: The protecting device of this invention comprises a laser beam generation device, a laser beam detection device and an accident detection device. The laser generation device always generates laser beams, which are permeated through coolants and detected by the laser beam detection device, the optical amount of which is transmitted to the accident detection device. The accident detection device judges the excess or insufficiency of the detected optical amount with respect to the optical amount of the laser beams under the stationary state as a reference and issues an accident signal. Since only the optical cables that do not undergo the effect of the magnetic fields are exposed to high magnetic fields in the protection device of this invention, a high reliability can be maintained. (Kamimura, M.)

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.

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.

The Estimation of Cortical Activity for Brain-Computer Interface: Applications in a Domotic Context

Directory of Open Access Journals (Sweden)

F. Babiloni

2007-08-01

Full Text Available In order to analyze whether the use of the cortical activity, estimated from noninvasive EEG recordings, could be useful to detect mental states related to the imagination of limb movements, we estimate cortical activity from high-resolution EEG recordings in a group of healthy subjects by using realistic head models. Such cortical activity was estimated in region of interest associated with the subject's Brodmann areas by using a depth-weighted minimum norm technique. Results showed that the use of the cortical-estimated activity instead of the unprocessed EEG improves the recognition of the mental states associated to the limb movement imagination in the group of normal subjects. The BCI methodology presented here has been used in a group of disabled patients in order to give them a suitable control of several electronic devices disposed in a three-room environment devoted to the neurorehabilitation. Four of six patients were able to control several electronic devices in this domotic context with the BCI system.

Organic bistable light-emitting devices

Science.gov (United States)

Ma, Liping; Liu, Jie; Pyo, Seungmoon; Yang, Yang

2002-01-01

An organic bistable device, with a unique trilayer structure consisting of organic/metal/organic sandwiched between two outmost metal electrodes, has been invented. [Y. Yang, L. P. Ma, and J. Liu, U.S. Patent Pending, U.S. 01/17206 (2001)]. When the device is biased with voltages beyond a critical value (for example 3 V), the device suddenly switches from a high-impedance state to a low-impedance state, with a difference in injection current of more than 6 orders of magnitude. When the device is switched to the low-impedance state, it remains in that state even when the power is off. (This is called "nonvolatile" phenomenon in memory devices.) The high-impedance state can be recovered by applying a reverse bias; therefore, this bistable device is ideal for memory applications. In order to increase the data read-out rate of this type of memory device, a regular polymer light-emitting diode has been integrated with the organic bistable device, such that it can be read out optically. These features make the organic bistable light-emitting device a promising candidate for several applications, such as digital memories, opto-electronic books, and recordable papers.

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.

Accelerated Aging System for Prognostics of Power Semiconductor Devices

Science.gov (United States)

Celaya, Jose R.; Vashchenko, Vladislav; Wysocki, Philip; Saha, Sankalita

2010-01-01

Prognostics is an engineering discipline that focuses on estimation of the health state of a component and the prediction of its remaining useful life (RUL) before failure. Health state estimation is based on actual conditions and it is fundamental for the prediction of RUL under anticipated future usage. Failure of electronic devices is of great concern as future aircraft will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. Therefore, development of prognostics solutions for electronics is of key importance. This paper presents an accelerated aging system for gate-controlled power transistors. This system allows for the understanding of the effects of failure mechanisms, and the identification of leading indicators of failure which are essential in the development of physics-based degradation models and RUL prediction. In particular, this system isolates electrical overstress from thermal overstress. Also, this system allows for a precise control of internal temperatures, enabling the exploration of intrinsic failure mechanisms not related to the device packaging. By controlling the temperature within safe operation levels of the device, accelerated aging is induced by electrical overstress only, avoiding the generation of thermal cycles. The temperature is controlled by active thermal-electric units. Several electrical and thermal signals are measured in-situ and recorded for further analysis in the identification of leading indicators of failures. This system, therefore, provides a unique capability in the exploration of different failure mechanisms and the identification of precursors of failure that can be used to provide a health management solution for electronic devices.

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.

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.

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.

Carrying Position Independent User Heading Estimation for Indoor Pedestrian Navigation with Smartphones

Directory of Open Access Journals (Sweden)

Zhi-An Deng

2016-05-01

Full Text Available This paper proposes a novel heading estimation approach for indoor pedestrian navigation using the built-in inertial sensors on a smartphone. Unlike previous approaches constraining the carrying position of a smartphone on the user’s body, our approach gives the user a larger freedom by implementing automatic recognition of the device carrying position and subsequent selection of an optimal strategy for heading estimation. We firstly predetermine the motion state by a decision tree using an accelerometer and a barometer. Then, to enable accurate and computational lightweight carrying position recognition, we combine a position classifier with a novel position transition detection algorithm, which may also be used to avoid the confusion between position transition and user turn during pedestrian walking. For a device placed in the trouser pockets or held in a swinging hand, the heading estimation is achieved by deploying a principal component analysis (PCA-based approach. For a device held in the hand or against the ear during a phone call, user heading is directly estimated by adding the yaw angle of the device to the related heading offset. Experimental results show that our approach can automatically detect carrying positions with high accuracy, and outperforms previous heading estimation approaches in terms of accuracy and applicability.

Cultural and Demographic Factors Influencing Noise Exposure Estimates from Use of Portable Listening Devices in an Urban Environment

Science.gov (United States)

Fligor, Brian J.; Levey, Sandra; Levey, Tania

2014-01-01

Purpose: This study examined listening levels and duration of portable listening devices (PLDs) used by people with diversity of ethnicity, education, music genre, and PLD manufacturer. The goal was to estimate participants' PLD noise exposure and identify factors influencing user behavior. Method: This study measured listening levels of 160…

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.

Gain optimization method of a DQW superluminescent diode with broad multi-state emission

KAUST Repository

Dimas, Clara E.

2010-01-01

Optimizing gain through systematic methods of varying current injection schemes analytically is significant to maximize experimentally device yield and evaluation. Various techniques are used to calculate the amplified spontaneous emission (ASE) gain for light emitting devices consisting of single-section and multiple-sections of even length. Recently double quantum well (DQW) superluminescent diodes (SLD) have shown a broad multi-state emission due to mutlielectrodes of non-equal lengths and at high non-equal current densities. In this study, we adopt an improved method utilizing an ASE intensity ratio to calibrate a gain curve based on the sum of the measured ASE spectra to efficiently estimate the gain. Although the laser gain for GaAs/AlGaAs material is well studied, the ASE gain of SLD devices has not been systematically studied particular to further explain the multiple-state emission observed in fabricated devices. In addition a unique gain estimate was achieved where the excited state gain clamps prior to the ground state due to approaching saturation levels. In our results, high current densities in long sectioned active regions achieved sufficient un-truncated gain that show evidence of excited state emission has been observed.

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)

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

Radiation-induced interface state generation in MOS devices with reoxidised nitrided SiO2 gate dielectrics

International Nuclear Information System (INIS)

Lo, G.Q.; Shih, D.K.; Ting, W.; Kwong, D.L.

1989-01-01

In this letter, the radiation-induced interface state generation ΔD it in MOS devices with reoxidised nitrided gate oxides has been studied. The reoxidised nitrided oxides were fabricated by rapid thermal reoxidation (RTO) of rapidly thermal nitrided (RTN) SiO 2 . The devices were irradiated by exposure to X-rays at doses of 0.5-5.0 Mrad (Si). It is found that the RTO process improves the radiation hardness of RTN oxides in terms of interface state generation. The enhanced interface ''hardness'' of reoxidised nitrided oxides is attributed to the strainless interfacial oxide regrowth or reduction of hydrogen concentration during RTO of RTN oxides. (author)

Estimation of four-dimensional dose distribution using electronic portal imaging device in radiation therapy

International Nuclear Information System (INIS)

Mizoguchi, Asumi; Arimura, Hidetaka; Shioyama, Yoshiyuki

2013-01-01

We are developing a method to evaluate four-dimensional radiation dose distribution in a patient body based upon the animated image of EPID (electronic portal imaging device) which is an image of beam-direction at the irradiation. In the first place, we have obtained the image of the dose which is emitted from patient body at therapy planning using therapy planning CT image and dose evaluation algorism. In the second place, we have estimated the emission dose image at the irradiation using EPID animated image which is obtained at the irradiation. In the third place, we have got an affine transformation matrix including respiratory movement in the body by performing linear registration on the emission dose image at therapy planning to get the one at the irradiation. In the fourth place, we have applied the affine transformation matrix on the therapy planning CT image and estimated the CT image 'at irradiation'. Finally we have evaluated four-dimensional dose distribution by calculating dose distribution in the CT image 'at irradiation' which has been estimated for each frame of the EPID animated-image. This scheme may be useful for evaluating therapy results and risk management. (author)

Estimation and harvesting of human heat power for wearable electronic devices

International Nuclear Information System (INIS)

Dziurdzia, P; Brzozowski, I; Bratek, P; Gelmuda, W; Kos, A

2016-01-01

The paper deals with the issue of self-powered wearable electronic devices that are capable of harvesting free available energy dissipated by the user in the form of human heat. The free energy source is intended to be used as a secondary power source supporting primary battery in a sensor bracelet. The main scope of the article is a presentation of the concept for a measuring setup used to quantitative estimation of heat power sources in different locations over the human body area. The crucial role in the measurements of the human heat plays a thermoelectric module working in the open circuit mode. The results obtained during practical tests are confronted with the requirements of the dedicated thermoelectric generator. A prototype design of a human warmth energy harvester with an ultra-low power DC-DC converter based on the LTC3108 circuit is analysed

Thermal energy storage devices, systems, and thermal energy storage device monitoring methods

Science.gov (United States)

Tugurlan, Maria; Tuffner, Francis K; Chassin, David P.

2016-09-13

Thermal energy storage devices, systems, and thermal energy storage device monitoring methods are described. According to one aspect, a thermal energy storage device includes a reservoir configured to hold a thermal energy storage medium, a temperature control system configured to adjust a temperature of the thermal energy storage medium, and a state observation system configured to provide information regarding an energy state of the thermal energy storage device at a plurality of different moments in time.

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

Science.gov (United States)

Warren, Robert; Warren, John Robert

2013-01-01

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

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

Science.gov (United States)

Warren, Robert; Warren, John Robert

2013-06-01

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

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

Kulkarni, Rishikesh; Rastogi, Pramod

2018-05-01

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

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

Science.gov (United States)

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

2002-01-01

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

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

Tri-state resistive switching characteristics of MnO/Ta2O5 resistive random access memory device by a controllable reset process

Science.gov (United States)

Lee, N. J.; Kang, T. S.; Hu, Q.; Lee, T. S.; Yoon, T.-S.; Lee, H. H.; Yoo, E. J.; Choi, Y. J.; Kang, C. J.

2018-06-01

Tri-state resistive switching characteristics of bilayer resistive random access memory devices based on manganese oxide (MnO)/tantalum oxide (Ta2O5) have been studied. The current–voltage (I–V) characteristics of the Ag/MnO/Ta2O5/Pt device show tri-state resistive switching (RS) behavior with a high resistance state (HRS), intermediate resistance state (IRS), and low resistance state (LRS), which are controlled by the reset process. The MnO/Ta2O5 film shows bipolar RS behavior through the formation and rupture of conducting filaments without the forming process. The device shows reproducible and stable RS both from the HRS to the LRS and from the IRS to the LRS. In order to elucidate the tri-state RS mechanism in the Ag/MnO/Ta2O5/Pt device, transmission electron microscope (TEM) images are measured in the LRS, IRS and HRS. White lines like dendrites are observed in the Ta2O5 film in both the LRS and the IRS. Poole–Frenkel conduction, space charge limited conduction, and Ohmic conduction are proposed as the dominant conduction mechanisms for the Ag/MnO/Ta2O5/Pt device based on the obtained I–V characteristics and TEM images.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

A concise account of techniques available for shipboard sea state estimation

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Hongxiao Yu

2015-05-01

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

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

NARCIS (Netherlands)

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

2013-01-01

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

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

DEFF Research Database (Denmark)

Wang, Yanbo; Tian, Yanjun; Wang, Xiongfei

2014-01-01

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

Adaptive state-of-charge indication system for a Li-ion battery-powered devices

NARCIS (Netherlands)

Pop, V.; Danilov, D.; Bergveld, H.J.; Notten, P.H.L.; Regtien, P.P.L.

2006-01-01

Accurate State-of-Charge (SoC) and remammg run-time indication for portable devices is important for the user convenience and to prolong the lifetime of batteries. So far, no one succeeded in coming up with a SoC system that is accurate enough under all realistic user conditions. An algorithm that

Process control device

International Nuclear Information System (INIS)

Hayashi, Toshifumi; Kobayashi, Hiroshi.

1994-01-01

A process control device comprises a memory device for memorizing a plant operation target, a plant state or a state of equipments related with each other as control data, a read-only memory device for storing programs, a plant instrumentation control device or other process control devices, an input/output device for performing input/output with an operator, and a processing device which conducts processing in accordance with the program and sends a control demand or a display demand to the input/output device. The program reads out control data relative to a predetermined operation target, compares and verify them with actual values to read out control data to be a practice premise condition which is further to be a practice premise condition if necessary, thereby automatically controlling the plant or requiring or displaying input. Practice presuming conditions for the operation target can be examined succesively in accordance with the program without constituting complicated logical figures and AND/OR graphs. (N.H.)

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

Science.gov (United States)

Song, Yu; Nuske, Stephen; Scherer, Sebastian

2016-12-22

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

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

KAUST Repository

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

2016-01-01

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

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

KAUST Repository

Ait-El-Fquih, Boujemaa

2016-08-12

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

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

Science.gov (United States)

Ahmadian Behrooz, Hesam; Boozarjomehry, R Bozorgmehry

2015-09-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Hicham Chaoui

2017-04-01

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

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

International Nuclear Information System (INIS)

Chen Lin; Zhu Huangjun; Wei, Tzu-Chieh

2011-01-01

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

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

DEFF Research Database (Denmark)

Zhao, Junbo; Zhang, Gexiang; Das, Kaushik

2016-01-01

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

A flexible super-capacitive solid-state power supply for miniature implantable medical devices.

Science.gov (United States)

Meng, Chuizhou; Gall, Oren Z; Irazoqui, Pedro P

2013-12-01

We present a high-energy local power supply based on a flexible and solid-state supercapacitor for miniature wireless implantable medical devices. Wireless radio-frequency (RF) powering recharges the supercapacitor through an antenna with an RF rectifier. A power management circuit for the super-capacitive system includes a boost converter to increase the breakdown voltage required for powering device circuits, and a parallel conventional capacitor as an intermediate power source to deliver current spikes during high current transients (e.g., wireless data transmission). The supercapacitor has an extremely high area capacitance of ~1.3 mF/mm(2), and is in the novel form of a 100 μm-thick thin film with the merit of mechanical flexibility and a tailorable size down to 1 mm(2) to meet various clinical dimension requirements. We experimentally demonstrate that after fully recharging the capacitor with an external RF powering source, the supercapacitor-based local power supply runs a full system for electromyogram (EMG) recording that consumes ~670 μW with wireless-data-transmission functionality for a period of ~1 s in the absence of additional RF powering. Since the quality of wireless powering for implantable devices is sensitive to the position of those devices within the RF electromagnetic field, this high-energy local power supply plays a crucial role in providing continuous and reliable power for medical device operations.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-04-15

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

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

Directory of Open Access Journals (Sweden)

Louis S. Matza

2017-11-01

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

Nanoscale chemical state analysis of resistance random access memory device reacting with Ti

Science.gov (United States)

Shima, Hisashi; Nakano, Takashi; Akinaga, Hiro

2010-05-01

The thermal stability of the resistance random access memory material in the reducing atmosphere at the elevated temperature was improved by the addition of Ti. The unipolar resistance switching before and after the postdeposition annealing (PDA) process at 400 °C was confirmed in Pt/CoO/Ti(5 nm)/Pt device, while the severe degradation of the initial resistance occurs in the Pt/CoO/Pt and Pt/CoO/Ti(50 nm)/Pt devices. By investigating the chemical bonding states of Co, O, and Ti using electron energy loss spectroscopy combined with transmission electron microscopy, it was revealed that excess Ti induces the formation of metallic Co, while the thermal stability was improved by trace Ti. Moreover, it was indicated that the filamentary conduction path can be thermally induced after PDA in the oxide layer by analyzing electrical properties of the degraded devices. The adjustment of the reducing elements is quite essential in order to participate in their profits.

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.

Guide to preemption of state-law claims against Class III PMA medical devices.

Science.gov (United States)

Whitney, Daniel W

2010-01-01

There is a perception that the express preemption holding of the Supreme Court in Riegel v. Medtronic, 552 U.S. 312(2008), immunizes medical device manufacturers from common law personal injury actions involving Class III devices that received FDA clearance under a premarket approval application (PMA). In the aftermath of Riegel, many lawsuits involving Class III PMA devices have been dismissed by district courts applying the new heightened pleading standard of Bell Atlantic Corp. v. Twombly, 550 U.S. 544 (2007). Other lawsuits involving Class III PMA devices premised on fraud-on-FDA have been dismissed based on the implied preemption holding of the Supreme Court in Buckman v. Plaintiffs' Legal Comm., 531 U.S. 341 (2001). When these decisions are carefully analyzed together with Medtronic, Inc. v. Lohr, 518 U.S. 470 (1996), which found no preemption regarding a Class III device receiving FDA clearance through the 510(k) mechanism, it is apparent that the preemption defense does not apply universally to Class III PMA devices. The overall methodology for framing a non-preempted claim is to first identify conduct which violated the PMA or other specific requirements related to safety or efficacy. If such conduct can also be stated in terms of a breach of a parallel common law duty (e.g, failure to warn under strict liability or negligence, manufacturing defect or breach of warranty), then it would appear the claim is not preempted. Alternatively, regardless of a specific violation, common law remedies are not preempted by general CGMP requirements.

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...

The influence of device position on the flow within the Penn State 12 cc pediatric ventricular assist device.

Science.gov (United States)

Schönberger, Markus; Deutsch, Steven; Manning, Keefe B

2012-01-01

Ventricular assist devices are a commonly used heart failure therapy for adult patients as bridge-to-transplant or bridge-to-recovery tools. The application of adult ventricular assist devices in pediatric patients has led to increased thrombotic events. Therefore, we have been developing a pediatric ventricular assist device (PVAD), the Penn State 12 cc PVAD. It is designed for patients with a body weight of 5-15 kg and has a stroke volume of 12 cc. Clot formation is the major concern. It is correlated to the coagulability of blood, the blood contacting materials and the fluid dynamics within the system. The intent is for the PVAD to be a long term therapy. Therefore, the system may be oriented in different positions according to the patient's behavior. This study evaluates for the first time the impact of position on the flow patterns within the Penn State 12 cc PVAD, which may help to improve the PVAD design concerning chamber and ports geometries. The fluid dynamics are visualized by particle image velocimetry. The evaluation is based on inlet jet behavior and calculated wall shear rates. Vertical and horizontal model orientations are compared, both with a beat rate of 75, outlet pressures of 90/60 mm Hg and a flow rate of 1.3 l/min. The results show a significant change of the inlet jet behavior and the development of a rotational flow pattern. Vertically, the inlet jet is strong along the wall. It initiates a rotational flow pattern with a wandering axis of rotation. In contrast, the horizontal model orientation results show a weaker inlet jet along the wall with a nearly constant center of rotation location, which can be correlated to a higher risk of thrombotic events. In addition, high speed videography illustrates differences in the diaphragm motion during diastole. Diaphragm opening trajectories measurements determine no significant impact of the density of the blood analog fluids. Hence, the results correlate to human blood.

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.

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

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.

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.

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)

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.

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.

Criticality alarm device

International Nuclear Information System (INIS)

Kasai, Kenji.

1994-01-01

The device of the present invention is utilized, for example, to a reprocessing facility for storing and processing nuclear fuels and measures and controls the nuclear fuel assembly system so as not to exceed criticality. That is, a conventional criticality alarm device applies a predetermined processing to neutron fluxes generated from a nuclear fuel assembly system containing nuclear fuels and outputs an alarm. The device of the present invention comprises (1) a neutron flux supply source for increasing and decreasing neutron fluxes periodically and supplying them to nuclear fuel assemblies, (2) a detector for detecting neutron fluxes in the nuclear fuel assemblies, (3) a critical state judging section for judging the critical state of the nuclear fuel assemblies based on the periodically changing signals obtained from the detector (2) and (4) an alarm section for outputting criticality alarms depending on the result of the judgement. The device of the present invention can accurately recognize the critical state of the nuclear fuel assembly system and can forecast reaching of the nuclear fuel assembly to criticality or prompt neutron critical state. (I.S.)

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).

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.

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.

Practical microwave electron devices

CERN Document Server

Meurant, Gerard

2013-01-01

Practical Microwave Electron Devices provides an understanding of microwave electron devices and their applications. All areas of microwave electron devices are covered. These include microwave solid-state devices, including popular microwave transistors and both passive and active diodes; quantum electron devices; thermionic devices (including relativistic thermionic devices); and ferrimagnetic electron devices. The design of each of these devices is discussed as well as their applications, including oscillation, amplification, switching, modulation, demodulation, and parametric interactions.

A Mixed WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

Directory of Open Access Journals (Sweden)

Tao Jin

2018-02-01

Full Text Available To address the issue that the phasor measurement units (PMUs of wide area measurement system (WAMS are not sufficient for static state estimation in most existing power systems, this paper proposes a mixed power system weighted least squares (WLS state estimation method integrating a wide-area measurement system and supervisory control and data acquisition (SCADA technology. The hybrid calculation model is established by incorporating phasor measurements (including the node voltage phasors and branch current phasors and the results of the traditional state estimator in a post-processing estimator. The performance assessment is discussed through setting up mathematical models of the distribution network. Based on PMU placement optimization and bias analysis, the effectiveness of the proposed method was proved to be accurate and reliable by simulations of different cases. Furthermore, emulating calculation shows this method greatly improves the accuracy and stability of the state estimation solution, compared with the traditional WLS state estimation.

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.

A conceptual design of the set-up for solid state spectroscopy with free electron laser and insertion device radiation

CERN Document Server

Makhov, V N

2001-01-01

The set-up for complex solid state spectroscopy with the use of enhanced properties of radiation from insertion devices and free electron lasers is proposed. Very high flux and pulsed properties of radiation from insertion devices and free electron lasers offer the possibility for the use of such powerful techniques as electron paramagnetic resonance (EPR) and optically detected magnetic resonance (ODMR) for the studies of excited states of electronic excitations or defects in solids. The power density of radiation can become high enough for one more method of exited-state spectroscopy: transient optical absorption spectroscopy. The set-up is supposed to combine the EPR/ODMR spectrometer, i.e. cryostat supplied with superconducting magnet and microwave system, and the optical channels for excitation (by radiation from insertion devices or free electron laser) and detection of luminescence (i.e. primary and secondary monochromators). The set-up can be used both for 'conventional' spectroscopy of solids (reflec...

Flow Visualization of Three-Dimensionality Inside the 12 cc Penn State Pulsatile Pediatric Ventricular Assist Device

OpenAIRE

Roszelle, Breigh N.; Deutsch, Steven; Manning, Keefe B.

2010-01-01

In order to aid the ongoing concern of limited organ availability for pediatric heart transplants, Penn State has continued development of a pulsatile Pediatric Ventricular Assist Device (PVAD). Initial studies of the PVAD observed an increase in thrombus formation due to differences in flow field physics when compared to adult sized devices, which included a higher degree of three-dimensionality. This unique flow field brings into question the use of 2D planar particle image velocimetry (PIV...

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

Science.gov (United States)

Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

Directory of Open Access Journals (Sweden)

Bin Ran

Full Text Available Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

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.

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.

Modeling and state-of-charge prediction of lithium-ion battery and ultracapacitor hybrids with a co-estimator

International Nuclear Information System (INIS)

Wang, Yujie; Liu, Chang; Pan, Rui; Chen, Zonghai

2017-01-01

The modeling and state-of-charge estimation of the batteries and ultracapacitors are crucial to the battery/ultracapacitor hybrid energy storage system. In recent years, the model based state estimators are welcomed widely, since they can adjust the gain according to the error between the model predictions and measurements timely. In most of the existing algorithms, the model parameters are either configured by theoretical values or identified off-line without adaption. But in fact, the model parameters always change continuously with loading wave or self-aging, and the lack of adaption will reduce the estimation accuracy significantly. To overcome this drawback, a novel co-estimator is proposed to estimate the model parameters and state-of-charge simultaneously. The extended Kalman filter is employed for parameter updating. To reduce the convergence time, the recursive least square algorithm and the off-line identification method are used to provide initial values with small deviation. The unscented Kalman filter is employed for the state-of-charge estimation. Because the unscented Kalman filter takes not only the measurement uncertainties but also the process uncertainties into account, it is robust to the noise. Experiments are executed to explore the robustness, stability and precision of the proposed method. - Highlights: • A co-estimator is proposed to estimate the model parameters and state-of-charge. • The extended Kalman filter is used for model parameter adaption. • The unscented Kalman filter is designed for state estimation with strong robust. • The dynamic profiles are employed to verify the proposed co-estimator.

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

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...

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.

Plasma control device

International Nuclear Information System (INIS)

Matsutomi, Akiyoshi.

1995-01-01

Plasma position and shape estimation values are outputted based on measured values of coil current. When the measured values of the position and the shape are judged to be abnormal, position and shape estimation values estimated by a plasma position and shape estimation means are outputted as position and shape feed back values to a plasma position and shape control means instead of the position and shape measured values. Since only a portion of the abnormal position and shape measured values may also be replaced with the position and shape estimation values, errors in the plasma position and shape feed back values can be reduced as a whole. In addition, even if the position and shape measured values are abnormal or if they can not be measured, plasma control can be continued by alternative position and shape estimation values, thereby enabling to avoid interruption of plasma control. Since the position and shape estimation values are obtained not only with the measured values of coil current but also with the position and shape estimation values, the accuracy is improved. Further, noises superposed on the position and shape measured values are filtered, and the device is stabilized compared with a prior art device. (N.H.)

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...

Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery

International Nuclear Information System (INIS)

Wei, Zhongbao; Lim, Tuti Mariana; Skyllas-Kazacos, Maria; Wai, Nyunt; Tseng, King Jet

2016-01-01

Highlights: • Battery model parameters and SOC co-estimation is investigated. • The model parameters and OCV are decoupled and estimated independently. • Multiple timescales are adopted to improve precision and stability. • SOC is online estimated without using the open-circuit cell. • The method is robust to aging levels, flow rates, and battery chemistries. - Abstract: A key function of battery management system (BMS) is to provide accurate information of the state of charge (SOC) in real time, and this depends directly on the precise model parameterization. In this paper, a novel multi-timescale estimator is proposed to estimate the model parameters and SOC for vanadium redox flow battery (VRB) in real time. The model parameters and OCV are decoupled and estimated independently, effectively avoiding the possibility of cross interference between them. The analysis of model sensitivity, stability, and precision suggests the necessity of adopting different timescales for each estimator independently. Experiments are conducted to assess the performance of the proposed method. Results reveal that the model parameters are online adapted accurately thus the periodical calibration on them can be avoided. The online estimated terminal voltage and SOC are both benchmarked with the reference values. The proposed multi-timescale estimator has the merits of fast convergence, high precision, and good robustness against the initialization uncertainty, aging states, flow rates, and also battery chemistries.

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....

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

Progress on Broadband Access to the Internet and Use of Mobile Devices in the United States.

Science.gov (United States)

Serrano, Katrina J; Thai, Chan L; Greenberg, Alexandra J; Blake, Kelly D; Moser, Richard P; Hesse, Bradford W

Healthy People 2020 (HP2020) aims to improve population health outcomes through several objectives, including health communication and health information technology. We used 7 administrations of the Health Information National Trends Survey to examine HP2020 goals toward access to the Internet through broadband and mobile devices (N = 34 080). We conducted descriptive analyses and obtained predicted marginals, also known as model-adjusted risks, to estimate the association between demographic characteristics and use of mobile devices. The HP2020 target (7.7% of the US population) for accessing the Internet through a cellular network was surpassed in 2014 (59.7%), but the HP2020 target (83.2%) for broadband access fell short (63.8%). Sex and age were associated with accessing the Internet through a cellular network throughout the years (Wald F test, P Internet through mobile devices presents an opportunity for technology-based health interventions that should be explored.

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.

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)

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.

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

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

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

Optimal allocation of sensors for state estimation of distributed parameter systems

International Nuclear Information System (INIS)

Sunahara, Yoshifumi; Ohsumi, Akira; Mogami, Yoshio.

1978-01-01

The purpose of this paper is to present a method for finding the optimal allocation of sensors for state estimation of linear distributed parameter systems. This method is based on the criterion that the error covariance associated with the state estimate becomes minimal with respect to the allocation of the sensors. A theorem is established, giving the sufficient condition for optimizing the allocation of sensors to make minimal the error covariance approximated by a modal expansion. The remainder of this paper is devoted to illustrate important phases of the general theory of the optimal measurement allocation problem. To do this, several examples are demonstrated, including extensive discussions on the mutual relation between the optimal allocation and the dynamics of sensors. (author)

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...

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.

A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

Directory of Open Access Journals (Sweden)

Tao Jin

2015-04-01

Full Text Available With the development of modern society, the scale of the power system is rapidly increased accordingly, and the framework and mode of running of power systems are trending towards more complexity. It is nowadays much more important for the dispatchers to know exactly the state parameters of the power network through state estimation. This paper proposes a robust power system WLS state estimation method integrating a wide-area measurement system (WAMS and SCADA technology, incorporating phasor measurements and the results of the traditional state estimator in a post-processing estimator, which greatly reduces the scale of the non-linear estimation problem as well as the number of iterations and the processing time per iteration. This paper firstly analyzes the wide-area state estimation model in detail, then according to the issue that least squares does not account for bad data and outliers, the paper proposes a robust weighted least squares (WLS method that combines a robust estimation principle with least squares by equivalent weight. The performance assessment is discussed through setting up mathematical models of the distribution network. The effectiveness of the proposed method was proved to be accurate and reliable by simulations and experiments.

Preliminary design study of a steady state tokamak device

International Nuclear Information System (INIS)

Miya, Naoyuki; Nakajima, Shinji; Ushigusa, Kenkichi; and athors)

1992-09-01

Preliminary design study has been made for a steady tokamak with the plasma current of 10MA, as the next to the JT-60U experimental programs. The goal of the research program is the integrated study of steady state, high-power physics and technology. Present candidate design is to use superconducting TF and PF magnet systems and long pulse operation of 100's-1000's of sec with non inductive current drive mainly by 500keV negative ion beam injection of 60MW. Low activation material such as titanium alloy is chosen for the water tank type vacuum vessel, which is also the nuclear shield for the superconducting coils. The present preliminary design study shows that the device can meet the existing JT-60U facility capability. (author)

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...

Estimating PM2.5-associated mortality increase in California due to the Volkswagen emission control defeat device

Science.gov (United States)

Wang, Tianyang; Jerrett, Michael; Sinsheimer, Peter; Zhu, Yifang

2016-11-01

The Volkswagen Group of America (VW) was found by the US Environmental Protection Agency (EPA) and the California Air Resources Board (CARB) to have installed "defeat devices" and emit more oxides of nitrogen (NOx) than permitted under current EPA standards. In this paper, we quantify the hidden NOx emissions from this so-called VW scandal and the resulting public health impacts in California. The NOx emissions are calculated based on VW road test data and the CARB Emission Factors (EMFAC) model. Cumulative hidden NOx emissions from 2009 to 2015 were estimated to be over 3500 tons. Adult mortality changes were estimated based on ambient fine particulate matter (PM2.5) change due to secondary nitrate formation and the related concentration-response functions. We estimated that hidden NOx emissions from 2009 to 2015 have resulted in a total of 12 PM2.5-associated adult mortality increases in California. Most of the mortality increase happened in metropolitan areas, due to their high population and vehicle density.

Device-independent characterizations of a shared quantum state independent of any Bell inequalities

Science.gov (United States)

Wei, Zhaohui; Sikora, Jamie

2017-03-01

In a Bell experiment two parties share a quantum state and perform local measurements on their subsystems separately, and the statistics of the measurement outcomes are recorded as a Bell correlation. For any Bell correlation, it turns out that a quantum state with minimal size that is able to produce this correlation can always be pure. In this work, we first exhibit two device-independent characterizations for the pure state that Alice and Bob share using only the correlation data. Specifically, we give two conditions that the Schmidt coefficients must satisfy, which can be tight, and have various applications in quantum tasks. First, one of the characterizations allows us to bound the entanglement between Alice and Bob using Renyi entropies and also to bound the underlying Hilbert space dimension. Second, when the Hilbert space dimension bound is tight, the shared pure quantum state has to be maximally entangled. Third, the second characterization gives a sufficient condition that a Bell correlation cannot be generated by particular quantum states. We also show that our results can be generalized to the case of shared mixed states.

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

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

Full State Feedback Control for Virtual Power Plants

Energy Technology Data Exchange (ETDEWEB)

Johnson, Jay Tillay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

This report presents an object-oriented implementation of full state feedback control for virtual power plants (VPP). The components of the VPP full state feedback control are (1) objectoriented high-fidelity modeling for all devices in the VPP; (2) Distribution System Distributed Quasi-Dynamic State Estimation (DS-DQSE) that enables full observability of the VPP by augmenting actual measurements with virtual, derived and pseudo measurements and performing the Quasi-Dynamic State Estimation (QSE) in a distributed manner, and (3) automated formulation of the Optimal Power Flow (OPF) in real time using the output of the DS-DQSE, and solving the distributed OPF to provide the optimal control commands to the DERs of the VPP.

Battery Management Systems: Accurate State-of-Charge Indication for Battery-Powered Applications

NARCIS (Netherlands)

Pop, V.; Bergveld, H.J.; Danilov, D.; Regtien, Paulus P.L.; Notten, P.H.L.

2008-01-01

Battery Management Systems – Universal State-of-Charge indication for portable applications describes the field of State-of-Charge (SoC) indication for rechargeable batteries. With the emergence of battery-powered devices with an increasing number of power-hungry features, accurately estimating the

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.

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.

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

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...

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

The improvement of all-solid-state electrochromic devices fabricated with the reactive sputter and cathodic arc technology

Directory of Open Access Journals (Sweden)

Min-Chuan Wang

2016-11-01

Full Text Available The all-solid-state electrochromic device (ECD with the one substrate structure fabricated by the reactive dc magnetron sputtering (DCMS and cathodic vacuum arc plasma (CVAP technology has been developed for smart electrochromic (EC glass application. The EC layer and ion conductor layer were deposited by reactive DCMS and CVAP technology, respectively. The ion conductor layer Ta2O5 deposited by the CVAP technology has provided the better porous material structure for ion transportation and showed 1.76 times ion conductivity than devices with all sputtering process. At the same time, the EC layer WO3 and NiO deposited by the reactive DCMS have also provided the high quality and uniform characteristic to overcome the surface roughness effect of the CVAP ion conductor layer in multilayer device structure. The all-solid-state ECD with the CVAP ion conductor layer has demonstrated a maximum transmittance variation (ΔT of 55% at 550nm and a faster-switching speed. Furthermore, the lower equipment cost and higher deposition rate could be achieved by the application of CVAP technology.

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

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.

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.

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...

76 FR 45860 - In the Matter of Certain Electronic Devices, Including Wireless Communication Devices, Portable...

Science.gov (United States)

2011-08-01

..., Including Wireless Communication Devices, Portable Music and Data Processing Devices, and Tablet Computers... electronic devices, including wireless communication devices, portable music and data processing devices, and...''). The complaint further alleges that an industry in the United States exists or is in the process of...

CURRENT STATE ANALYSIS OF AUTOMATIC BLOCK SYSTEM DEVICES, METHODS OF ITS SERVICE AND MONITORING

Directory of Open Access Journals (Sweden)

A. M. Beznarytnyy

2014-01-01

Full Text Available Purpose. Development of formalized description of automatic block system of numerical code based on the analysis of characteristic failures of automatic block system and procedure of its maintenance. Methodology. For this research a theoretical and analytical methods have been used. Findings. Typical failures of the automatic block systems were analyzed, as well as basic reasons of failure occur were found out. It was determined that majority of failures occurs due to defects of the maintenance system. Advantages and disadvantages of the current service technology of automatic block system were analyzed. Works that can be automatized by means of technical diagnostics were found out. Formal description of the numerical code of automatic block system as a graph in the state space of the system was carried out. Originality. The state graph of the numerical code of automatic block system that takes into account gradual transition from the serviceable condition to the loss of efficiency was offered. That allows selecting diagnostic information according to attributes and increasing the effectiveness of recovery operations in the case of a malfunction. Practical value. The obtained results of analysis and proposed the state graph can be used as the basis for the development of new means of diagnosing devices for automatic block system, which in turn will improve the efficiency and service of automatic block system devices in general.

Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network.

Science.gov (United States)

Mu, Wenying; Cui, Baotong; Li, Wen; Jiang, Zhengxian

2014-07-01

This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator-sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

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

A Performance Comparison Between Extended Kalman Filter and Unscented Kalman Filter in Power System Dynamic State Estimation

DEFF Research Database (Denmark)

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

2016-01-01

Dynamic State Estimation (DSE) is a critical tool for analysis, monitoring and planning of a power system. The concept of DSE involves designing state estimation with Extended Kalman Filter (EKF) or Unscented Kalman Filter (UKF) methods, which can be used by wide area monitoring to improve......-linear state estimator is developed in MatLab to solve states by applying the unscented Kalman filter (UKF) and Extended Kalman Filter (EKF) algorithm. Finally, a DSE model is built for a 14 bus power system network to evaluate the proposed algorithm for the networks.This article will focus on comparing...

Porous Organic Nanolayers for Coating of Solid-state Devices

Science.gov (United States)

2011-01-01

Background Highly hydrophobic surfaces can have very low surface energy and such low surface energy biological interfaces can be obtained using fluorinated coatings on surfaces. Deposition of biocompatible organic films on solid-state surfaces is attained with techniques like plasma polymerization, biomineralization and chemical vapor deposition. All these require special equipment or harsh chemicals. This paper presents a simple vapor-phase approach to directly coat solid-state surfaces with biocompatible films without any harsh chemical or plasma treatment. Hydrophilic and hydrophobic monomers were used for reaction and deposition of nanolayer films. The monomers were characterized and showed a very consistent coating of 3D micropore structures. Results The coating showed nano-textured surface morphology which can aid cell growth and provide rich molecular functionalization. The surface properties of the obtained film were regulated by varying monomer concentrations, reaction time and the vacuum pressure in a simple reaction chamber. Films were characterized by contact angle analysis for surface energy and with profilometer to measure the thickness. Fourier Transform Infrared Spectroscopy (FTIR) analysis revealed the chemical composition of the coated films. Variations in the FTIR results with respect to different concentrations of monomers showed the chemical composition of the resulting films. Conclusion The presented approach of vapor-phase coating of solid-state structures is important and applicable in many areas of bio-nano interface development. The exposure of coatings to the solutions of different pH showed the stability of the coatings in chemical surroundings. The organic nanocoating of films can be used in bio-implants and many medical devices. PMID:21569579

Porous Organic Nanolayers for Coating of Solid-state Devices

Directory of Open Access Journals (Sweden)

Asghar Waseem

2011-05-01

Full Text Available Abstract Background Highly hydrophobic surfaces can have very low surface energy and such low surface energy biological interfaces can be obtained using fluorinated coatings on surfaces. Deposition of biocompatible organic films on solid-state surfaces is attained with techniques like plasma polymerization, biomineralization and chemical vapor deposition. All these require special equipment or harsh chemicals. This paper presents a simple vapor-phase approach to directly coat solid-state surfaces with biocompatible films without any harsh chemical or plasma treatment. Hydrophilic and hydrophobic monomers were used for reaction and deposition of nanolayer films. The monomers were characterized and showed a very consistent coating of 3D micropore structures. Results The coating showed nano-textured surface morphology which can aid cell growth and provide rich molecular functionalization. The surface properties of the obtained film were regulated by varying monomer concentrations, reaction time and the vacuum pressure in a simple reaction chamber. Films were characterized by contact angle analysis for surface energy and with profilometer to measure the thickness. Fourier Transform Infrared Spectroscopy (FTIR analysis revealed the chemical composition of the coated films. Variations in the FTIR results with respect to different concentrations of monomers showed the chemical composition of the resulting films. Conclusion The presented approach of vapor-phase coating of solid-state structures is important and applicable in many areas of bio-nano interface development. The exposure of coatings to the solutions of different pH showed the stability of the coatings in chemical surroundings. The organic nanocoating of films can be used in bio-implants and many medical devices.

77 FR 58576 - Certain Wireless Communication Devices, Portable Music and Data Processing Devices, Computers...

Science.gov (United States)

2012-09-21

... Devices, Portable Music and Data Processing Devices, Computers, and Components Thereof; Institution of... communication devices, portable music and data processing devices, computers, and components thereof by reason... alleges that an industry in the United States exists as required by subsection (a)(2) of section 337. The...

Quantum process estimation via generic two-body correlations

International Nuclear Information System (INIS)

Mohseni, M.; Rezakhani, A. T.; Barreiro, J. T.; Kwiat, P. G.; Aspuru-Guzik, A.

2010-01-01

Performance of quantum process estimation is naturally limited by fundamental, random, and systematic imperfections of preparations and measurements. These imperfections may lead to considerable errors in the process reconstruction because standard data-analysis techniques usually presume ideal devices. Here, by utilizing generic auxiliary quantum or classical correlations, we provide a framework for the estimation of quantum dynamics via a single measurement apparatus. By construction, this approach can be applied to quantum tomography schemes with calibrated faulty-state generators and analyzers. Specifically, we present a generalization of the work begun by M. Mohseni and D. A. Lidar [Phys. Rev. Lett. 97, 170501 (2006)] with an imperfect Bell-state analyzer. We demonstrate that for several physically relevant noisy preparations and measurements, classical correlations and a small data-processing overhead suffice to accomplish the full system identification. Furthermore, we provide the optimal input states whereby the error amplification due to inversion of the measurement data is minimal.

Rapid cable tension estimation using dynamic and mechanical properties

Science.gov (United States)

Martínez-Castro, Rosana E.; Jang, Shinae; Christenson, Richard E.

2016-04-01

Main tension elements are critical to the overall stability of cable-supported bridges. A dependable and rapid determination of cable tension is desired to assess the state of a cable-supported bridge and evaluate its operability. A portable smart sensor setup is presented to reduce post-processing time and deployment complexity while reliably determining cable tension using dynamic characteristics extracted from spectral analysis. A self-recording accelerometer is coupled with a single-board microcomputer that communicates wirelessly with a remote host computer. The portable smart sensing device is designed such that additional algorithms, sensors and controlling devices for various monitoring applications can be installed and operated for additional structural assessment. The tension-estimating algorithms are based on taut string theory and expand to consider bending stiffness. The successful combination of cable properties allows the use of a cable's dynamic behavior to determine tension force. The tension-estimating algorithms are experimentally validated on a through-arch steel bridge subject to ambient vibration induced by passing traffic. The tension estimation is determined in well agreement with previously determined tension values for the structure.

Deep energetic trap states in organic photovoltaic devices

KAUST Repository

Shuttle, Christopher G.; Treat, Neil D.; Douglas, Jessica D.; Frechet, Jean; Chabinyc, Michael L.

2011-01-01

The nature of energetic disorder in organic semiconductors is poorly understood. In photovoltaics, energetic disorder leads to reductions in the open circuit voltage and contributes to other loss processes. In this work, three independent optoelectronic methods were used to determine the long-lived carrier populations in a high efficiency N-alkylthieno[3,4-c]pyrrole-4,6-dione (TPD) based polymer: fullerene solar cell. In the TPD co-polymer, all methods indicate the presence of a long-lived carrier population of ∼ 10 15 cm -3 on timescales ≤100 μs. Additionally, the behavior of these photovoltaic devices under optical bias is consistent with deep energetic lying trap states. Comparative measurements were also performed on high efficiency poly-3-hexylthiophene (P3HT): fullerene solar cells; however a similar long-lived carrier population was not observed. This observation is consistent with a higher acceptor concentration (doping) in P3HT than in the TPD-based copolymer. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep energetic trap states in organic photovoltaic devices

KAUST Repository

Shuttle, Christopher G.

2011-11-23

The nature of energetic disorder in organic semiconductors is poorly understood. In photovoltaics, energetic disorder leads to reductions in the open circuit voltage and contributes to other loss processes. In this work, three independent optoelectronic methods were used to determine the long-lived carrier populations in a high efficiency N-alkylthieno[3,4-c]pyrrole-4,6-dione (TPD) based polymer: fullerene solar cell. In the TPD co-polymer, all methods indicate the presence of a long-lived carrier population of ∼ 10 15 cm -3 on timescales ≤100 μs. Additionally, the behavior of these photovoltaic devices under optical bias is consistent with deep energetic lying trap states. Comparative measurements were also performed on high efficiency poly-3-hexylthiophene (P3HT): fullerene solar cells; however a similar long-lived carrier population was not observed. This observation is consistent with a higher acceptor concentration (doping) in P3HT than in the TPD-based copolymer. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India-An application of small area estimation techniques.

Science.gov (United States)

Chandra, Hukum; Aditya, Kaustav; Sud, U C

2018-01-01

Poverty affects many people, but the ramifications and impacts affect all aspects of society. Information about the incidence of poverty is therefore an important parameter of the population for policy analysis and decision making. In order to provide specific, targeted solutions when addressing poverty disadvantage small area statistics are needed. Surveys are typically designed and planned to produce reliable estimates of population characteristics of interest mainly at higher geographic area such as national and state level. Sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. In many instances estimates are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct survey estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This paper describes an application of small area estimation (SAE) approach to improve the precision of estimates of poverty incidence at district level in the State of Bihar in India by linking data from the Household Consumer Expenditure Survey 2011-12 of NSSO and the Population Census 2011. The results show that the district level estimates generated by SAE method are more precise and representative. In contrast, the direct survey estimates based on survey data alone are less stable.

Localised estimates and spatial mapping of poverty incidence in the state of Bihar in India—An application of small area estimation techniques

Science.gov (United States)

Aditya, Kaustav; Sud, U. C.

2018-01-01

Poverty affects many people, but the ramifications and impacts affect all aspects of society. Information about the incidence of poverty is therefore an important parameter of the population for policy analysis and decision making. In order to provide specific, targeted solutions when addressing poverty disadvantage small area statistics are needed. Surveys are typically designed and planned to produce reliable estimates of population characteristics of interest mainly at higher geographic area such as national and state level. Sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. In many instances estimates are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct survey estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This paper describes an application of small area estimation (SAE) approach to improve the precision of estimates of poverty incidence at district level in the State of Bihar in India by linking data from the Household Consumer Expenditure Survey 2011–12 of NSSO and the Population Census 2011. The results show that the district level estimates generated by SAE method are more precise and representative. In contrast, the direct survey estimates based on survey data alone are less stable. PMID:29879202

Virtual MIMO Beamforming and Device Pairing Enabled by Device-to-Device Communications for Multidevice Networks

Directory of Open Access Journals (Sweden)

Yeonjin Jeong

2017-01-01

Full Text Available We consider a multidevice network with asymmetric antenna configurations which supports not only communications between an access point and devices but also device-to-device (D2D communications for the Internet of things. For the network, we propose the transmit and receive beamforming with the channel state information (CSI for virtual multiple-input multiple-output (MIMO enabled by D2D receive cooperation. We analyze the sum rate achieved by a device pair in the proposed method and identify the strategies to improve the sum rate of the device pair. We next present a distributed algorithm and its equivalent algorithm for device pairing to maximize the throughput of the multidevice network. Simulation results confirm the advantages of the transmit CSI and D2D cooperation as well as the validity of the distributive algorithm.

Towards room temperature solid state quantum devices at the edge of quantum chaos for long-living quantum states

International Nuclear Information System (INIS)

Prati, Enrico

2015-01-01

Long living coherent quantum states have been observed in biological systems up to room temperature. Light harvesting in chromophoresis realized by excitonic systems living at the edge of quantum chaos, where energy level distribution becomes semi-Poissonian. On the other hand, artificial materials suffer the loss of coherence of quantum states in quantum information processing, but semiconductor materials are known to exhibit quantum chaotic conditions, so the exploitation of similar conditions are to be considered. The advancements of nanofabrication, together with the control of implantation of individual atoms at nanometric precision, may open the experimental study of such special regime at the edge of the phase transitions for the electronic systems obtained by implanting impurity atoms in a silicon transistor. Here I review the recent advancements made in the field of theoretical description of the light harvesting in biological system in its connection with phase transitions at the few atoms scale and how it would be possible to achieve transition point to quantum chaotic regime. Such mechanism may thus preserve quantum coherent states at room temperature in solid state devices, to be exploited for quantum information processing as well as dissipation-free quantum electronics. (paper)

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....

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

Solar Irradiance Measurements Using Smart Devices: A Cost-Effective Technique for Estimation of Solar Irradiance for Sustainable Energy Systems

Directory of Open Access Journals (Sweden)

Hussein Al-Taani

2018-02-01

Full Text Available Solar irradiance measurement is a key component in estimating solar irradiation, which is necessary and essential to design sustainable energy systems such as photovoltaic (PV systems. The measurement is typically done with sophisticated devices designed for this purpose. In this paper we propose a smartphone-aided setup to estimate the solar irradiance in a certain location. The setup is accessible, easy to use and cost-effective. The method we propose does not have the accuracy of an irradiance meter of high precision but has the advantage of being readily accessible on any smartphone. It could serve as a quick tool to estimate irradiance measurements in the preliminary stages of PV systems design. Furthermore, it could act as a cost-effective educational tool in sustainable energy courses where understanding solar radiation variations is an important aspect.

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

Science.gov (United States)

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

2016-01-01

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

ICRF heating on helical devices

International Nuclear Information System (INIS)

Rasmussen, D.A.; Lyon, J.F.; Hoffman, D.J.; Murakami, M.; England, A.C.; Wilgen, J.B.; Jaeger, E.F.; Wang, C.; Batchelor, D.B.

1995-01-01

Ion cyclotron range of frequency (ICRF) heating is currently in use on CHS and W7-AS and is a major element of the heating planned for steady state helical devices. In helical devices, the lack of a toroidal current eliminates both disruptions and the need for ICRF current drive, simplifying the design of antenna structures as compared to tokamak applications. However the survivability of plasma facing components and steady state cooling issues are directly applicable to tokamak devices. Results from LHD steady state experiments should be available on a time scale to strongly influence the next generation of steady state tokamak experiments. The helical plasma geometry provides challenges not faced with tokamak ICRF heating, including the potential for enhanced fast ion losses, impurity accumulation, limited access for antenna structures, and open magnetic field lines in the plasma edge. The present results and near term plans provide the basis for steady state ICRF heating of larger helical devices. An approach which includes direct electron, mode conversion, ion minority and ion Bernstein wave heating addresses these issues

ICRF heating on helical devices

International Nuclear Information System (INIS)

Rasmussen, D.A.; Lyon, J.F.; Hoffman, D.J.

1995-01-01

Ion cyclotron range of frequency (ICRF) heating is currently in use on CHS and W7AS and is a major element of the heating planned for steady state helical devices. In helical devices, the lack of a toroidal current eliminates both disruptions and the need for ICRF current drive, simplifying the design of antenna structures as compared to tokamak applications. However the survivability of plasma facing components and steady state cooling issues are directly applicable to tokamak devices. Results from LHD steady state experiments should be available on a time scale to strongly influence the next generation of steady state tokamak experiments. The helical plasma geometry provides challenges not faced with tokamak ICRF heating, including the potential for enhanced fast ion losses, impurity accumulation, limited access for antenna structures, and open magnetic field lines in the plasma edge. The present results and near term plans provide the basis for steady state ICRF heating of larger helical devices. An approach which includes direct electron, mode conversion, ion minority and ion Bernstein wave heating addresses these issues

Analysis of field usage failure rate data for plastic encapsulated solid state devices

Science.gov (United States)

1981-01-01

Survey and questionnaire techniques were used to gather data from users and manufacturers on the failure rates in the field of plastic encapsulated semiconductors. It was found that such solid state devices are being successfully used by commercial companies which impose certain screening and qualification procedures. The reliability of these semiconductors is now adequate to support their consideration in NASA systems, particularly in low cost systems. The cost of performing necessary screening for NASA applications was assessed.

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 ...

Electronic processes in organic electronics bridging nanostructure, electronic states and device properties

CERN Document Server

Kudo, Kazuhiro; Nakayama, Takashi; Ueno, Nobuo

2015-01-01

The book covers a variety of studies of organic semiconductors, from fundamental electronic states to device applications, including theoretical studies. Furthermore, innovative experimental techniques, e.g., ultrahigh sensitivity photoelectron spectroscopy, photoelectron yield spectroscopy, spin-resolved scanning tunneling microscopy (STM), and a material processing method with optical-vortex and polarization-vortex lasers, are introduced. As this book is intended to serve as a textbook for a graduate level course or as reference material for researchers in organic electronics and nanoscience from electronic states, fundamental science that is necessary to understand the research is described. It does not duplicate the books already written on organic electronics, but focuses mainly on electronic properties that arise from the nature of organic semiconductors (molecular solids). The new experimental methods introduced in this book are applicable to various materials (e.g., metals, inorganic and organic mater...

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

Smartphone-Based Bioelectrical Impedance Analysis Devices for Daily Obesity Management

Directory of Open Access Journals (Sweden)

Ahyoung Choi

2015-09-01

Full Text Available Current bioelectric impedance analysis (BIA systems are often large, cumbersome devices which require strict electrode placement on the user, thus inhibiting mobile capabilities. In this work, we developed a handheld BIA device that measures impedance from multiple frequencies (5 kHz~200 kHz with four contact electrodes and evaluated the BIA device against standard body composition analysis systems: a dual-energy X-ray absorptiometry (DXA system (GE Lunar Prodigy, GE Healthcare, Buckinghamshire, UK and a whole-body BIA system (InBody S10, InBody, Co. Ltd, Seoul, Korea. In the study, 568 healthy participants, varying widely in body mass index, age, and gender, were recruited at two research centers: the Samsung Medical Center (SMC in South Korea and the Pennington Biomedical Research Center (PBRC in the United States. From the measured impedance data, we analyzed individual body fat and skeletal muscle mass by applying linear regression analysis against target reference data. Results indicated strong correlations of impedance measurements between the prototype pathways and corresponding InBody S10 electrical pathways (R = 0.93, p < 0.0001. Additionally, body fat estimates from DXA did not yield significant differences (p > 0.728 (paired t-test, DXA mean body fat 29.45 ± 10.77 kg, estimated body fat 29.52 ± 12.53 kg. Thus, this portable BIA system shows a promising ability to estimate an individual’s body composition that is comparable to large stationary BIA systems.

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.

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.

Solid-State Electrochromic Device Consisting of Amorphous WO3 and Various Thin Oxide Layers

Science.gov (United States)

Shizukuishi, Makoto; Shimizu, Isamu; Inoue, Eiichi

1980-11-01

A mixed oxide containing Cr2O3 was introduced into an amorphous WO3 solid-state electrochromic device (ECD) in order to improve its colour memory effect. The electrochromic characteristics were greatly affected by the chemical constituents of a dielectric layer on the a-WO3 layer. Particularly, long memory effect and low power dissipation were attained in a solid-state ECD consisting of a-WO3 and Cr2O3\\cdotV2O5(50 wt.%). Some electrochromic characteristics of the a-WO3/Cr2O3\\cdotV2O5 ECD and the role of V2O5 were investigated.

Students' Beliefs about Mobile Devices vs. Desktop Computers in South Korea and the United States

Science.gov (United States)

Sung, Eunmo; Mayer, Richard E.

2012-01-01

College students in the United States and in South Korea completed a 28-item multidimensional scaling (MDS) questionnaire in which they rated the similarity of 28 pairs of multimedia learning materials on a 10-point scale (e.g., narrated animation on a mobile device Vs. movie clip on a desktop computer) and a 56-item semantic differential…

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.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

Directory of Open Access Journals (Sweden)

Xiaoxue Feng

2014-11-01

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

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2014-11-10

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

Estimation of scattering contribution in the calibration of neutron devices with radionuclide sources in rooms of different sizes

Directory of Open Access Journals (Sweden)

Khabaz Rahim

2015-01-01

Full Text Available Calibrations of neutron devices used in area monitoring are often performed by radionuclide neutron sources. Device readings increase due to neutrons scattered by the surroundings and the air. The influence of said scattering effects have been investigated in this paper by performing Monte Carlo simulations for ten different radionuclide neutron sources inside several sizes of concrete wall spherical rooms (Rsp = 200 to 1500 cm. In order to obtain the parameters that relate the additional contribution from scattered neutrons, calculations using a polynomial fit model were evaluated. Obtained results show that the contribution of scattering is roughly independent of the geometric shape of the calibration room. The parameter that relates the room-return scattering has been fitted in terms of the spherical room radius, so as to reasonably accurately estimate the scattering value for each radionuclide neutron source in any geometry of the calibration room.

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.

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.

State-of-the-art implantable cardiac assist device therapy for heart failure: bridge to transplant and destination therapy.

Science.gov (United States)

Park, S J; Kushwaha, S S; McGregor, C G A

2012-01-01

Congestive heart failure is associated with poor quality of life (QoL) and low survival rates. The development of state-of-the-art cardiac devices holds promise for improved therapy in patients with heart failure. The field of implantable cardiac assist devices is changing rapidly with the emergence of continuous-flow pumps (CFPs). The important developments in this field, including pertinent clinical trials, registry reports, innovative research, and potential future directions are discussed in this paper.

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 (...

Recoil transporter devices

International Nuclear Information System (INIS)

Madhavan, N.

2005-01-01

The study of sparsely produced nuclear reaction products in the direction of intense primary beam is a challenging task, the pursuit of which has given rise to the advent or several types of selective devices. These range from a simple parallel plate electrostatic deflector to state-of-the-art electromagnetic separators. There is no single device which can satisfy all the requirements of an ideal recoil transporter, simultaneously. An overview of such devices and their building blocks is presented, which may help in the proper choice of the device as per the experimental requirements. (author)

Charge transport through image charged stabilized states in a single molecule single electron transistor device

International Nuclear Information System (INIS)

Hedegard, Per; Bjornholm, Thomas

2005-01-01

The present paper gives an elaborate theoretical description of a new molecular charge transport mechanism applying to a single molecule trapped between two macroscopic electrodes in a solid state device. It is shown by a Hubbard type model of the electronic and electrostatic interactions, that the close proximity of metal electrodes may allow electrons to tunnel from the electrode directly into very localized image charge stabilized states on the molecule. Due to this mechanism, an exceptionally large number of redox states may be visited within an energy scale which would normally not allow the molecular HOMO-LUMO gap to be transversed. With a reasonable set of parameters, a good fit to recent experimental values may be obtained. The theoretical model is furthermore used to search for the physical boundaries of this effect, and it is found that a rather narrow geometrical space is available for the new mechanism to work: in the specific case of oligophenylenevinylene molecules recently explored in such devices several atoms in the terminal benzene rings need to be at van der Waal's distance to the electrode in order for the mechanism to work. The model predicts, that chemisorption of the terminal benzene rings too gold electrodes will impede the image charge effect very significantly because the molecule is pushed away from the electrode by the covalent thiol-gold bond

Adaptive estimation of state of charge and capacity with online identified battery model for vanadium redox flow battery

Science.gov (United States)

Wei, Zhongbao; Tseng, King Jet; Wai, Nyunt; Lim, Tuti Mariana; Skyllas-Kazacos, Maria

2016-11-01

Reliable state estimate depends largely on an accurate battery model. However, the parameters of battery model are time varying with operating condition variation and battery aging. The existing co-estimation methods address the model uncertainty by integrating the online model identification with state estimate and have shown improved accuracy. However, the cross interference may arise from the integrated framework to compromise numerical stability and accuracy. Thus this paper proposes the decoupling of model identification and state estimate to eliminate the possibility of cross interference. The model parameters are online adapted with the recursive least squares (RLS) method, based on which a novel joint estimator based on extended Kalman Filter (EKF) is formulated to estimate the state of charge (SOC) and capacity concurrently. The proposed joint estimator effectively compresses the filter order which leads to substantial improvement in the computational efficiency and numerical stability. Lab scale experiment on vanadium redox flow battery shows that the proposed method is highly authentic with good robustness to varying operating conditions and battery aging. The proposed method is further compared with some existing methods and shown to be superior in terms of accuracy, convergence speed, and computational cost.

Effect of single walled carbon nanotubes on the threshold voltage of dye based photovoltaic devices

International Nuclear Information System (INIS)

Chakraborty, S.; Manik, N.B.

2016-01-01

Carbon nanotubes are being widely used in organic photovoltaic (OPV) devices as their usage has been reported to enhance the device efficiency along with other related parameters. In this work we have studied the energy (E_c) effect of single walled carbon nanotubes (SWCNT) on the threshold voltage (V_t_h) and also on the trap states of dye based photovoltaic devices. SWCNT is added in a series of dyes such as Rose Bengal (RB), Methyl Red (MR), Malachite Green (MG) and Crystal Violet (CV). By analysing the steady state dark current–voltage (I–V) characteristics V_t_h and E_c is estimated for the different devices with and without addition of SWCNT. It is observed that on an average for all the dyes V_t_h is reduced by about 30% in presence of SWCNT. The trap energy E_c also reduces in case of all the dyes. The relation between V_t_h, E_c and total trap density is discussed. From the photovoltaic measurements it is seen that the different photovoltaic parameters change with addition of SWCNT to the dye based devices. Both the short circuit current density and fill factor are found to increase for all the dye based devices in presence of SWCNT.

Reactor core performance calculating device

International Nuclear Information System (INIS)

Tominaga, Kenji; Bando, Masaru; Sano, Hiroki; Maruyama, Hiromi.

1995-01-01

The device of the present invention can calculate a power distribution efficiently at high speed by a plurality of calculation means while taking an amount of the reactor state into consideration. Namely, an input device takes data from a measuring device for the amount of the reactor core state such as a large number of neutron detectors disposed in the reactor core for monitoring the reactor state during operation. An input data distribution device comprises a state recognition section and a data distribution section. The state recognition section recognizes the kind and amount of the inputted data and information of the calculation means. The data distribution section analyzes the characteristic of the inputted data, divides them into a several groups, allocates them to each of the calculation means for the purpose of calculating the reactor core performance efficiently at high speed based on the information from the state recognition section. A plurality of the calculation means calculate power distribution of each of regions based on the allocated inputted data, to determine the power distribution of the entire reactor core. As a result, the reactor core can be evaluated at high accuracy and at high speed irrespective of the whole reactor core or partial region. (I.S.)

One-sided measurement-device-independent quantum key distribution

Science.gov (United States)

Cao, Wen-Fei; Zhen, Yi-Zheng; Zheng, Yu-Lin; Li, Li; Chen, Zeng-Bing; Liu, Nai-Le; Chen, Kai

2018-01-01

Measurement-device-independent quantum key distribution (MDI-QKD) protocol was proposed to remove all the detector side channel attacks, while its security relies on the trusted encoding systems. Here we propose a one-sided MDI-QKD (1SMDI-QKD) protocol, which enjoys detection loophole-free advantage, and at the same time weakens the state preparation assumption in MDI-QKD. The 1SMDI-QKD can be regarded as a modified MDI-QKD, in which Bob's encoding system is trusted, while Alice's is uncharacterized. For the practical implementation, we also provide a scheme by utilizing coherent light source with an analytical two decoy state estimation method. Simulation with realistic experimental parameters shows that the protocol has a promising performance, and thus can be applied to practical QKD applications.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

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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.

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.

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

Link-state-estimation-based transmission power control in wireless body area networks.

Science.gov (United States)

Kim, Seungku; Eom, Doo-Seop

2014-07-01

This paper presents a novel transmission power control protocol to extend the lifetime of sensor nodes and to increase the link reliability in wireless body area networks (WBANs). We first experimentally investigate the properties of the link states using the received signal strength indicator (RSSI). We then propose a practical transmission power control protocol based on both short- and long-term link-state estimations. Both the short- and long-term link-state estimations enable the transceiver to adapt the transmission power level and target the RSSI threshold range, respectively, to simultaneously satisfy the requirements of energy efficiency and link reliability. Finally, the performance of the proposed protocol is experimentally evaluated in two experimental scenarios-body posture change and dynamic body motion-and compared with the typical WBAN transmission power control protocols, a real-time reactive scheme, and a dynamic postural position inference mechanism. From the experimental results, it is found that the proposed protocol increases the lifetime of the sensor nodes by a maximum of 9.86% and enhances the link reliability by reducing the packet loss by a maximum of 3.02%.

Theoretical basis, application, reliability, and sample size estimates of a Meridian Energy Analysis Device for Traditional Chinese Medicine Research

Directory of Open Access Journals (Sweden)

Ming-Yen Tsai

Full Text Available OBJECTIVES: The Meridian Energy Analysis Device is currently a popular tool in the scientific research of meridian electrophysiology. In this field, it is generally believed that measuring the electrical conductivity of meridians provides information about the balance of bioenergy or Qi-blood in the body. METHODS AND RESULTS: PubMed database based on some original articles from 1956 to 2014 and the authoŕs clinical experience. In this short communication, we provide clinical examples of Meridian Energy Analysis Device application, especially in the field of traditional Chinese medicine, discuss the reliability of the measurements, and put the values obtained into context by considering items of considerable variability and by estimating sample size. CONCLUSION: The Meridian Energy Analysis Device is making a valuable contribution to the diagnosis of Qi-blood dysfunction. It can be assessed from short-term and long-term meridian bioenergy recordings. It is one of the few methods that allow outpatient traditional Chinese medicine diagnosis, monitoring the progress, therapeutic effect and evaluation of patient prognosis. The holistic approaches underlying the practice of traditional Chinese medicine and new trends in modern medicine toward the use of objective instruments require in-depth knowledge of the mechanisms of meridian energy, and the Meridian Energy Analysis Device can feasibly be used for understanding and interpreting traditional Chinese medicine theory, especially in view of its expansion in Western countries.

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

Directory of Open Access Journals (Sweden)

Yecai Liu

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

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

Science.gov (United States)

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

2012-01-01

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

Adiabatic interpretation of a two-level atom diode, a laser device for unidirectional transmission of ground-state atoms

International Nuclear Information System (INIS)

Ruschhaupt, A.; Muga, J. G.

2006-01-01

We present a generalized two-level scheme for an 'atom diode', namely, a laser device that lets a two-level ground-state atom pass in one direction, say from left to right, but not in the opposite direction. The laser field is composed of two lateral state-selective mirror regions and a central pumping region. We demonstrate the robustness of the scheme and propose a physical realization. It is shown that the inclusion of a counterintuitive laser field blocking the excited atoms on the left side of the device is essential for a perfect diode effect. The reason for this, the diodic behavior, and the robustness may be understood with an adiabatic approximation. The conditions to break down the approximation, which imply also the diode failure, are analyzed

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.

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.