Thermal monitoring as a method for estimation of technical state of digital devices
Directory of Open Access Journals (Sweden)
Lavrich Yu. N.
2015-08-01
Full Text Available Requirements to the reliability level of modern element base are so high that traditional methods of assessing the technical condition of electronics become ineffective, the modern theory of reliability has almost no practical applications [1], and reliability index does not reflect the true state of an electronic device due to an insufficient amount of information received during testing of electronic devices. The majority of modern electronics are limitedly easy-to-test. They are equipped with small number of tools for direct measurement that leads to a delayed troubleshooting and the inability to take measures efficiently. Despite the fact that new generations of electronics use modern components and new design technologies, their performance is still defined by two states — serviceability or failure, and the failure still happens unexpectedly. We may note, that failure is an uncontrolled result of an irreversible degradation process, taking place in time and having appropriate time parameters, but it's not the critical act. Research of various structural and hierarchical levels of functional units of digital electronics show that temperature control can be used for automatic condition monitoring of such devices in real time. As a generalized control parameter, it is advisable to use the temperature of the case of the element, and the case itself — as a generalized point.
Reactor core performance estimating device
International Nuclear Information System (INIS)
Tanabe, Akira; Yamamoto, Toru; Shinpuku, Kimihiro; Chuzen, Takuji; Nishide, Fusayo.
1995-01-01
The present invention can autonomously simplify a neural net model thereby enabling to conveniently estimate various amounts which represents reactor core performances by a simple calculation in a short period of time. Namely, a reactor core performance estimation device comprises a nerve circuit net which divides the reactor core into a large number of spacial regions, and receives various physical amounts for each region as input signals for input nerve cells and outputs estimation values of each amount representing the reactor core performances as output signals of output nerve cells. In this case, the nerve circuit net (1) has a structure of extended multi-layered model having direct coupling from an upper stream layer to each of downstream layers, (2) has a forgetting constant q in a corrected equation for a joined load value ω using an inverse error propagation method, (3) learns various amounts representing reactor core performances determined using the physical models as teacher signals, (4) determines the joined load value ω decreased as '0' when it is to less than a predetermined value upon learning described above, and (5) eliminates elements of the nerve circuit net having all of the joined load value decreased to 0. As a result, the neural net model comprises an autonomously simplifying means. (I.S.)
Location Estimation of Mobile Devices
Directory of Open Access Journals (Sweden)
Kamil ŽIDEK
2009-06-01
Full Text Available This contribution describes mathematical model (kinematics for Mobile Robot carriage. The mathematical model is fully parametric. Model is designed universally for any measures three or four wheeled carriage. The next conditions are: back wheels are driving-wheel, front wheels change angle of Robot turning. Position of the front wheel gives the actual position of the robot. Position of the robot is described by coordinates x, y and by angle of the front wheel α in reference position. Main reason for model implementation is indoor navigation. We need some estimation of robot position especially after turning of the Robot. Next use is for outdoor navigation especially for precising GPS information.
DEFF Research Database (Denmark)
Knudsen, Torben
2014-01-01
the results using full-scale wind turbine data. The previously developed methods were based on extended Kalman filtering. This method has several drawback compared to unscented Kalman filtering which has therefore been developed. The unscented Kalman filter was first tested on linear and non-linear test cases......Dynamic inflow is an effect which is normally not included in the models used for wind turbine control design. Therefore, potential improvement from including this effect exists. The objective in this project is to improve the methods previously developed for this and especially to verify...... which was successful. Then the estimation of a wind turbine state including dynamic inflow was tested on a simulated NREL 5MW turbine was performed. This worked perfectly with wind speeds from low to nominal wind speed as the output prediction errors where white. In high wind where the pitch actuator...
Silicon solid state devices and radiation detection
Leroy, Claude
2012-01-01
This book addresses the fundamental principles of interaction between radiation and matter, the principles of working and the operation of particle detectors based on silicon solid state devices. It covers a broad scope with respect to the fields of application of radiation detectors based on silicon solid state devices from low to high energy physics experiments including in outer space and in the medical environment. This book covers stateof- the-art detection techniques in the use of radiation detectors based on silicon solid state devices and their readout electronics, including the latest developments on pixelated silicon radiation detector and their application.
Solid-state devices and applications
Lewis, Rhys
1971-01-01
Solid-State Devices and Applications is an introduction to the solid-state theory and its devices and applications. The book also presents a summary of all major solid-state devices available, their theory, manufacture, and main applications. The text is divided into three sections. The first part deals with the semiconductor theory and discusses the fundamentals of semiconductors; the kinds of diodes and techniques in their manufacture; the types and modes of operation of bipolar transistors; and the basic principles of unipolar transistors and their difference with bipolar transistors. The s
State Estimation for Tensegrity Robots
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.
Solid-state electronic devices an introduction
Papadopoulos, Christo
2014-01-01
A modern and concise treatment of the solid state electronic devices that are fundamental to electronic systems and information technology is provided in this book. The main devices that comprise semiconductor integrated circuits are covered in a clear manner accessible to the wide range of scientific and engineering disciplines that are impacted by this technology. Catering to a wider audience is becoming increasingly important as the field of electronic materials and devices becomes more interdisciplinary, with applications in biology, chemistry and electro-mechanical devices (to name a few) becoming more prevalent. Updated and state-of-the-art advancements are included along with emerging trends in electronic devices and their applications. In addition, an appendix containing the relevant physical background will be included to assist readers from different disciplines and provide a review for those more familiar with the area. Readers of this book can expect to derive a solid foundation for understanding ...
Runtime Verification with State Estimation
Stoller, Scott D.; Bartocci, Ezio; Seyster, Justin; Grosu, Radu; Havelund, Klaus; Smolka, Scott A.; Zadok, Erez
2011-01-01
We introduce the concept of Runtime Verification with State Estimation and show how this concept can be applied to estimate theprobability that a temporal property is satisfied by a run of a program when monitoring overhead is reduced by sampling. In such situations, there may be gaps in the observed program executions, thus making accurate estimation challenging. To deal with the effects of sampling on runtime verification, we view event sequences as observation sequences of a Hidden Markov Model (HMM), use an HMM model of the monitored program to "fill in" sampling-induced gaps in observation sequences, and extend the classic forward algorithm for HMM state estimation (which determines the probability of a state sequence, given an observation sequence) to compute the probability that the property is satisfied by an execution of the program. To validate our approach, we present a case study based on the mission software for a Mars rover. The results of our case study demonstrate high prediction accuracy for the probabilities computed by our algorithm. They also show that our technique is much more accurate than simply evaluating the temporal property on the given observation sequences, ignoring the gaps.
Physics of Nanostructured Solid State Devices
Bandyopadhyay, Supriyo
2012-01-01
Physics of Nanostructured Solid State Devices introduces readers to theories and concepts such as semi-classical and quantum mechanical descriptions of electron transport, methods for calculations of band structures in solids with applications in calculation of optical constants, and other advanced concepts. The information presented here will equip readers with the necessary tools to carry out cutting edge research in modern solid state nanodevices. This book also: Covers sophisticated models of charge transport including the drift-diffusion model, Boltzmann transport model and various quantum transport models Discusses the essential elements of quantum mechanics necessary for an understanding of nanostructured solid state devices Presents band structure calculation methods based on time-independent perturbation theory Discusses theory of optical transitions and optical devices employing quantum-confined structures such as quantum wells,wires and dots Elucidates quantum mechanics of electrons in a magneti...
Estimation methods of unique devices reliability
International Nuclear Information System (INIS)
Fedik, I.I.; Golubev, M.P.
1991-01-01
In this report, the results of the approbation and choice of the methods for the probability analysis of service life and the reliability estimation of unique products including nuclear power plants. In practice, the information on nuclear power plant elements and assemblies is that their properties are not uniform. There are the data on particular tests and also the data on analogous tests. The aim of this work is the development of a methodological approach and an effective algorithm for processing these different data for the reliability estimation of the product at the stage of design and development. The typical situations of the tests and information are considered. As the result of investigation, a number of the methods which form the adaptive algorithm allowing to use practically all the information at research and development stages were chosen. The procedure of effectively using and processing the information is explained. The main features of the proposed algorithm are shown. The systematic prediction error is eliminated, and the casual error in all probability characteristics is reduced. This approach has been used for three types of nuclear power plants, and gave the good results. (K.I.)
Lin, Pei-Sheng; Rosset, Denis; Zhang, Yanbao; Bancal, Jean-Daniel; Liang, Yeong-Cherng
2018-03-01
The device-independent approach to physics is one where conclusions are drawn directly from the observed correlations between measurement outcomes. In quantum information, this approach allows one to make strong statements about the properties of the underlying systems or devices solely via the observation of Bell-inequality-violating correlations. However, since one can only perform a finite number of experimental trials, statistical fluctuations necessarily accompany any estimation of these correlations. Consequently, an important gap remains between the many theoretical tools developed for the asymptotic scenario and the experimentally obtained raw data. In particular, a physical and concurrently practical way to estimate the underlying quantum distribution has so far remained elusive. Here, we show that the natural analogs of the maximum-likelihood estimation technique and the least-square-error estimation technique in the device-independent context result in point estimates of the true distribution that are physical, unique, computationally tractable, and consistent. They thus serve as sound algorithmic tools allowing one to bridge the aforementioned gap. As an application, we demonstrate how such estimates of the underlying quantum distribution can be used to provide, in certain cases, trustworthy estimates of the amount of entanglement present in the measured system. In stark contrast to existing approaches to device-independent parameter estimations, our estimation does not require the prior knowledge of any Bell inequality tailored for the specific property and the specific distribution of interest.
State Alcohol-Impaired-Driving Estimates
... 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 ...
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 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.
UAV State Estimation Modeling Techniques in AHRS
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.
Using Mobile Device Samples to Estimate Traffic Volumes
2017-12-01
In this project, TTI worked with StreetLight Data to evaluate a beta version of its traffic volume estimates derived from global positioning system (GPS)-based mobile devices. TTI evaluated the accuracy of average annual daily traffic (AADT) volume :...
State Energy Data Report, 1991: Consumption estimates
Energy Technology Data Exchange (ETDEWEB)
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.
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.
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
Xu, Ru-Gang; Koga, Dennis (Technical Monitor)
2001-01-01
The goal of 'Estimate' is to take advantage of attitude information to produce better pose while staying flexible and robust. Currently there are several instruments that are used for attitude: gyros, inclinometers, and compasses. However, precise and useful attitude information cannot come from one instrument. Integration of rotational rates, from gyro data for example, would result in drift. Therefore, although gyros are accurate in the short-term, accuracy in the long term is unlikely. Using absolute instruments such as compasses and inclinometers can result in an accurate measurement of attitude in the long term. However, in the short term, the physical nature of compasses and inclinometers, and the dynamic nature of a mobile platform result in highly volatile and therefore useless data. The solution then is to use both absolute and relative data. Kalman Filtering is known to be able to combine gyro and compass/inclinometer data to produce stable and accurate attitude information. Since the model of motion is linear and the data comes in as discrete samples, a Discrete Kalman Filter was selected as the core of the new estimator. Therefore, 'Estimate' can be divided into two parts: the Discrete Kalman Filter and the code framework.
Parameter and State Estimator for State Space Models
Directory of Open Access Journals (Sweden)
Ruifeng Ding
2014-01-01
Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Parameter and state estimator for state space models.
Ding, Ruifeng; Zhuang, Linfan
2014-01-01
This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
State Estimation for Humanoid Robots
2015-07-01
tactical grade IMU mounted on the pelvis of the robot . It provides pelvis orientation and angular velocity, which are used in the forward kinematics ...depends on sensors available to the robot . We use sensed joint posi- tion with forward kinematics to compute CoM position. The root variables are estimated...when the robot is shifting its supporting foot. Fig. 6.4 is a plot of the CoM velocity from the Kalman filter, and from forward kinemat - ics. The CoM
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...... be useful, but that further analysis is needed to evaluate the efficiency of this estimation method compared to traditional methods....
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)
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.
Device-to-Device Underlay Cellular Networks with Uncertain Channel State Information
Memmi, Amen
2016-01-06
Device-to-Device (D2D) communications underlying the cellular infrastructure is a technology that has recently been proposed as a promising solution to enhance cellular network capabilities: It improves spectrum utilization, overall throughput and energy efficiency while enabling new peer-to-peer and location-based applications and services. However, interference is the major challenge since the same resources are shared by both systems. Therefore, interference management techniques are required to keep the interference under control. In this work, in order to mitigate interference, we consider centralized and distributed power control algorithms in a one-cell random network model. Differently from previous works, we are assuming that the channel state information (CSI) may be imperfect and include estimation errors. We evaluate how this uncertainty impacts performances.
Guide to state-of-the-art electron devices
2013-01-01
Concise, high quality and comparative overview of state-of-the-art electron device development, manufacturing technologies and applications Guide to State-of-the-Art Electron Devices marks the 60th anniversary of the IEEE Electron Devices Committee and the 35th anniversary of the IEEE Electron Devices Society, as such it defines the state-of-the-art of electron devices, as well as future directions across the entire field. Spans full range of electron device types such as photovoltaic devices, semiconductor manufacturing and VLSI technology and circuits, covered by IEEE Electron and Devices Society Contributed by internationally respected members of the electron devices community A timely desk reference with fully-integrated colour and a unique lay-out with sidebars to highlight the key terms Discusses the historical developments and speculates on future trends to give a more rounded picture of the topics covered A valuable resource R&D managers; engineers in the semiconductor industry; applied scientists...
State and parameter estimation in bio processes
Energy Technology Data Exchange (ETDEWEB)
Maher, M.; Roux, G.; Dahhou, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France)]|[Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1994-12-31
A major difficulty in monitoring and control of bio-processes is the lack of reliable and simple sensors for following the evolution of the main state variables and parameters such as biomass, substrate, product, growth rate, etc... In this article, an adaptive estimation algorithm is proposed to recover the state and parameters in bio-processes. This estimator utilizes the physical process model and the reference model approach. Experimentations concerning estimation of biomass and product concentrations and specific growth rate, during batch, fed-batch and continuous fermentation processes are presented. The results show the performance of this adaptive estimation approach. (authors) 12 refs.
Linear Covariance Analysis and Epoch State Estimators
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
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
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.
Device-independent randomness generation from several Bell estimators
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.
Introduction to quantum-state estimation
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...
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...
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.
SOLID-STATE STORAGE DEVICE WITH PROGRAMMABLE PHYSICAL STORAGE ACCESS
DEFF Research Database (Denmark)
2017-01-01
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...... 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...
New Concepts for Shipboard Sea State Estimation
DEFF Research Database (Denmark)
Nielsen, Ulrik D.; Bjerregård, Mikkel; Galeazzi, Roberto
2015-01-01
The wave buoy analogy is a tested means for shipboard sea state estimation. Basically, the estimation principle resembles that of a traditional wave rider buoy which relies, fundamentally, on transfer functions used to relate measured wave-induced responses and the unknown wave excitation. This p...
SOLID-STATE STORAGE DEVICE FLASH TRANSLATION LAYER
DEFF Research Database (Denmark)
2017-01-01
Embodiments of the present invention include a method for storing a data page d on a solid-state storage device, wherein the solid-state storage device is configured to maintain a mapping table in a Log-Structure Merge (LSM) tree having a C0 component which is a random access memory (RAM) device...... and a C1 component which is a flash-based memory device. Methods comprise: writing the data page d at a physical storage page having physical storage page address P in the storage device in response to receiving a write request to store the data page d at a logical storage page having a logical storage...
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
Estimating the Energy State of Liquids
Directory of Open Access Journals (Sweden)
Lianwen Wang
2014-12-01
Full Text Available In contrast to the gaseous and the solid states, the liquid state does not have a simple model that could be developed into a quantitative theory. A central issue in the understanding of liquids is to estimate the energy state of liquids. Here, on the basis of our recent studies on crystal melting, we show that the energy sate of liquids may be reasonably approximated by the energy and volume of a vacancy. Consequently, estimation of the liquid state energy is significantly simplified comparing with previous methods that inevitably invoke many-body interactions. Accordingly, a possible equation for the state for liquids is proposed. On this basis, it seems that a simple model for liquids is in sight.
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.
On state estimation in electric drives
Energy Technology Data Exchange (ETDEWEB)
Leon, A.E., E-mail: aleon@ymail.co [Instituto de Investigaciones en Ingenieria Electrica (IIIE) ' Alfredo Desages' (UNS-CONICET), Departamento de Ingenieria Electrica y de Computadoras, Universidad Nacional del Sur - UNS, 1253 Alem Avenue, P.O. 8000, Bahia Blanca (Argentina); Solsona, J.A., E-mail: jsolsona@uns.edu.a [Instituto de Investigaciones en Ingenieria Electrica (IIIE) ' Alfredo Desages' (UNS-CONICET), Departamento de Ingenieria Electrica y de Computadoras, Universidad Nacional del Sur - UNS, 1253 Alem Avenue, P.O. 8000, Bahia Blanca (Argentina)
2010-03-15
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.
2017-12-20
The Food and Drug Administration (FDA or we) is classifying the image processing device for estimation of external blood loss into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the image processing device for estimation of external blood loss' classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.
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.
State estimation for integrated vehicle dynamics control
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
An Empirical State Error Covariance Matrix for Batch State Estimation
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
Resting State Network Estimation in Individual Subjects
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
Spin State Estimation of Tumbling Small Bodies
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.
Applied solid state science advances in materials and device research
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
Applied solid state science advances in materials and device research
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.
Simulation of devices mobility to estimate wireless channel quality metrics in 5G networks
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.
Temperature and Dilatation Estimation for Modern Semiconductor Devices
Directory of Open Access Journals (Sweden)
Eric JOUBERT
2015-01-01
Full Text Available This paper presents a new approach for measuring physical variables on micro- electronic components. An optical system is used to simultaneously quantify the surface temperature of a component and its expansion. This double acquisition is realized by a Michelson interferometer coupled with a Charge Coupled Device (CCD line device. To validate this method, the temperature measurements were directly compared with the results obtained by an infrared camera and by a measurement of variation of I (V. The displacement measurements were compared with those obtained by a laser 3D vibrometer, whose physical principle is completely different. Consistent results were obtained regarding the different techniques.
An Empirical Method to Fuse Partially Overlapping State Vectors for Distributed State Estimation
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.
Hierarchical state-space estimation of leatherback turtle navigation ability.
Directory of Open Access Journals (Sweden)
Joanna Mills Flemming
Full Text Available Remotely sensed tracking technology has revealed remarkable migration patterns that were previously unknown; however, models to optimally use such data have developed more slowly. Here, we present a hierarchical Bayes state-space framework that allows us to combine tracking data from a collection of animals and make inferences at both individual and broader levels. We formulate models that allow the navigation ability of animals to be estimated and demonstrate how information can be combined over many animals to allow improved estimation. We also show how formal hypothesis testing regarding navigation ability can easily be accomplished in this framework. Using Argos satellite tracking data from 14 leatherback turtles, 7 males and 7 females, during their southward migration from Nova Scotia, Canada, we find that the circle of confusion (the radius around an animal's location within which it is unable to determine its location precisely is approximately 96 km. This estimate suggests that the turtles' navigation does not need to be highly accurate, especially if they are able to use more reliable cues as they near their destination. Moreover, for the 14 turtles examined, there is little evidence to suggest that male and female navigation abilities differ. Because of the minimal assumptions made about the movement process, our approach can be used to estimate and compare navigation ability for many migratory species that are able to carry electronic tracking devices.
Improved Battery State Estimation Using Novel Sensing Techniques
Abdul Samad, Nassim
Lithium-ion batteries have been considered a great complement or substitute for gasoline engines due to their high energy and power density capabilities among other advantages. However, these types of energy storage devices are still yet not widespread, mainly because of their relatively high cost and safety issues, especially at elevated temperatures. This thesis extends existing methods of estimating critical battery states using model-based techniques augmented by real-time measurements from novel temperature and force sensors. Typically, temperature sensors are located near the edge of the battery, and away from the hottest core cell regions, which leads to slower response times and increased errors in the prediction of core temperatures. New sensor technology allows for flexible sensor placement at the cell surface between cells in a pack. This raises questions about the optimal locations of these sensors for best observability and temperature estimation. Using a validated model, which is developed and verified using experiments in laboratory fixtures that replicate vehicle pack conditions, it is shown that optimal sensor placement can lead to better and faster temperature estimation. Another equally important state is the state of health or the capacity fading of the cell. This thesis introduces a novel method of using force measurements for capacity fade estimation. Monitoring capacity is important for defining the range of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). Current capacity estimation techniques require a full discharge to monitor capacity. The proposed method can complement or replace current methods because it only requires a shallow discharge, which is especially useful in EVs and PHEVs. Using the accurate state estimation accomplished earlier, a method for downsizing a battery pack is shown to effectively reduce the number of cells in a pack without compromising safety. The influence on the battery performance (e
Optofluidic devices with integrated solid-state nanopores
Hawkins, Aaron R.; Schmidt, Holger
2016-01-01
This review (with 90 refs.) covers the state of the art in optofluidic devices with integrated solid-state nanopores for use in detection and sensing. Following an introduction into principles of optofluidics and solid-state nanopore technology, we discuss features of solid-state nanopore based assays using optofluidics. This includes the incorporation of solid-state nanopores into optofluidic platforms based on liquid-core anti-resonant reflecting optical waveguides (ARROWs), methods for their fabrication, aspects of single particle detection and particle manipulation. We then describe the new functionalities provided by solid-state nanopores integrated into optofluidic chips, in particular acting as smart gates for correlated electro-optical detection and discrimination of nanoparticles. This enables the identification of viruses and λ-DNA, particle trajectory simulations, enhancing sensitivity by tuning the shape of nanopores. The review concludes with a summary and an outlook. PMID:27046940
Energy Technology Data Exchange (ETDEWEB)
Meliopoulos, Sakis [Georgia Inst. of Technology, Atlanta, GA (United States); Cokkinides, George [Georgia Inst. of Technology, Atlanta, GA (United States); Fardanesh, Bruce [New York Power Authority, NY (United States); Hedrington, Clinton [U.S. Virgin Islands Water and Power Authority (WAPA), St. Croix (U.S. Virgin Islands)
2013-12-31
This is the final report for this project that was performed in the period: October1, 2009 to June 30, 2013. In this project, a fully distributed high-fidelity dynamic state estimator (DSE) that continuously tracks the real time dynamic model of a wide area system with update rates better than 60 times per second is achieved. The proposed technology is based on GPS-synchronized measurements but also utilizes data from all available Intelligent Electronic Devices in the system (numerical relays, digital fault recorders, digital meters, etc.). The distributed state estimator provides the real time model of the system not only the voltage phasors. The proposed system provides the infrastructure for a variety of applications and two very important applications (a) a high fidelity generating unit parameters estimation and (b) an energy function based transient stability monitoring of a wide area electric power system with predictive capability. Also the dynamic distributed state estimation results are stored (the storage scheme includes data and coincidental model) enabling an automatic reconstruction and “play back” of a system wide disturbance. This approach enables complete play back capability with fidelity equal to that of real time with the advantage of “playing back” at a user selected speed. The proposed technologies were developed and tested in the lab during the first 18 months of the project and then demonstrated on two actual systems, the USVI Water and Power Administration system and the New York Power Authority’s Blenheim-Gilboa pumped hydro plant in the last 18 months of the project. The four main thrusts of this project, mentioned above, are extremely important to the industry. The DSE with the achieved update rates (more than 60 times per second) provides a superior solution to the “grid visibility” question. The generator parameter identification method fills an important and practical need of the industry. The “energy function” based
RSPF-based Prognosis Framework for Estimation of Remaining Useful Life in Energy Storage Devices
National Aeronautics and Space Administration — This paper presents a case study where a RSPF-based prognosis framework is applied to estimate the remaining useful life of an energy storage device (Li-Ion...
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
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...... 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...... of this method is the use of phasor measurements to improve results of conventional state estimator and detect the bad data associated with critical measurements, which cannot be detected by the conventional sate estimation algorithm. This algorithm will be developed based on (rNmax) test that shows that phasor...
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 st...
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.
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.
State estimation for a hexapod robot
CSIR Research Space (South Africa)
Lubbe, Estelle
2015-09-01
Full Text Available on a quadruped. The EKF fuses the kinematic model with on-board IMU measurements to estimate the pose of the robot. The methodology was tested with experiments using a physical hexapod robot and validated with independent ground truth measurements....
Park, Jong-Uk; Erdenebayar, Urtnasan; Joo, Eun-Yeon; Lee, Kyoung-Joung
2017-06-27
This paper proposes a method for classifying sleep-wakefulness and estimating sleep parameters using nasal pressure signals applicable to a continuous positive airway pressure (CPAP) device. In order to classify the sleep-wakefulness states of patients with sleep-disordered breathing (SDB), apnea-hypopnea and snoring events are first detected. Epochs detected as SDB are classified as sleep, and time-domain- and frequency-domain-based features are extracted from the epochs that are detected as normal breathing. Subsequently, sleep-wakefulness is classified using a support vector machine (SVM) classifier in the normal breathing epoch. Finally, four sleep parameters-sleep onset, wake after sleep onset, total sleep time and sleep efficiency-are estimated based on the classified sleep-wakefulness. In order to develop and test the algorithm, 110 patients diagnosed with SDB participated in this study. Ninety of the subjects underwent full-night polysomnography (PSG) and twenty underwent split-night PSG. The subjects were divided into 50 patients of a training set (full/split: 42/8), 30 of a validation set (full/split: 24/6) and 30 of a test set (full/split: 24/6). In the experiments conducted, sleep-wakefulness classification accuracy was found to be 83.2% in the test set, compared with the PSG scoring results of clinical experts. Furthermore, all four sleep parameters showed higher correlations than the results obtained via PSG (r ⩾ 0.84, p CPAP, sleep-wakefulness classification performances were evaluated for each CPAP in the split-night PSG data. The results indicate that the accuracy and sensitivity of sleep-wakefulness classification by CPAP variation shows no statistically significant difference (p CPAP devices and evaluation of the quality of sleep.
Schneider, Iris K.; Parzuchowski, Michal; Wojciszke, Bogdan; Schwarz, Norbert; Koole, Sander L.
2015-01-01
Previous work suggests 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 po...
Bayesian estimation of traffic lane state
Czech Academy of Sciences Publication Activity Database
Nagy, Ivan; Kárný, Miroslav; Nedoma, Petr; Voráčová, Š.
2003-01-01
Roč. 17, č. 1 (2003), s. 51-65 ISSN 0890-6327 R&D Projects: GA ČR GA102/03/0049; GA AV ČR IBS1075351 Institutional research plan: CEZ:AV0Z1075907 Keywords : mixture models * estimation * Bayesian approach Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.602, year: 2003 http://library.utia.cas.cz/prace/20030021.ps
Application of radial basis neural network for state estimation of ...
African Journals Online (AJOL)
user
An original application of radial basis function (RBF) neural network for power system state estimation is proposed in this ... conventional Weighted Least Squares (WLS) State Estimator on basis of time, accuracy and robustness. ... redundant measurement data normally available in form of nodal injection and line flows.
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 ...
State Estimation for the Automotive SCR Process
DEFF Research Database (Denmark)
Zhou, Guofeng; Huusom, Jakob Kjøbsted; Jørgensen, John Bagterp
2012-01-01
Selective catalytic reduction (SCR) of NOx is a widely applied diesel engine exhaust gas aftertreatment technology. For advanced SCR process control, like model predictive control, full state information of the process is required. The ammonia coverage ratio inside the catalyst is difficult to me...
New developments in state estimation for Nonlinear Systems
DEFF Research Database (Denmark)
Nørgård, Peter Magnus; Poulsen, Niels Kjølstad; Ravn, Ole
2000-01-01
-dimensional interpolation formula. It is shown that under certain assumptions the estimators perform better than estimators based on Taylor approximations. Nevertheless, the implementation is significantly simpler as no derivatives are required. Thus, it is believed that the new state estimators can replace well...
Advances in Derivative-Free State Estimation for Nonlinear Systems
DEFF Research Database (Denmark)
Nørgaard, Magnus; Poulsen, Niels Kjølstad; Ravn, Ole
In this paper we show that it involves considerable advantages to use polynomial approximations obtained with an interpolation formula for derivation of state estimators for nonlinear systems. The estimators become more accurate than estimators based on Taylor approximations, and yet the implemen...
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.
TPmsm: Estimation of the Transition Probabilities in 3-State Models
Directory of Open Access Journals (Sweden)
Artur Araújo
2014-12-01
Full Text Available One major goal in clinical applications of multi-state models is the estimation of transition probabilities. The usual nonparametric estimator of the transition matrix for non-homogeneous Markov processes is the Aalen-Johansen estimator (Aalen and Johansen 1978. However, two problems may arise from using this estimator: first, its standard error may be large in heavy censored scenarios; second, the estimator may be inconsistent if the process is non-Markovian. The development of the R package TPmsm has been motivated by several recent contributions that account for these estimation problems. Estimation and statistical inference for transition probabilities can be performed using TPmsm. The TPmsm package provides seven different approaches to three-state illness-death modeling. In two of these approaches the transition probabilities are estimated conditionally on current or past covariate measures. Two real data examples are included for illustration of software usage.
Digital Real-Time Multiple Channel Multiple Mode Neutron Flux Estimation on FPGA-based Device
Directory of Open Access Journals (Sweden)
Thevenin Mathieu
2016-01-01
Full Text Available This paper presents a complete custom full-digital instrumentation device that was designed for real-time neutron flux estimation, especially for nuclear reactor in-core measurement using subminiature Fission Chambers (FCs. Entire fully functional small-footprint design (about 1714 LUTs is implemented on FPGA. It enables real-time acquisition and analysis of multiple channels neutron's flux both in counting mode and Campbelling mode. Experimental results obtained from this brand new device are consistent with simulation results and show good agreement within good uncertainty. This device paves the way for new applications perspectives in real-time nuclear reactor monitoring.
State estimation for large-scale wastewater treatment plants.
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.
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.
The Mirror Illusion’s Effects on Body State Estimation
Soliman, Tamer M.; Buxbaum, Laurel J.; Jax, Steven A.
2016-01-01
The mirror illusion uses a standard mirror to create a compelling illusion in which movements of one limb seem to be made by the other hidden limb. In this paper we adapt a motor control framework to examine which estimates of the body’s configuration are affected by the illusion. We propose that the illusion primarily alters estimates related to upcoming states of the body (the desired state and the predicted state), with smaller effects on the estimate of the body state prior to movement initiation. Support for this proposal is provided both by behavioral effects of the illusion as well as neuroimaging evidence from one neural region, V6A, that is critically involved in the mirror illusion and limb state estimation more generally. PMID:27390062
State estimation for autopilot control of small unmanned aerial vehicles in windy conditions
Poorman, David Paul
The use of small unmanned aerial vehicles (UAVs) both in the military and civil realms is growing. This is largely due to the proliferation of inexpensive sensors and the increase in capability of small computers that has stemmed from the personal electronic device market. Methods for performing accurate state estimation for large scale aircraft have been well known and understood for decades, which usually involve a complex array of expensive high accuracy sensors. Performing accurate state estimation for small unmanned aircraft is a newer area of study and often involves adapting known state estimation methods to small UAVs. State estimation for small UAVs can be more difficult than state estimation for larger UAVs due to small UAVs employing limited sensor suites due to cost, and the fact that small UAVs are more susceptible to wind than large aircraft. The purpose of this research is to evaluate the ability of existing methods of state estimation for small UAVs to accurately capture the states of the aircraft that are necessary for autopilot control of the aircraft in a Dryden wind field. The research begins by showing which aircraft states are necessary for autopilot control in Dryden wind. Then two state estimation methods that employ only accelerometer, gyro, and GPS measurements are introduced. The first method uses assumptions on aircraft motion to directly solve for attitude information and smooth GPS data, while the second method integrates sensor data to propagate estimates between GPS measurements and then corrects those estimates with GPS information. The performance of both methods is analyzed with and without Dryden wind, in straight and level flight, in a coordinated turn, and in a wings level ascent. It is shown that in zero wind, the first method produces significant steady state attitude errors in both a coordinated turn and in a wings level ascent. In Dryden wind, it produces large noise on the estimates for its attitude states, and has a non
High efficiency solid-state sensitized heterojunction photovoltaic device
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.
Response-Based Estimation of Sea State Parameters
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 sea state parameters can be estimated by Bayesian Modelling which uses complex-valued frequency response functions (FRF) to estimate the wave spectrum on the basis...... of measured ship responses. It is therefore interesting to investigate how the filtering aspect, introduced by FRF, affects the final outcome of the estimation procedures. The paper contains a study based on numerical generated time series, and the study shows that filtering has an influence...
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 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...
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
Schneider, Iris K; Parzuchowski, Michal; Wojciszke, Bogdan; Schwarz, Norbert; Koole, Sander L
2014-01-01
Previous work suggests 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 tax information 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 (Experiments 2A,B).
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.
Directory of Open Access Journals (Sweden)
Wydra Michał
2016-06-01
Full Text Available Power system state estimation is a process of real-time online modeling of an electric power system. The estimation is performed with the application of a static model of the system and current measurements of electrical quantities that are encumbered with an error. Usually, a model of the estimated system is also encumbered with an uncertainty, especially power line resistances that depend on the temperature of conductors. At present, a considerable development of technologies for dynamic power line rating can be observed. Typically, devices for dynamic line rating are installed directly on the conductors and measure basic electric parameters such as the current and voltage as well as non-electric ones as the surface temperature of conductors, their expansion, stress or the conductor sag angle relative to the plumb line. The objective of this paper is to present a method for power system state estimation that uses temperature measurements of overhead line conductors as supplementary measurements that enhance the model quality and thereby the estimation accuracy. Power system state estimation is presented together with a method of using the temperature measurements of power line conductors for updating the static power system model in the state estimation process. The results obtained with that method have been analyzed based on the estimation calculations performed for an example system - with and without taking into account the conductor temperature measurements. The final part of the article includes conclusions and suggestions for the further research.
National intelligence estimates and the Failed State Index.
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.
Estimation of background radiation at Rivers State University of ...
African Journals Online (AJOL)
Background radiation from the use of photocopies, computers and other electronic devices around River State University of Science and Technology was measured using a specialize digital, radiation meter type, radalert - 50, which is optimized to detect radiations like alpha, beta, gamma and x-rays. Measurements were ...
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.
Sea State Estimation Using Vessel Response in Dynamic Positioning
DEFF Research Database (Denmark)
H. Brodtkorb, Astrid; Nielsen, Ulrik Dam; J. Sørensen, Asgeir
2018-01-01
This paper presents a novel method for estimating the sea state parameters based on the heave, roll and pitch response of a vessel in dynamic positioning (DP), i.e., without forward speed. The algorithm finds the wave spectrum estimate from the response measurements by directly solving a set...
Hybrid Approach to State Estimation for Bioprocess Control.
Simutis, Rimvydas; Lübbert, Andreas
2017-03-08
An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF) is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the less established relationship between the state variables and the measurement quantities, is formulated in a data driven way. The latter is formulated by means of a support vector regression (SVR) model. The UKF is applied to a recombinant therapeutic protein production process using Escherichia coli bacteria. Additionally, the state vector was extended by the specific biomass growth rate µ in order to allow for the estimation of this key variable which is crucial for the implementation of innovative control algorithms in recombinant therapeutic protein production processes. The state estimates depict a sufficiently low noise level which goes perfectly with different advanced bioprocess control applications.
Metastable State Diamond Growth and its Applications to Electronic Devices.
Jeng, David Guang-Kai
Diamond which consists of a dense array of carbon atoms joined by strong covalent bonds and formed into a tetrahedral crystal structure has remarkable mechanical, thermal, optical and electrical properties suitable for many industrial applications. With a proper type of doping, diamond is also an ideal semiconductor for high performance electronic devices. Unfortunately, natural diamond is rare and limited by its size and cost, it is not surprising that people continuously look for a synthetic replacement. It was believed for long time that graphite, another form of carbon, may be converted into diamond under high pressure and temperature. However, the exact condition of conversion was not clear. In 1939, O. I. Leipunsky developed an equilibrium phase diagram between graphite and diamond based on thermodynamic considerations. In the phase diagram, there is a low temperature (below 1000^ circC) and low pressure (below 1 atm) region in which diamond is metastable and graphite is stable, therefore establishes the conditions for the coexistence of the two species. Leipunsky's pioneer work opened the door for diamond synthesis. In 1955, the General Electric company (GE) was able to produce artificial diamond at 55k atm pressure and a temperature of 2000^ circC. Contrary to GE, B. Derjaguin and B. V. Spitzyn in Soviet Union, developed a method of growing diamonds at 1000^circC and at a much lower pressure in 1956. Since then, researchers, particularly in Soviet Union, are continuously looking for methods to grow diamond and diamond film at lower temperatures and pressures with slow but steady progress. It was only in the early 80's that the importance of growing diamond films had attracted the attentions of researchers in the Western world and in Japan. Recent progress in plasma physics and chemical vapor deposition techniques in integrated electronics technology have pushed the diamond growth in its metastable states into a new era. In this research, a microwave plasma
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.
Macroscopic Traffic State Estimation: Understanding Traffic Sensing Data-Based Estimation Errors
Directory of Open Access Journals (Sweden)
Paul B. C. van Erp
2017-01-01
Full Text Available Traffic state estimation is a crucial element in traffic management systems and in providing traffic information to road users. In this article, we evaluate traffic sensing data-based estimation error characteristics in macroscopic traffic state estimation. We consider two types of sensing data, that is, loop-detector data and probe speed data. These data are used to estimate the mean speed in a discrete space-time mesh. We assume that there are no errors in the sensing data. This allows us to study the errors resulting from the differences in characteristics between the sensing data and desired estimate together with the incomplete description of the relation between the two. The aim of the study is to evaluate the dependency of this estimation error on the traffic conditions and sensing data characteristics. For this purpose, we use microscopic traffic simulation, where we compare the estimates with the ground truth using Edie’s definitions. The study exposes a relation between the error distribution characteristics and traffic conditions. Furthermore, we find that it is important to account for the correlation between individual probe data-based estimation errors. Knowledge related to these estimation errors contributes to making better use of the available sensing data in traffic state estimation.
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...... 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...
Vehicle lateral state estimation based on measured tyre forces.
Tuononen, Ari J
2009-01-01
Future active safety systems need more accurate information about the state of vehicles. This article proposes a method to evaluate the lateral state of a vehicle based on measured tyre forces. The tyre forces of two tyres are estimated from optically measured tyre carcass deflections and transmitted wirelessly to the vehicle body. The two remaining tyres are so-called virtual tyre sensors, the forces of which are calculated from the real tyre sensor estimates. The Kalman filter estimator for lateral vehicle state based on measured tyre forces is presented, together with a simple method to define adaptive measurement error covariance depending on the driving condition of the vehicle. The estimated yaw rate and lateral velocity are compared with the validation sensor measurements.
Vehicle Lateral State Estimation Based on Measured Tyre Forces
Directory of Open Access Journals (Sweden)
Ari J. Tuononen
2009-10-01
Full Text Available Future active safety systems need more accurate information about the state of vehicles. This article proposes a method to evaluate the lateral state of a vehicle based on measured tyre forces. The tyre forces of two tyres are estimated from optically measured tyre carcass deflections and transmitted wirelessly to the vehicle body. The two remaining tyres are so-called virtual tyre sensors, the forces of which are calculated from the real tyre sensor estimates. The Kalman filter estimator for lateral vehicle state based on measured tyre forces is presented, together with a simple method to define adaptive measurement error covariance depending on the driving condition of the vehicle. The estimated yaw rate and lateral velocity are compared with the validation sensor measurements.
Progressive Bayes: a new framework for nonlinear state estimation
Hanebeck, Uwe D.; Briechle, Kai; Rauh, Andreas
2003-04-01
This paper is concerned with recursively estimating the internal state of a nonlinear dynamic system by processing noisy measurements and the known system input. In the case of continuous states, an exact analytic representation of the probability density characterizing the estimate is generally too complex for recursive estimation or even impossible to obtain. Hence, it is replaced by a convenient type of approximate density characterized by a finite set of parameters. Of course, parameters are desired that systematically minimize a given measure of deviation between the (often unknown) exact density and its approximation, which in general leads to a complicated optimization problem. Here, a new framework for state estimation based on progressive processing is proposed. Rather than trying to solve the original problem, it is exactly converted into a corresponding system of explicit ordinary first-order differential equations. Solving this system over a finite "time" interval yields the desired optimal density parameters.
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.
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.
Fuzzy filter for state estimation of a glucoregulatory system.
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.
Estimating the Burden of Chagas Disease in the United States.
Manne-Goehler, Jennifer; Umeh, Chukwuemeka A; Montgomery, Susan P; Wirtz, Veronika J
2016-11-01
In recent years, there has been growing awareness of the significant burden of Chagas disease in the United States (US). However, epidemiological data on both prevalence and access to care for this disease are limited. The objective of this study is to provide an updated national estimate of Chagas disease prevalence, the first state-level estimates of cases of T. cruzi infection in the US and to analyze these estimates in the context of data on confirmed cases of infection in the US blood supply. In this study, we calculated estimates of the state and national prevalence of Chagas disease. The number of residents originally from Chagas disease endemic countries were computed using data on Foreign-Born Hispanic populations from the American Community Survey, along with recent prevalence estimates for Chagas disease in Latin America from the World Health Organization that were published in 2006 and updated in 2015. We then describe the distribution of estimated cases in each state in relation to the number of infections identified in the donated blood supply per data from the AABB (formerly American Association of Blood Banks). The results of this analysis offer an updated national estimate of 238,091 cases of T. cruzi infection in the United States as of 2012, using the same method as was used by Bern and Montgomery to estimate cases in 2005. This estimate indicates that there are 62,070 cases less than the most recent prior estimate, though it does not include undocumented immigrants who may account for as many as 109,000 additional cases. The state level results show that four states (California, Texas, Florida and New York) have over 10,000 cases and an additional seven states have over 5,000 cases. Moreover, since 2007, the AABB has reported 1,908 confirmed cases of T. cruzi infection identified through screening of blood donations. This study demonstrates a substantial burden of Chagas disease in the US, with state variation that reflects the distribution of
Hybrid Approach to State Estimation for Bioprocess Control
Simutis, Rimvydas; L?bbert, Andreas
2017-01-01
An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF) is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the less established relationship between the state variables and the measurement quantities, is formula...
Active classification for POMDPs: A kalman-like state estimator
Zois, DS; Levorato, M; Mitra, U
2014-01-01
© 1991-2012 IEEE. The problem of state tracking with active observation control is considered for a system modeled by a discrete-time, finite-state Markov chain observed through conditionally Gaussian measurement vectors. The measurement model statistics are shaped by the underlying state and an exogenous control input, which influence the observations' quality. Exploiting an innovations approach, an approximate minimum mean-squared error (MMSE) filter is derived to estimate the Markov chain ...
Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation.
Liu, Xi; Qu, Hua; Zhao, Jihong; Yue, Pengcheng; Wang, Meng
2016-09-20
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.
Deep energetic trap states in organic photovoltaic devices
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.
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...
Minimax estimation of qubit states with Bures risk
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.
State-level estimates of cancer-related absenteeism costs.
Tangka, Florence K; Trogdon, Justin G; Nwaise, Isaac; Ekwueme, Donatus U; Guy, Gery P; Orenstein, Diane
2013-09-01
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. 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. 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. 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.
Dynamic state estimation assisted power system monitoring and protection
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
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.
Estimating annualized earthquake losses for the conterminous 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.
Estimation of current sheath curvature in plasma focus device using magnetic probes
International Nuclear Information System (INIS)
Li, Cai; Yujuan, Shi; Patran, A.; Rawat, R.S.
2002-01-01
The dynamics of current sheath, in terms of its speed and sheath curvature, in dense plasma focus device was investigated in its axial acceleration phase using multiple magnetic probes. The investigation was performed for different filling gas pressures of neon. The relative X-ray yields were estimated using a diode X-ray spectrometer. A possible correlation between the current sheath curvature and the X-ray emission was explored. The investigation demonstrates the effective use of relatively simple diagnostics tool, the magnetic probes, in the estimation of current sheath axial speeds and curvatures. (authors)
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)
DEFF Research Database (Denmark)
Ma, Ke; Liserre, Marco; Blaabjerg, Frede
2015-01-01
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 for the re......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....... Consequently, a relative more advanced approach is proposed in this paper, which is based on the loading and strength analysis of devices and takes into account different time constants of the thermal behaviors in power converter. With the established methods for loading and lifetime estimation for power...... 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....
Olberg, Britta; Perleth, Matthias; Felgentraeger, Katja; Schulz, Sandra; Busse, Reinhard
2017-01-01
The aim of this study was to assess the quality of reporting sample size calculation and underlying design assumptions in pivotal trials of high-risk medical devices (MDs) for neurological conditions. Systematic review of research protocols for publicly registered randomized controlled trials (RCTs). In the absence of a published protocol, principal investigators were contacted for additional data. To be included, trials had to investigate a high-risk MD, registered between 2005 and 2015, with indications stroke, headache disorders, and epilepsy as case samples within central nervous system diseases. Extraction of key methodological parameters for sample size calculation was performed independently and peer-reviewed. In a final sample of seventy-one eligible trials, we collected data from thirty-one trials. Eighteen protocols were obtained from the public domain or principal investigators. Data availability decreased during the extraction process, with almost all data available for stroke-related trials. Of the thirty-one trials with sample size information available, twenty-six reported a predefined calculation and underlying assumptions. Justification was given in twenty and evidence for parameter estimation in sixteen trials. Estimates were most often based on previous research, including RCTs and observational data. Observational data were predominantly represented by retrospective designs. Other references for parameter estimation indicated a lower level of evidence. Our systematic review of trials on high-risk MDs confirms previous research, which has documented deficiencies regarding data availability and a lack of reporting on sample size calculation. More effort is needed to ensure both relevant sources, that is, original research protocols, to be publicly available and reporting requirements to be standardized.
Robust state estimation for neural networks with discontinuous activations.
Liu, Xiaoyang; Cao, Jinde
2010-12-01
Discontinuous dynamical systems, particularly neural networks with discontinuous activation functions, arise in a number of applications and have received considerable research attention in recent years. In this paper, the robust state estimation problem is investigated for uncertain neural networks with discontinuous activations and time-varying delays, where the neuron-dependent nonlinear disturbance on the network outputs are only assumed to satisfy the local Lipschitz condition. Based on the theory of differential inclusions and nonsmooth analysis, several criteria are presented to guarantee the existence of the desired robust state estimator for the discontinuous neural networks. It is shown that the design of the state estimator for such networks can be achieved by solving some linear matrix inequalities, which are dependent on the size of the time derivative of the time-varying delays. Finally, numerical examples are given to illustrate the theoretical results.
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.
Use of Mobile Devices: A Case Study with Children from Kuwait and the 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…
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.
Disruption of state estimation in the human lateral cerebellum.
Directory of Open Access Journals (Sweden)
R Chris Miall
2007-11-01
Full Text Available The cerebellum has been proposed to be a crucial component in the state estimation process that combines information from motor efferent and sensory afferent signals to produce a representation of the current state of the motor system. Such a state estimate of the moving human arm would be expected to be used when the arm is rapidly and skillfully reaching to a target. We now report the effects of transcranial magnetic stimulation (TMS over the ipsilateral cerebellum as healthy humans were made to interrupt a slow voluntary movement to rapidly reach towards a visually defined target. Errors in the initial direction and in the final finger position of this reach-to-target movement were significantly higher for cerebellar stimulation than they were in control conditions. The average directional errors in the cerebellar TMS condition were consistent with the reaching movements being planned and initiated from an estimated hand position that was 138 ms out of date. We suggest that these results demonstrate that the cerebellum is responsible for estimating the hand position over this time interval and that TMS disrupts this state estimate.
Estimating the state of large spatio-temporally chaotic systems
Energy Technology Data Exchange (ETDEWEB)
Ott, E. [University of Maryland, College Park, MD 20742 (United States); Hunt, B.R. [University of Maryland, College Park, MD 20742 (United States); Szunyogh, I. [University of Maryland, College Park, MD 20742 (United States)]. E-mail: szunyogh@ipst.umd.edu; Zimin, A.V. [University of Maryland, College Park, MD 20742 (United States); Kostelich, E.J. [University of Maryland, College Park, MD 20742 (United States); Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287 (United States); Corazza, M. [University of Maryland, College Park, MD 20742 (United States); Kalnay, E. [University of Maryland, College Park, MD 20742 (United States); Patil, D.J. [University of Maryland, College Park, MD 20742 (United States); Yorke, J.A. [University of Maryland, College Park, MD 20742 (United States)
2004-09-27
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.
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 well as for DD1 lter and the DD2 lter, as well as functions for Unscented Kalman lters and several versions of particle lters. The toolbox requires MATLAB version 7, but no additional toolboxes are required....
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
Remote optimal state estimation over communication channels with random delays
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.
Demographic estimation methods for plants with unobservable life-states
Kery, M.; Gregg, K.B.; Schaub, M.
2005-01-01
Demographic estimation of vital parameters in plants with an unobservable dormant state is complicated, because time of death is not known. Conventional methods assume that death occurs at a particular time after a plant has last been seen aboveground but the consequences of assuming a particular duration of dormancy have never been tested. Capture-recapture methods do not make assumptions about time of death; however, problems with parameter estimability have not yet been resolved. To date, a critical comparative assessment of these methods is lacking. We analysed data from a 10 year study of Cleistes bifaria, a terrestrial orchid with frequent dormancy, and compared demographic estimates obtained by five varieties of the conventional methods, and two capture-recapture methods. All conventional methods produced spurious unity survival estimates for some years or for some states, and estimates of demographic rates sensitive to the time of death assumption. In contrast, capture-recapture methods are more parsimonious in terms of assumptions, are based on well founded theory and did not produce spurious estimates. In Cleistes, dormant episodes lasted for 1-4 years (mean 1.4, SD 0.74). The capture-recapture models estimated ramet survival rate at 0.86 (SE~ 0.01), ranging from 0.77-0.94 (SEs # 0.1) in anyone year. The average fraction dormant was estimated at 30% (SE 1.5), ranging 16 -47% (SEs # 5.1) in anyone year. Multistate capture-recapture models showed that survival rates were positively related to precipitation in the current year, but transition rates were more strongly related to precipitation in the previous than in the current year, with more ramets going dormant following dry years. Not all capture-recapture models of interest have estimable parameters; for instance, without excavating plants in years when they do not appear aboveground, it is not possible to obtain independent timespecific survival estimates for dormant plants. We introduce rigorous
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.
Complex sample survey estimation in static state-space
Raymond L. Czaplewski
2010-01-01
Increased use of remotely sensed data is a key strategy adopted by the Forest Inventory and Analysis Program. However, multiple sensor technologies require complex sampling units and sampling designs. The Recursive Restriction Estimator (RRE) accommodates this complexity. It is a design-consistent Empirical Best Linear Unbiased Prediction for the state-vector, which...
Improving the accuracy of estimation of eutrophication state index ...
African Journals Online (AJOL)
ISSN 1816-7950 (On-line) = Water SA Vol. 41 No. 5 October 2015. Published under a Creative Commons Attribution Licence. Improving the accuracy of estimation of eutrophication state index using a remote sensing data-driven method: A case study of Chaohu Lake, China. Bo Xiang1, 2*, Jing-Wei Song1, 2, Xin-Yuan ...
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.
Estimation of beryllium ground state energy by Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Kabir, K. M. Ariful [Department of Physical Sciences, School of Engineering and Computer Science, Independent University, Bangladesh (IUB) Dhaka (Bangladesh); Halder, Amal [Department of Mathematics, University of Dhaka Dhaka (Bangladesh)
2015-05-15
Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.
Estimating aboveground live understory vegetation carbon in the United States
Johnson, Kristofer D.; Domke, Grant M.; Russell, Matthew B.; Walters, Brian; Hom, John; Peduzzi, Alicia; Birdsey, Richard; Dolan, Katelyn; Huang, Wenli
2017-12-01
Despite the key role that understory vegetation plays in ecosystems and the terrestrial carbon cycle, it is often overlooked and has few quantitative measurements, especially at national scales. To understand the contribution of understory carbon to the United States (US) carbon budget, we developed an approach that relies on field measurements of understory vegetation cover and height on US Department of Agriculture Forest Service, Forest Inventory and Analysis (FIA) subplots. Allometric models were developed to estimate aboveground understory carbon. A spatial model based on stand characteristics and remotely sensed data was also applied to estimate understory carbon on all FIA plots. We found that most understory carbon was comprised of woody shrub species (64%), followed by nonwoody forbs and graminoid species (35%) and seedlings (1%). The largest estimates were found in temperate or warm humid locations such as the Pacific Northwest and southeastern US, thus following the same broad trend as aboveground tree biomass. The average understory aboveground carbon density was estimated to be 0.977 Mg ha-1, for a total estimate of 272 Tg carbon across all managed forest land in the US (approximately 2% of the total aboveground live tree carbon pool). This estimate is more than twice as low as previous FIA modeled estimates that did not rely on understory measurements, suggesting that this pool may currently be overestimated in US National Greenhouse Gas reporting.
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
Controllability, not chaos, key criterion for ocean state estimation
Gebbie, Geoffrey; Hsieh, Tsung-Lin
2017-07-01
The Lagrange multiplier method for combining observations and models (i.e., the adjoint method or 4D-VAR) has been avoided or approximated when the numerical model is highly nonlinear or chaotic. This approach has been adopted primarily due to difficulties in the initialization of low-dimensional chaotic models, where the search for optimal initial conditions by gradient-descent algorithms is hampered by multiple local minima. Although initialization is an important task for numerical weather prediction, ocean state estimation usually demands an additional task - a solution of the time-dependent surface boundary conditions that result from atmosphere-ocean interaction. Here, we apply the Lagrange multiplier method to an analogous boundary control problem, tracking the trajectory of the forced chaotic pendulum. Contrary to previous assertions, it is demonstrated that the Lagrange multiplier method can track multiple chaotic transitions through time, so long as the boundary conditions render the system controllable. Thus, the nonlinear timescale poses no limit to the time interval for successful Lagrange multiplier-based estimation. That the key criterion is controllability, not a pure measure of dynamical stability or chaos, illustrates the similarities between the Lagrange multiplier method and other state estimation methods. The results with the chaotic pendulum suggest that nonlinearity should not be a fundamental obstacle to ocean state estimation with eddy-resolving models, especially when using an improved first-guess trajectory.
International Nuclear Information System (INIS)
Liang Tao; Jia Xinzhang
2012-01-01
The problem of yield estimation merely from performance test data of qualified semiconductor devices is studied. An empirical formula is presented to calculate the yield directly by the sample mean and standard deviation of singly truncated normal samples based on the theoretical relation between process capability indices and the yield. Firstly, we compare four commonly used normality tests under different conditions, and simulation results show that the Shapiro—Wilk test is the most powerful test in recognizing singly truncated normal samples. Secondly, the maximum likelihood estimation method and the empirical formula are compared by Monte Carlo simulation. The results show that the simple empirical formulas can achieve almost the same accuracy as the maximum likelihood estimation method but with a much lower amount of calculations when estimating yield from singly truncated normal samples. In addition, the empirical formula can also be used for doubly truncated normal samples when some specific conditions are met. Practical examples of yield estimation from academic and IC test data are given to verify the effectiveness of the proposed method. (semiconductor integrated circuits)
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.
Forward models and state estimation in compensatory eye movements
Directory of Open Access Journals (Sweden)
Maarten A Frens
2009-11-01
Full Text Available The compensatory eye movement system maintains a stable retinal image, integrating information from different sensory modalities to compensate for head movements. Inspired by recent models of physiology of limb movements, we suggest that compensatory eye movements (CEM can be modeled as a control system with three essential building blocks: a forward model that predicts the effects of motor commands; a state estimator that integrates sensory feedback into this prediction; and, a feedback controller that translates a state estimate into motor commands. We propose a specific mapping of nuclei within the CEM system onto these control functions. Specifically, we suggest that the Flocculus is responsible for generating the forward model prediction and that the Vestibular Nuclei integrate sensory feedback to generate an estimate of current state. Finally, the brainstem motor nuclei – in the case of horizontal compensation this means the Abducens Nucleus and the Nucleus Prepositus Hypoglossi – implement a feedback controller, translating state into motor commands. While these efforts to understand the physiological control system as a feedback control system are in their infancy, there is the intriguing possibility that compensatory eye movements and targeted voluntary movements use the same cerebellar circuitry in fundamentally different ways.
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 Estimation for Landing Maneuver on High Performance Aircraft
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.
Heterojunction Solid-State Devices for Millimeter-Wave Sources.
1983-10-01
ergy barrier in the conduction band. Current flow through pa) and distance (x_-. 1 pm) scales has identified velocity the barrier is asymetrical with...response should also be as flat as possible. The synthesis of maximally tolerant The excellent work of Me. Kathy Julian. the filters will aid the...device capacitance variations is presented. A synthesis procedure for these networks is presented and experimentally verified with the con- struction of a
Estimated use of water in the United States in 2005
Kenny, Joan F.; Barber, Nancy L.; Hutson, Susan S.; Linsey, Kristin S.; Lovelace, John K.; Maupin, Molly A.
2009-01-01
Estimates of water use in the United States indicate that about 410 billion gallons per day (Bgal/d) were withdrawn in 2005 for all categories summarized in this report. This total is slightly less than the estimate for 2000, and about 5 percent less than total withdrawals in the peak year of 1980. Freshwater withdrawals in 2005 were 349 Bgal/d, or 85 percent of the total freshwater and saline-water withdrawals. Fresh groundwater withdrawals of 79.6 Bgal/day in 2005 were about 5 percent less than in 2000, and fresh surface-water withdrawals of 270 Bgal/day were about the same as in 2000. Withdrawals for thermoelectric-power generation and irrigation, the two largest uses of water, have stabilized or decreased since 1980. Withdrawals for public-supply and domestic uses have increased steadily since estimates began.
State estimation in water distribution network: A review
CSIR Research Space (South Africa)
Tshehla, KS
2017-11-01
Full Text Available state estimation can be categorised according to the minimisation cost function used. This is formulated as either a quadratic or a non-quadratic function. According to Arsene and Gabrys [12] the criterion used in the SE procedure can be divided... and a constrained optimization problem was solved using a Successive Quadratic Programming (SQP) technique which implied the calculation of the Jacobian and the Hessian matrices of the objective function and the Jacobian of the reduced constraints...
State Estimation For An Agonistic-Antagonistic Muscle System
Nguyen, Thang; Warner, Holly; La, Hung; Mohammadi, Hanieh; Simon, Dan; Richter, Hanz
2017-01-01
Research on assistive technology, rehabilitation, and prosthesis requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic-antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown input...
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
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
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...... web-cameras for each eye and 6D magnetic sensors allowing free head movements in 3D. Evaluation of initial experiments indicate comparable results to current state-of-the-art on estimating gaze in 3D. Initial results show an RMS error of 39-50 mm in the depth dimension and even smaller...
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.
2012-02-27
... Marine Sanitation Devices (MSDs): No Discharge Zone (NDZ) for California State Marine Waters AGENCY... (EPA) is establishing a No Discharge Zone (NDZ) for marine waters of the State of California for sewage... while the vessel was outside of the marine waters of the State of California, pursuant to Section 312(f...
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)
Improving medical device regulation: the United States and Europe in perspective.
Sorenson, Corinna; Drummond, Michael
2014-03-01
Recent debates and events have brought into question the effectiveness of existing regulatory frameworks for medical devices in the United States and Europe to ensure their performance, safety, and quality. This article provides a comparative analysis of medical device regulation in the two jurisdictions, explores current reforms to improve the existing systems, and discusses additional actions that should be considered to fully meet this aim. Medical device regulation must be improved to safeguard public health and ensure that high-quality and effective technologies reach patients. We explored and analyzed medical device regulatory systems in the United States and Europe in accordance with the available gray and peer-reviewed literature and legislative documents. The two regulatory systems differ in their mandate and orientation, organization, pre- and postmarket evidence requirements, and transparency of process. Despite these differences, both jurisdictions face similar challenges for ensuring that only safe and effective devices reach the market, monitoring real-world use, and exchanging pertinent information on devices with key users such as clinicians and patients. To address these issues, reforms have recently been introduced or debated in the United States and Europe that are principally focused on strengthening regulatory processes, enhancing postmarket regulation through more robust surveillance systems, and improving the traceability and monitoring of devices. Some changes in premarket requirements for devices are being considered. Although the current reforms address some of the outstanding challenges in device regulation, additional steps are needed to improve existing policy. We examine a number of actions to be considered, such as requiring high-quality evidence of benefit for medium- and high-risk devices; moving toward greater centralization and coordination of regulatory approval in Europe; creating links between device identifier systems and
Estimating irrigation water use in the humid eastern 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
Validity of Arm-to-Arm BIA Devices Compared to DXA for Estimating % Fat in College Men and Women.
Rockamann, Rebecca A; Dalton, Emily K; Arabas, Jana L; Jorn, Liz; Mayhew, Jerry L
2017-01-01
Bioelectric impedance analysis (BIA) devices are commonly used to estimate percent body fat (%fat), although validation of their accuracy varies widely. The purpose of this study was to assess the validity of four commonly used BIA devices compared to dual-energy X-ray absorptiometry (DXA). College-aged men (n = 29, age = 19.7 ± 1.2 y, weight = 76.9 ± 12.5 kg) and women (n = 31, age = 20.5 ± 0.8 y, weight = 61.5 ± 9.2 kg) were evaluated for %fat using four single-frequency (50 mHz) BIA devices and DXA. A gender × device repeated measures ANOVA indicated some less expensive BIA devices produced %fat values that were not significantly different from DXA. A thumb-to-thumb BIA device produced the closest values in men (21.9 ± 6.6%) and women (32.1 ± 5.3%) compared to DXA (20.6 ± 6.1% and 30.3 ± 5.4%, respectively). The two more expensive BIA devices significantly underestimated in men (14.7 ± 5.8% and 17.0 ± 5.6%) and women (23.3 ± 4.2% and 23.3 ± 4.2%) compared to DXA. Interclass correlation coefficients with DXA were higher for the more expensive devices in men (ICC = 0.899 and 0.958) than the less expensive devices (ICC = 0.681 and 0.730). In women, all BIA devices showed moderate correlations with DXA (ICC = 0.537 to 0.658). Despite the convenience of simple BIA devices, their use in estimating body composition in young men and women might be questionable due to large variations in the differences between DXA and each device in this study.
On-line, adaptive state estimator for active noise control
Lim, Tae W.
1994-01-01
Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control
State Estimation for Sensor Monitoring System with Uncertainty and Disturbance
Directory of Open Access Journals (Sweden)
Jianhong Sun
2014-10-01
Full Text Available This paper considers the state estimation problem for the sensor monitoring system which contains system uncertainty and nonlinear disturbance. In the sensor monitoring system, states of each inner sensor node usually contains system uncertainty, and external noise often works as nonlinear item. Besides, information transmission in the system is also time consuming. All mentioned above may arouse in unstable of the monitoring system. In this case, states of sensors could be wrongly sampled. Under this circumstance, a proper mathematical model is proposed and by the use of Lipschitz condition, the nonlinear item is transformed to linear one. In addition, we suppose that all sensor nodes are distributed arranged, no interface occurs with each other. By establishing proper Lyapunov– Krasovskii functional, sufficient conditions are acquired by solving linear matrix inequality to make the error augmented system stable, and the gains of observers are also derived. Finally, an illustrated example is given to show that system observed value tracks system states well, which fully demonstrate the effectiveness of our result.
State estimators for tracking sharply-maneuvering ground targets
Visina, Radu S.; Bar-Shalom, Yaakov; Willett, Peter
2017-05-01
This paper presents an algorithm, based on the Interacting Multiple Model Estimator, that can be used to track the state of kinematic point targets, moving in two dimensions, that are capable of making sharp heading maneuvers over short periods of time, such as certain ground vehicles moving in an open field. The targets are capable of up to 60 °/s turn rates, while polar measurements are received at 1 Hz. We introduce the Non-Zero Mean, White Noise Turn-Rate IMM (IMM-WNTR) that consists of 3 modes based on a White Noise Turn Rate (WNTR) kinematic model that contains additive, white, Gaussian turn rate process noises. Two of the modes are considered maneuvering modes, and they have opposite (left/right), non-zero mean turn rate input noise. The need for non-zero mean turn rate process noise is explained, and Monte Carlo simulations compare this novel design to the traditional (single-mode) White Noise Acceleration Kalman Filter (WNA KF) and the two-mode White Noise Acceleration/Nearly-Coordinated Turn Rate IMM (IMM-CT). Results show that the IMM-WNTR filter achieves better accuracy and real-time consistency between expected error and actual error as compared to the (single-mode) WNA KF and the IMM-CT in all simulated scenarios, making it a very accurate state estimator for targets with sharp coordinated turn capability in 2D.
Estimated use of water in the United States in 1970
Murray, Charles Richard; Reeves, E. Bodette
1972-01-01
Estimates of water use in the United States in 1970 indicate that an average of about 370 bgd (billion gallons per day)about 1,800 gallons per capita per day--was withdrawn for the four principal off-channel uses which are (1) public-supply (for domestic, commercial, and industrial uses), (2) rural (domestic and livestock), (3) irrigation, and (4) self-supplied industrial (including thermoelectric power). In 1970, withdrawals for these uses exceeded by 19 percent the 310 bgd estimated for 1965. Increases in the various categories of off-channel water use since 1965 were: approximately 25 percent for self-supplied industry (mainly in electric-utility thermoelectric plants), 13 percent for public supplies, 13 percent for rural supplies, and 8 percent for irrigation. Industrial water withdrawals included 54 bgd of saline water, a 20 percent increase in 5 years. The fifth principal withdrawal use, hydroelectric power (an in-channel use), amounted to 2,800 bgd, a 5-year increase of 22 percent. In computing total withdrawals, recycling within a plant (reuse) is not counted, but withdrawal of the same water by a downstream user (cumulative withdrawals) is counted. The quantity of fresh water consumed--that is, water made unavailable for further possible withdrawal because of evaporation, incorporation in crops and manufactured products, and other causes--was estimated to average 87 bgd for 1970, an increase of about 12 percent since 1965.
Elimination of Thermally Generated Charge in Charged Coupled Devices Using Bayesian Estimator
Directory of Open Access Journals (Sweden)
J. Svihlik
2008-06-01
Full Text Available This paper deals with advanced methods for elimination of thermally generated charge in astronomical images, which were acquired by a Charged Coupled Device (CCD sensor. There exist a number of light images acquired by telescope, which were not corrected by dark frame. The reason is simple: the dark frame doesn't exist, because it was not acquired. This situation may for instance come when sufficient memory space is not available. Correction methods based on the modeling of the light and dark image in the wavelet domain will be discussed. As the model for the dark frame image and for the light image the generalized Laplacian was chosen. The model parameters were estimated using moment method, whereas an extensive measurement on an astronomical camera was proposed and done. This measurement simplifies estimation of the dark frame model parameters. Finally a set of astronomical testing images was corrected and then the objective criteria for an image quality evaluation based on the aperture photometry were applied.
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
Modeling, State Estimation and Control of Unmanned Helicopters
Lau, Tak Kit
Unmanned helicopters hold both tremendous potential and challenges. Without risking the lives of human pilots, these vehicles exhibit agile movement and the ability to hover and hence open up a wide range of applications in the hazardous situations. Sparing human lives, however, comes at a stiff price for technology. Some of the key difficulties that arise in these challenges are: (i) There are unexplained cross-coupled responses between the control axes on the hingeless helicopters that have puzzled researchers for years. (ii) Most, if not all, navigation on the unmanned helicopters relies on Global Navigation Satellite Systems (GNSSs), which are susceptible to jamming. (iii) It is often necessary to accommodate the re-configurations of the payload or the actuators on the helicopters by repeatedly tuning an autopilot, and that requires intensive human supervision and/or system identification. For the dynamics modeling and analysis, we present a comprehensive review on the helicopter actuation and dynamics, and contributes toward a more complete understanding on the on-axis and off-axis dynamical responses on the helicopter. We focus on a commonly used modeling technique, namely the phase-lag treatment, and employ a first-principles modeling method to justify that (i) why that phase-lag technique is inaccurate, (ii) how we can analyze the helicopter actuation and dynamics more accurately. Moreover, these dynamics modeling and analysis reveal the hard-to-measure but crucial parameters on a helicopter model that require the constant identifications, and hence convey the reasoning of seeking a model-implicit method to solve the state estimation and control problems on the unmanned helicopters. For the state estimation, we present a robust localization method for the unmanned helicopter against the GNSS outage. This method infers position from the acceleration measurement from an inertial measurement unit (IMU). In the core of our method are techniques of the sensor
Remaining lifetime modeling using State-of-Health estimation
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
Estimated Use of Water in the United States in 1985
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
Energy Technology Data Exchange (ETDEWEB)
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.
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.
National Aeronautics and Space Administration — Recent work has developed a number of architectures and algorithms for accurately estimating spacecraft and formation states. The estimation accuracy achievable...
Parameter and state estimation in nonlinear dynamical systems
Creveling, Daniel R.
This thesis is concerned with the problem of state and parameter estimation in nonlinear systems. The need to evaluate unknown parameters in models of nonlinear physical, biophysical and engineering systems occurs throughout the development of phenomenological or reduced models of dynamics. When verifying and validating these models, it is important to incorporate information from observations in an efficient manner. Using the idea of synchronization of nonlinear dynamical systems, this thesis develops a framework for presenting data to a candidate model of a physical process in a way that makes efficient use of the measured data while allowing for estimation of the unknown parameters in the model. The approach presented here builds on existing work that uses synchronization as a tool for parameter estimation. Some critical issues of stability in that work are addressed and a practical framework is developed for overcoming these difficulties. The central issue is the choice of coupling strength between the model and data. If the coupling is too strong, the model will reproduce the measured data regardless of the adequacy of the model or correctness of the parameters. If the coupling is too weak, nonlinearities in the dynamics could lead to complex dynamics rendering any cost function comparing the model to the data inadequate for the determination of model parameters. Two methods are introduced which seek to balance the need for coupling with the desire to allow the model to evolve in its natural manner without coupling. One method, 'balanced' synchronization, adds to the synchronization cost function a requirement that the conditional Lyapunov exponents of the model system, conditioned on being driven by the data, remain negative but small in magnitude. Another method allows the coupling between the data and the model to vary in time according to a specific form of differential equation. The coupling dynamics is damped to allow for a tendency toward zero coupling
Li, Judith Yue; Kokkinaki, Amalia; Ghorbanidehno, Hojat; Darve, Eric F.; Kitanidis, Peter K.
2015-12-01
Reservoir monitoring aims to provide snapshots of reservoir conditions and their uncertainties to assist operation management and risk analysis. These snapshots may contain millions of state variables, e.g., pressures and saturations, which can be estimated by assimilating data in real time using the Kalman filter (KF). However, the KF has a computational cost that scales quadratically with the number of unknowns, m, due to the cost of computing and storing the covariance and Jacobian matrices, along with their products. The compressed state Kalman filter (CSKF) adapts the KF for solving large-scale monitoring problems. The CSKF uses N preselected orthogonal bases to compute an accurate rank-N approximation of the covariance that is close to the optimal spectral approximation given by SVD. The CSKF has a computational cost that scales linearly in m and uses an efficient matrix-free approach that propagates uncertainties using N + 1 forward model evaluations, where N≪m. Here we present a generalized CSKF algorithm for nonlinear state estimation problems such as CO2 monitoring. For simultaneous estimation of multiple types of state variables, the algorithm allows selecting bases that represent the variability of each state type. Through synthetic numerical experiments of CO2 monitoring, we show that the CSKF can reproduce the Kalman gain accurately even for large compression ratios (m/N). For a given computational cost, the CSKF uses a robust and flexible compression scheme that gives more reliable uncertainty estimates than the ensemble Kalman filter, which may display loss of ensemble variability leading to suboptimal uncertainty estimates.
Estimated use of water in the United States - 1950
MacKichan, Kenneth Allen
1951-01-01
An estimated 170,000 million gallons of water was withdrawn from the ground, lakes, or streams each day on the average during 1950 and used on the farms and in the homes, factories, and business establishments of the United States. An additional 1,100,000 million gallons per day was used to generate hydro-power. Water power is the largest user of water; however, irrigation and industry also are large users of both ground and surface water. More surface water was used for industrial purposes than for irrigation, whereas more ground water was used for irrigation than for industrial purposes (fig. 1). The total withdrawal of surface water was considerably in excess of ground-water withdrawal, as shown by figure 1. Large quantities of water were used also for purposes requiring no diversion, such as navigation, waste disposal, recreation, and support of wildlife.
Chapter 16 - Predictive Analytics for Comprehensive Energy Systems State Estimation
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yang, Rui [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Jie [University of Texas at Dallas; Weng, Yang [Arizona State University
2017-12-01
Energy sustainability is a subject of concern to many nations in the modern world. It is critical for electric power systems to diversify energy supply to include systems with different physical characteristics, such as wind energy, solar energy, electrochemical energy storage, thermal storage, bio-energy systems, geothermal, and ocean energy. Each system has its own range of control variables and targets. To be able to operate such a complex energy system, big-data analytics become critical to achieve the goal of predicting energy supplies and consumption patterns, assessing system operation conditions, and estimating system states - all providing situational awareness to power system operators. This chapter presents data analytics and machine learning-based approaches to enable predictive situational awareness of the power systems.
State-Estimation Algorithm Based on Computer Vision
Bayard, David; Brugarolas, Paul
2007-01-01
An algorithm and software to implement the algorithm are being developed as means to estimate the state (that is, the position and velocity) of an autonomous vehicle, relative to a visible nearby target object, to provide guidance for maneuvering the vehicle. In the original intended application, the autonomous vehicle would be a spacecraft and the nearby object would be a small astronomical body (typically, a comet or asteroid) to be explored by the spacecraft. The algorithm could also be used on Earth in analogous applications -- for example, for guiding underwater robots near such objects of interest as sunken ships, mineral deposits, or submerged mines. It is assumed that the robot would be equipped with a vision system that would include one or more electronic cameras, image-digitizing circuitry, and an imagedata- processing computer that would generate feature-recognition data products.
Estimated use of water in the United States in 2010
Maupin, Molly A.; Kenny, Joan F.; Hutson, Susan S.; Lovelace, John K.; Barber, Nancy L.; Linsey, Kristin S.
2014-01-01
Water use in the United States in 2010 was estimated to be about 355 billion gallons per day (Bgal/d), which was 13 percent less than in 2005. The 2010 estimates put total withdrawals at the lowest level since before 1970. Freshwater withdrawals were 306 Bgal/d, or 86 percent of total withdrawals, and saline-water withdrawals were 48.3 Bgal/d, or 14 percent of total withdrawals. Fresh surface-water withdrawals (230 Bgal/d) were almost 15 percent less than in 2005, and fresh groundwater withdrawals (76.0 Bgal/d) were about 4 percent less than in 2005. Saline surface-water withdrawals were 45.0 Bgal/d, or 24 percent less than in 2005. Updates to the 2005 saline groundwater withdrawals, mostly for thermoelectric power, reduced total saline groundwater withdrawals to 1.51 Bgal/d, down from the originally reported 3.02 Bgal/d. Total saline groundwater withdrawals in 2010 were 3.29 Bgal/d, mostly for mining use.
INTERVAL STATE ESTIMATION FOR SINGULAR DIFFERENTIAL EQUATION SYSTEMS WITH DELAYS
Directory of Open Access Journals (Sweden)
T. A. Kharkovskaia
2016-07-01
Full Text Available The paper deals with linear differential equation systems with algebraic restrictions (singular systems and a method of interval observer design for this kind of systems. The systems contain constant time delay, measurement noise and disturbances. Interval observer synthesis is based on monotone and cooperative systems technique, linear matrix inequations, Lyapunov function theory and interval arithmetic. The set of conditions that gives the possibility for interval observer synthesis is proposed. Results of synthesized observer operation are shown on the example of dynamical interindustry balance model. The advantages of proposed method are that it is adapted to observer design for uncertain systems, if the intervals of admissible values for uncertain parameters are given. The designed observer is capable to provide asymptotically definite limits on the estimation accuracy, since the interval of admissible values for the object state is defined at every instant. The obtained result provides an opportunity to develop the interval estimation theory for complex systems that contain parametric uncertainty, varying delay and nonlinear elements. Interval observers increasingly find applications in economics, electrical engineering, mechanical systems with constraints and optimal flow control.
An application to estimate the cyber-risk detection skill of mobile device users
Schaff, Guillaume; Harpes, Carlo; Martin, Romain; Junger, Marianne; Berntzen, Lasse; Böhm, Stephan
2013-01-01
According to experts’ predictions, mobile devices (smartphones, tablet computers) will replace the widespread personal computer by 2017 for personal and work tasks (emergence of BYOD). In parallel, the expert community has observed an increase of cyber-attacks against mobile devices. Mobile device
Kumar, Rajesh; Pillai, Rajesh G; Pekas, Nikola; Wu, Yiliang; McCreery, Richard L
2012-09-12
A three terminal molecular memory device was monitored with in situ Raman spectroscopy during bias-induced switching between two metastable states having different conductivity. The device structure is similar to that of a polythiophene field effect transistor, but ethylviologen perchlorate was added to provide a redox counter-reaction to accompany polythiophene redox reactions. The conductivity of the polythiophene layer was reversibly switched between high and low conductance states with a "write/erase" (W/E) bias, while a separate readout circuit monitored the polymer conductance. Raman spectroscopy revealed reversible polythiophene oxidation to its polaron form accompanied by a one-electron viologen reduction. "Write", "read", and "erase" operations were repeatable, with only minor degradation of response after 200 W/E cycles. The devices exhibited switching immediately after fabrication and did not require an "electroforming" step required in many types of memory devices. Spatially resolved Raman spectroscopy revealed polaron formation throughout the polymer layer, even away from the electrodes in the channel and drain regions, indicating that thiophene oxidation "propagates" by growth of the conducting polaron form away from the source electrode. The results definitively demonstrate concurrent redox reactions of both polythiophene and viologen in solid-state devices and correlate such reactions with device conductivity. The mechanism deduced from spectroscopic and electronic monitoring should guide significant improvements in memory performance.
Using support vector machines in the multivariate state estimation technique
International Nuclear Information System (INIS)
Zavaljevski, N.; Gross, K.C.
1999-01-01
One approach to validate nuclear power plant (NPP) signals makes use of pattern recognition techniques. This approach often assumes that there is a set of signal prototypes that are continuously compared with the actual sensor signals. These signal prototypes are often computed based on empirical models with little or no knowledge about physical processes. A common problem of all data-based models is their limited ability to make predictions on the basis of available training data. Another problem is related to suboptimal training algorithms. Both of these potential shortcomings with conventional approaches to signal validation and sensor operability validation are successfully resolved by adopting a recently proposed learning paradigm called the support vector machine (SVM). The work presented here is a novel application of SVM for data-based modeling of system state variables in an NPP, integrated with a nonlinear, nonparametric technique called the multivariate state estimation technique (MSET), an algorithm developed at Argonne National Laboratory for a wide range of nuclear plant applications
Pipeline heating method based on optimal control and state estimation
Energy Technology Data Exchange (ETDEWEB)
Vianna, F.L.V. [Dept. of Subsea Technology. Petrobras Research and Development Center - CENPES, Rio de Janeiro, RJ (Brazil)], e-mail: fvianna@petrobras.com.br; Orlande, H.R.B. [Dept. of Mechanical Engineering. POLI/COPPE, Federal University of Rio de Janeiro - UFRJ, Rio de Janeiro, RJ (Brazil)], e-mail: helcio@mecanica.ufrj.br; Dulikravich, G.S. [Dept. of Mechanical and Materials Engineering. Florida International University - FIU, Miami, FL (United States)], e-mail: dulikrav@fiu.edu
2010-07-01
In production of oil and gas wells in deep waters the flowing of hydrocarbon through pipeline is a challenging problem. This environment presents high hydrostatic pressures and low sea bed temperatures, which can favor the formation of solid deposits that in critical operating conditions, as unplanned shutdown conditions, may result in a pipeline blockage and consequently incur in large financial losses. There are different methods to protect the system, but nowadays thermal insulation and chemical injection are the standard solutions normally used. An alternative method of flow assurance is to heat the pipeline. This concept, which is known as active heating system, aims at heating the produced fluid temperature above a safe reference level in order to avoid the formation of solid deposits. The objective of this paper is to introduce a Bayesian statistical approach for the state estimation problem, in which the state variables are considered as the transient temperatures within a pipeline cross-section, and to use the optimal control theory as a design tool for a typical heating system during a simulated shutdown condition. An application example is presented to illustrate how Bayesian filters can be used to reconstruct the temperature field from temperature measurements supposedly available on the external surface of the pipeline. The temperatures predicted with the Bayesian filter are then utilized in a control approach for a heating system used to maintain the temperature within the pipeline above the critical temperature of formation of solid deposits. The physical problem consists of a pipeline cross section represented by a circular domain with four points over the pipe wall representing heating cables. The fluid is considered stagnant, homogeneous, isotropic and with constant thermo-physical properties. The mathematical formulation governing the direct problem was solved with the finite volume method and for the solution of the state estimation problem
Joint parameter and state estimation algorithms for real-time traffic monitoring.
2013-12-01
A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...
Full State Estimation for Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon
coordinate formulation and can be used to model all body to body slung load suspension systems. Both estimators include bias estimation for the accelerometers and gyros and the model based estimator furthermore includes estimation of external wind disturbances. A vision system is used to measure the motion...
Full State Estimation for Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon
2007-01-01
coordinate formulation and can be used to model all body to body slung load suspension systems. Both estimators include bias estimation for the accelerometers and gyros and the model based estimator furthermore includes estimation of external wind disturbances. A vision system is used to measure the motion...
Sommerstein, Rami; Hasse, Barbara; Marschall, Jonas; Sax, Hugo; Genoni, Michele; Schlegel, Matthias; Widmer, Andreas F
2018-03-01
Investigations of a worldwide epidemic of invasive Mycobacterium chimaera associated with heater-cooler devices in cardiac surgery have been hampered by low clinical awareness and challenging diagnoses. Using data from Switzerland, we estimated the burden of invasive M. chimaera to be 156-282 cases/year in 10 major cardiac valve replacement market countries.
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…
Estimating the ground-state probability of a quantum simulation with product-state measurements
Directory of Open Access Journals (Sweden)
Bryce eYoshimura
2015-10-01
Full Text Available .One of the goals in quantum simulation is to adiabatically generate the ground state of a complicated Hamiltonian by starting with the ground state of a simple Hamiltonian and slowly evolving the system to the complicated one. If the evolution is adiabatic and the initial and final ground states are connected due to having the same symmetry, then the simulation will be successful. But in most experiments, adiabatic simulation is not possible because it would take too long, and the system has some level of diabatic excitation. In this work, we quantify the extent of the diabatic excitation even if we do not know {it a priori} what the complicated ground state is. Since many quantum simulator platforms, like trapped ions, can measure the probabilities to be in a product state, we describe techniques that can employ these simple measurements to estimate the probability of being in the ground state of the system after the diabatic evolution. These techniques do not require one to know any properties about the Hamiltonian itself, nor to calculate its eigenstate properties. All the information is derived by analyzing the product-state measurements as functions of time.
Nonlinear State Estimation and Modeling of a Helicopter UAV
Barczyk, Martin
Experimentally-validated nonlinear flight control of a helicopter UAV has two necessary conditions: an estimate of the vehicle’s states from noisy multirate output measurements, and a nonlinear dynamics model with minimum complexity, physically controllable inputs and experimentally identified parameter values. This thesis addresses both these objectives for the Applied Nonlinear Controls Lab (ANCL)'s helicopter UAV project. A magnetometer-plus-GPS aided Inertial Navigation System (INS) for outdoor flight as well as an Attitude and Heading Reference System (AHRS) for indoor testing are designed, implemented and experimentally validated employing an Extended Kalman Filter (EKF), using a novel calibration technique for the magnetometer aiding sensor added to remove the limitations of an earlier GPS-only aiding design. Next the recently-developed nonlinear observer design methodology of invariant observers is adapted to the aided INS and AHRS examples, employing a rotation matrix representation for the state manifold to obtain designs amenable to global stability analysis, obtaining a direct nonlinear design for gains of the AHRS observer, modifying the previously-proposed Invariant EKF systematic method for computing gains, and culminating in simulation and experimental validation of the observers. Lastly a nonlinear control-oriented model of the helicopter UAV is derived from first principles, using a rigid-body dynamics formulation augmented with models of the on-board subsystems: main rotor forces and blade flapping dynamics, the Bell-Hiller system and flybar flapping dynamics, tail rotor forces, tail gyro unit, engine and rotor speed, servo operation, fuselage drag, and tail stabilizer forces. The parameter values in the resulting models are identified experimentally. Using these the model is further simplified to be tractable for model-based control design.
Estimation of malaria transmission intensity in Sennar state, central Sudan.
Elmahdi, Z A; Nugud, A A; Elhassan, I M
2012-09-01
Understanding the behaviour of malaria vectors is crucial for planning mosquito control programmes. The aim of this study was to estimate the malaria transmission intensity in 2 different ecological zones in a highly endemic malaria area of Sennar state in central Sudan over the main transmission period. Species confirmation by PCR indicated that Anopheles arabiensis was the only malaria vector in the study area, with high anthropophilic behaviour (84.9% human-feeding). ELISA studies showed Plasmodium falciparum sporozoite rates rose from 1.8% to 4.5% and the average entomological inoculation rates rose from 2.4 to 4.2 infectious bites per person per night in September (the beginning) to November (the end) of the 3-month transmission season. The proportion of malaria-positive slides ranged from 50.1% to 57.0%. The proportion of human-blood positive mosquitoes was significantly higher in the irrigated area (El Booster) compared with the non-irrigated area (Rahal).
National scale biomass estimators for United States tree species
Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey
2003-01-01
Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...
Estimated withdrawals from principal aquifers in the United States, 2000
Maupin, Molly A.; Barber, Nancy L.
2005-01-01
Fresh ground-water withdrawals from 66 principal aquifers in the United States were estimated for irrigation, public-supply, and self-supplied industrial water uses for the year 2000. Total ground-water withdrawals were 76,500 million gallons per day, or 85,800 thousand acre-feet per year for these three uses. Irrigation used the largest amount of ground water, 56,900 million gallons per day, followed by public supply with 16,000 million gallons per day, and self-supplied industrial with 3,570 million gallons per day. These three water uses represented 92 percent of the fresh groundwater withdrawals for all uses in the United States, the remaining 8 percent included self-supplied domestic, aquaculture, livestock, mining, and thermoelectric power uses. Aquifer withdrawals were categorized by five lithologic groups: unconsolidated and semiconsolidated sand and gravel aquifers, carbonate-rock aquifers, igneous and metamorphic-rock aquifers, sandstone aquifers, and sandstone and carbonate-rock aquifers. Withdrawals from aquifers that were not included in one of the 66 principal aquifers were reported in an “Other” aquifers group. The largest withdrawals in the United States were from unconsolidated and semiconsolidated sand and gravel aquifers, which accounted for 80 percent of total withdrawals from all aquifers. Carbonate-rock aquifers provided 8 percent of the withdrawals, and igneous and metamorphic-rock aquifers, 6 percent. Withdrawals from sandstone aquifers, from sandstone and carbonate-rock aquifers, and from the “Other” aquifers category each constituted about 2 percent of the total withdrawals reported.Fifty-five percent of the total withdrawals for irrigation, public-supply, and self-supplied industrial water uses were provided by the High Plains aquifer, California Central Valley aquifer system, the Mississippi River Valley alluvial aquifer, and the Basin and Range basin-fill aquifers. These aquifers provided most of the withdrawals for irrigation
Students' Beliefs about Mobile Devices vs. Desktop Computers in South Korea and the 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…
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.
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
Directory of Open Access Journals (Sweden)
O. V. Murav’eva
2017-01-01
Full Text Available Measuring the characteristics of process fluids allows us to evaluate their quality, biological tissues – to differentiate healthy tissues and tissues with pathologies. Measuring the characteristics of process fluids allows us to evaluate their quality, biological tissues – to differentiate healthy tissues and tissues with pathologies. One of the complex acoustic parameters is the impedance, which allows one to fully evaluate the characteristics of viscoelastic media. Most of impedance methods of measurements require using two or more reference media and the availability of calibrated acoustic transducers. The aim of this work ware introduced a methods and construction for the experimental evaluation of the longitudinal and shear impedance of viscoelastic media based on measuring the parameters of the amplitude-frequency characteristics and calculating the elements of the electric circuit for replacing the piezoelectric element which vibrating in the test medium.The paper introduces a methods and construction of the experimental evaluation of the impedances of viscoelastic media. The suggested methods is allowed measuring longitudinal and shear impedances and determining velocities of longitudinal and transverse ultrasonic waves and the values of the elastic moduli of viscoelastic media, including in various aggregate states. The technique is fairly simple to implement and can be reproduced using simple laboratory equipment.The obtained values of the acoustic impedances of the investigated media are in satisfactory agreement with their reference data. In contrast to the known methods for determining the acoustic impedance, the developed technique allows us to estimate with sufficient accuracy the parameter of the shear impedance of viscoelastic media that is difficult to measure at the frequencies of the megahertz range, which determines the shear modulus of the material and characterizes its resistance to shear deformations. The results of
Distribution system intelligent state estimation through minimal meter placement
Energy Technology Data Exchange (ETDEWEB)
Ramesh, L. [Jadavpur Univ., Kolkata (India). Dept. of Electrical Engineering; Chowdhury, S.; Chowdhury, S.P.; Gaunt, C.T. [Cape Town Univ. (South Africa)
2009-03-11
A method of accurately estimating electrical parameters for distribution automation systems in power distribution networks was presented. A particle swarm optimization (PSO) algorithm was used to identify meter locations as well as to monitor and estimate parameters in the distribution system. The determined locations were then used to monitor and estimate parameters using a SCADA system arrangement. Parameter values were estimated using a hybrid artificial neural network (ANN) based estimation technique where pseudo-measurements were injected at un-metered buses. An Institute of Electrical and Electronic Engineers (IEEE) 13-node system with a distribution system used by the Tamil Nadu Electrical Board in India was used to verify the method. Results of the study showed that the proposed algorithm can be used to accurately estimate the electrical parameters of distribution automation systems. The method will be used to determine the position of future switch position and transformer locations. 22 refs., 1 tab., 6 figs.
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 representative milk samples compared with devices used by certified milk recording providers on farms with conventional milking systems (CMS) and (2) devices used on both AMS and CMS comply with accuracy crite...
Electric-field enhanced performance in catalysis and solid-state devices involving gases
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.
Exploratory Study of the State of Environmentally Conscious Design in the Medical Device Industry
DEFF Research Database (Denmark)
Moultrie, James; Sutcliffe, L.; Maier, Anja
2015-01-01
This exploratory study seeks to explore the current state of design for the environment (DfE) in the development of medical devices; an historically risk averse industry that lags behind others in terms of addressing environmental considerations. A cross-sectional survey of 34 medical device...... designers, primarily in the UK and USA, was conducted in order to fulfil this objective. Findings indicate that there is significant motivation to enhance DfE practice, but that there are multiple barriers to this. Major barriers identified are a perception of the high cost of DfE, the industry’s current...
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
Particle filter based MAP state estimation: A comparison
Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha
2009-01-01
MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi
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)
Coupling Resistive Switching Devices with Neurons: State of the Art and Perspectives.
Chiolerio, Alessandro; Chiappalone, Michela; Ariano, Paolo; Bocchini, Sergio
2017-01-01
Here we provide the state-of-the-art of bioelectronic interfacing between biological neuronal systems and artificial components, focusing the attention on the potentiality offered by intrinsically neuromorphic synthetic devices based on Resistive Switching (RS). Neuromorphic engineering is outside the scopes of this Perspective. Instead, our focus is on those materials and devices featuring genuine physical effects that could be sought as non-linearity, plasticity, excitation, and extinction which could be directly and more naturally coupled with living biological systems. In view of important applications, such as prosthetics and future life augmentation, a cybernetic parallelism is traced, between biological and artificial systems. We will discuss how such intrinsic features could reduce the complexity of conditioning networks for a more natural direct connection between biological and synthetic worlds. Putting together living systems with RS devices could represent a feasible though innovative perspective for the future of bionics.
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.
A flexible super-capacitive solid-state power supply for miniature implantable medical devices.
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.
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 cheap...... of an interview with questions regarding the functionality of the tangible widgets. The results show that using two devices is significantly better at inducing the illusion of internal state....
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. PMID:25429243
Optimal state estimation over communication channels with random delays
Mahmoud, Magdi S.
2013-04-01
This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node stores the sum of arrived measurements between two adjacent processing time instants and also counts the number of arrived measurements. The original linear system is modeled as an extended system with uncertain observation to capture the feature of communication, then the optimal estimation algorithm of systems with uncertain observations is proposed. Additionally, a numerical simulation is presented to show the performance of this work. © 2013 The Franklin Institute.
Estimates of the Resident Nonimmigrant Population in the United States: 2008
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...
Multi-party Measurement-Device-Independent Quantum Key Distribution Based on Cluster 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.
Multi-party Measurement-Device-Independent Quantum Key Distribution Based on Cluster States
Liu, Chuanqi; Zhu, Changhua; Ma, Shuquan; Pei, Changxing
2017-12-01
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.
Analysis of field usage failure rate data for plastic encapsulated solid state devices
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.
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...
Estimating mental states of a depressed person with bayesian networks
Klein, Michel C.A.; Modena, Gabriele
2013-01-01
In this work in progress paper we present an approach based on Bayesian Networks to model the relationship between mental states and empirical observations in a depressed person. We encode relationships and domain expertise as a Hierarchical Bayesian Network. Mental states are represented as latent
Estimation of Overtopping Rates on Slopes in Wave Power Devices and Other Low Crested Structures
DEFF Research Database (Denmark)
Kofoed, Jens Peter; Burcharth, Hans Falk
2002-01-01
Motivated by questions raised by developers of wave energy devices based on wave overtopping concepts, model tests have been performed to study overtopping of structures with limited draught, low crest freeboards and slope geometries designed to increase overtopping and thereby also the captured ...
DEFF Research Database (Denmark)
Valenzuela, Reuben M; Rai, Ruju; Kirk, Brian H
2017-01-01
Because of a previous association of pseudotumor cerebri (PTC) with levonorgestrel, we wished to evaluate the use of levonorgestrel-eluting intrauterine devices ("levonorgestrel intrauterine systems", LNG-IUS) in our University of Utah and Rigshospitalet PTC patients. In our retrospective series...
International Nuclear Information System (INIS)
2015-01-01
This meeting has provided an appropriate forum to discuss current issues covering a wide range of technical topics related to the steady state operation issues and also to encourage forecast of the ITER performances. The technical meeting includes invited and contributed papers. The topics that have been dealt with are: 1) Superconducting devices (ITER, KSTAR, Tore-Supra, HT-7U, EAST, LHD, Wendelstein-7-X,...); 2) Long-pulse operation and advanced tokamak physics; 3) steady state fusion technologies; 4) Long pulse heating and current drive; 5) Particle control and power exhaust, and 6) ITER-related research and development issues. This document gathers the abstracts
Event-based state estimation a stochastic perspective
Shi, Dawei; Chen, Tongwen
2016-01-01
This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs ...
Response-Based Estimation of Sea State Parameters
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam
2007-01-01
of measured ship responses. It is therefore interesting to investigate how the filtering aspect, introduced by FRF, affects the final outcome of the estimation procedures. The paper contains a study based on numerical generated time series, and the study shows that filtering has an influence...... calculated by a 3-D time domain code and by closed-form (analytical) expressions, respectively. Based on comparisons with wave radar measurements and satellite measurements it is seen that the wave estimations based on closedform expressions exhibit a reasonable energy content, but the distribution of energy...
Guide to preemption of state-law claims against Class III PMA medical devices.
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.
State Estimates of Adolescent Cigarette Use and Perceptions of Risk of Smoking: 2012 and 2013
... Short Report May 18, 2015 STATE ESTIMATES OF ADOLESCENT CIGARETTE USE AND PERCEPTIONS OF RISK OF SMOKING: ... on our nation and its states. 3 Preventing adolescents from starting to smoke may be the most ...
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.
On algebraic time-derivative estimation and deadbeat state reconstruction
DEFF Research Database (Denmark)
Reger, Johann; Jouffroy, Jerome
2009-01-01
This paper places into perspective the so-called algebraic time-derivative estimation method recently introduced by Fliess and co-authors with standard results from linear statespace theory for control systems. In particular, it is shown that the algebraic method can essentially be seen...
State of the Art in Photon-Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Georgiev, Iliyan
2013-01-01
Photon-density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface sc...
State of the Art in Photon Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Bouchard, Guillaume
2012-01-01
Photon-density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface sc...
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
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.
Charge Transfer and Triplet States in High Efficiency OPV Materials and Devices
Dyakonov, Vladimir
2013-03-01
The advantage of using polymers and molecules in electronic devices, such as light-emitting diodes (LED), field-effect transistors (FET) and, more recently, solar cells (SC) is justified by the unique combination of high device performance and processing of the semiconductors used. Power conversion efficiency of nanostructured polymer SC is in the range of 10% on lab scale, making them ready for up-scaling. Efficient charge carrier generation and recombination in SC are strongly related to dissociation of the primary singlet excitons. The dissociation (or charge transfer) process should be very efficient in photovoltaics. The mechanisms governing charge carrier generation, recombination and transport in SC based on the so-called bulk-heterojunctions, i.e. blends of two or more semiconductors with different electron affinities, appear to be very complex, as they imply the presence of the intermediate excited states, neutral and charged ones. Charge transfer states, or polaron pairs, are the intermediate states between free electrons/holes and strongly bound excitons. Interestingly, the mostly efficient OLEDs to date are based on the so-called triplet emitters, which utilize the triplet-triplet annihilation process. In SC, recent investigations indicated that on illumination of the device active layer, not only mobile charges but also triplet states were formed. With respect to triplets, it is unclear how these excited states are generated, via inter-system crossing or via back transfer of the electron from acceptor to donor. Triplet formation may be considered as charge carrier loss channel; however, the fusion of two triplets may lead to a formation of singlet excitons instead. In such case, a generation of charges by utilizing of the so far unused photons will be possible. The fundamental understanding of the processes involving the charge transfer and triplet states and their relation to nanoscale morphology and/or energetics of blends is essential for the
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.
Dip-Coating Process Engineering and Performance Optimization for Three-State Electrochromic Devices
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.
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.
Rankings & Estimates: Rankings of the States 2016 and Estimates of School Statistics 2017
National Education Association, 2017
2017-01-01
The data presented in this combined report provide facts about the extent to which local, state, and national governments commit resources to public education. NEA Research offers this report to its state and local affiliates as well as to researchers, policymakers, and the public as a tool to examine public education policies, programs, and…
State of the art on wind resource estimation
Energy Technology Data Exchange (ETDEWEB)
Maribo Pedersen, B.
1998-12-31
With the increasing number of wind resource estimation studies carried out for regions, countries and even larger areas all over the world, the IEA finds that the time has come to stop and take stock of the various methods used in these studies. The IEA would therefore like to propose an Experts Meeting on wind resource estimation. The Experts Meeting should describe the models and databases used in the various studies. It should shed light on the strengths and shortcomings of the models and answer questions like: where and under what circumstances should a specific model be used? what is the expected accuracy of the estimate of the model? and what is the applicability? When addressing databases the main goal will be to identify the content and scope of these. Further, the quality, availability and reliability of the databases must also be recognised. In the various studies of wind resources the models and databases have been combined in different ways. A final goal of the Experts Meeting is to see whether it is possible to develop systems of methods which would depend on the available input. These systems of methods should be able to address the simple case (level 0) of a region with barely no data, to the complex case of a region with all available measurements: surface observations, radio soundings, satellite observations and so on. The outcome of the meeting should be an inventory of available models as well as databases and a map of already studied regions. (au)
FISH PRODUCTION ESTIMATES FOR GBEDIKERE LAKE, BASSA, KOGI STATE, NIGERIA
Directory of Open Access Journals (Sweden)
Samuel Olusegun Adeyemi
2013-10-01
Full Text Available Annual estimates of the fish caught by local fishermen in randomly selected fishing villages adjacent to Gbedikere Lake were determined using Catch Assessment (CAS. The studies were carried out within two seasons of low water (February and high water (September periods between 2006 to 2008. Annual fish catch varied from 537.4 mts to 576.9 mts at high water. Mean catch per boat ranged from 7.40 kg to 10.60 kg among the landing sites. A total of 12 fish species were identified belonging to ten families. The catches were dominated by the cichlids with Orechromis niloticus dominating the overall catch compositions. Production estimate was compared with the catches obtained through experimental gill-net sampling and potential fish yield estimates using Ryder’s Morpho - Edaphic Index (MEI as modified by Henderson and Welcomme (1974. Contributions of the gears in use were also done with cast nets ranking above others (29%, followed by the set net (25%, hook and lines (16.6%, traps (16.6%, clap net (8.3%. Management measures were suggested.
Estimation of health state utilities in breast cancer
Directory of Open Access Journals (Sweden)
Kim SH
2017-03-01
Full Text Available Seon-Ha Kim,1 Min-Woo Jo,2 Minsu Ock,2 Hyeon-Jeong Lee,2 Jong-Won Lee3,4 1Department of Nursing, College of Nursing, Dankook University, Cheonan, 2Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, 3Department of Breast and Endocrine Surgery, Asan Medical Center, Seoul, 4Department of Surgery, University of Ulsan College of Medicine, Seoul, South Korea Purpose: The aim of this study is to determine the utility of breast cancer health states using the standard gamble (SG and visual analog scale (VAS methods in the Korean general population.Materials and methods: Eight hypothetical breast cancer health states were developed based on patient education material and previous publications. Data from 509 individuals from the Korean general population were used to evaluate breast cancer health states using the VAS and the SG methods, which were obtained via computer-assisted personal interviews. Mean utility values were calculated for each human papillomavirus (HPV-related health state.Results: The rank of health states was identical between two valuation methods. SG values were higher than VAS values in all health states. The utility values derived from SG were 0.801 (noninvasive breast cancer with mastectomy and followed by reconstruction, 0.790 (noninvasive breast cancer with mastectomy only, 0.779 (noninvasive breast cancer with breast-conserving surgery and radiation therapy, 0.731 (invasive breast cancer with surgery, radiation therapy, and/or chemotherapy, 0.610 (locally advanced breast cancer with radical mastectomy with radiation therapy, 0.587 (inoperable locally advanced breast cancer, 0.496 (loco-regional recurrent breast cancer, and 0.352 (metastatic breast cancer.Conclusion: Our findings might be useful for economic evaluation of breast cancer screening and interventions in general populations. Keywords: breast neoplasm, Korea, quality-adjusted life years, quality of life
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.
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
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
Detection and analysis of bad data is an important sector of the static state estimation. This paper addresses single and multiple bad data in the modern phasor measurement unit (PMU)-based power system static state estimations. To accomplish this objective, available approaches in the PMU-based ...
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...
Improving the accuracy of estimation of eutrophication state index ...
African Journals Online (AJOL)
Trophic Level Index (TLI) is oen used to assess the general eutrophication state of inland lakes in water science, technology, and engineering. In this paper, a data-driven inland-lake eutrophication assessment method was proposed by using an articial neural network (ANN) to build relationships from remote sensing data ...
Attia, A; Dhahbi, W; Chaouachi, A; Padulo, J; Wong, D P; Chamari, K
2017-03-01
Common methods to estimate vertical jump height (VJH) are based on the measurements of flight time (FT) or vertical reaction force. This study aimed to assess the measurement errors when estimating the VJH with flight time using photocell devices in comparison with the gold standard jump height measured by a force plate (FP). The second purpose was to determine the intrinsic reliability of the Optojump photoelectric cells in estimating VJH. For this aim, 20 subjects (age: 22.50±1.24 years) performed maximal vertical jumps in three modalities in randomized order: the squat jump (SJ), counter-movement jump (CMJ), and CMJ with arm swing (CMJarm). Each trial was simultaneously recorded by the FP and Optojump devices. High intra-class correlation coefficients (ICCs) for validity (0.98-0.99) and low limits of agreement (less than 1.4 cm) were found; even a systematic difference in jump height was consistently observed between FT and double integration of force methods (-31% to -27%; p1.2). Intra-session reliability of Optojump was excellent, with ICCs ranging from 0.98 to 0.99, low coefficients of variation (3.98%), and low standard errors of measurement (0.8 cm). It was concluded that there was a high correlation between the two methods to estimate the vertical jump height, but the FT method cannot replace the gold standard, due to the large systematic bias. According to our results, the equations of each of the three jump modalities were presented in order to obtain a better estimation of the jump height.
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.
Estimated prevalence of compulsive buying behavior in the United States.
Koran, Lorrin M; Faber, Ronald J; Aboujaoude, Elias; Large, Michael D; Serpe, Richard T
2006-10-01
Compulsive buying (uncontrolled urges to buy, with resulting significant adverse consequences) has been estimated to affect from 1.8% to 16% of the adult U.S. population. To the authors' knowledge, no study has used a large general population sample to estimate its prevalence. The authors conducted a random sample, national household telephone survey in the spring and summer of 2004 and interviewed 2,513 adults. The interviews addressed buying attitudes and behaviors, their consequences, and the respondents' financial and demographic data. The authors used a clinically validated screening instrument, the Compulsive Buying Scale, to classify respondents as either compulsive buyers or not. The rate of response was 56.3%, which compares favorably with rates in federal national health surveys. The cooperation rate was 97.6%. Respondents included a higher percentage of women and people ages 55 and older than the U.S. adult population. The estimated point prevalence of compulsive buying among respondents was 5.8% (by gender: 6.0% for women, 5.5% for men). The gender-adjusted prevalence rate was 5.8%. Compared with other respondents, compulsive buyers were younger, and a greater proportion reported incomes under 50,000 US dollars. They exhibited more maladaptive responses on most consumer behavior measures and were more than four times less likely to pay off credit card balances in full. A study using clinically valid interviews is needed to evaluate these results. The emotional and functional toll of compulsive buying and the frequency of comorbid psychiatric disorders suggests that studies of treatments and social interventions are warranted.
Directory of Open Access Journals (Sweden)
Ibrahim M. Safwat
2017-11-01
Full Text Available State-of-charge (SOC estimations of Li-ion batteries have been the focus of many research studies in previous years. Many articles discussed the dynamic model’s parameters estimation of the Li-ion battery, where the fixed forgetting factor recursive least square estimation methodology is employed. However, the change rate of each parameter to reach the true value is not taken into consideration, which may tend to poor estimation. This article discusses this issue, and proposes two solutions to solve it. The first solution is the usage of a variable forgetting factor instead of a fixed one, while the second solution is defining a vector of forgetting factors, which means one factor for each parameter. After parameters estimation, a new idea is proposed to estimate state-of-charge (SOC of the Li-ion battery based on Newton’s method. Also, the error percentage and computational cost are discussed and compared with that of nonlinear Kalman filters. This methodology is applied on a 36 V 30 A Li-ion pack to validate this idea.
Development of an on-line state estimator for fed-batch filamentous fungal fermentations
DEFF Research Database (Denmark)
Mears, Lisa; Stocks, Stuart M.; Albæk, Mads O.
to monitor and control bioprocess systems. There is therefore an interest in state estimation, in order to model these key process states based on available on-line measurements [1]. This work discusses the application of a first principle model to pilot scale filamentous fungal fermentation systems operated...... pressure [4], [5]. This stoichiometric-based coupled process model is successfully applied on-line as a state estimator in order to predict the biomass and product concentration, from robust, available on-line measurements. Such state estimators will be valuable as part of control strategy development...... for on-line process control and optimization....
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...... Estimation (DSE), creates an updated admittance matrix. First, a hybrid AC/DC network model is developed to combine the AC network and DC links. Then a non-linear state estimator can solve for hybrid AC/DC states by applying the unscented Kalman filter (UKF) algorithm. It is demonstrated that UKF is easy...
Energy Technology Data Exchange (ETDEWEB)
Williams, TE; Chang, CM; Rosen, EL; Garcia, G; Runnerstrom, EL; Williams, BL; Koo, B; Buonsanti, R; Milliron, DJ; Helms, BA
2014-01-01
We report here the first solid-state, NIR-selective electrochromic devices. Critical to device performance is the arrangement of nanocrystal-derived electrodes into heteromaterial frameworks, where hierarchically porous ITO nanocrystal active layers are infiltrated by an ion-conducting polymer electrolyte with mesoscale periodicity. Enhanced coloration efficiency and transport are realized over unarchitectured electrodes in devices, paving the way towards new smart windows technologies.
Error estimates for extrapolations with matrix-product states
Hubig, C.; Haegeman, J.; Schollwöck, U.
2018-01-01
We introduce an error measure for matrix-product states without requiring the relatively costly two-site density-matrix renormalization group (2DMRG). This error measure is based on an approximation of the full variance 〈ψ |(Ĥ-E ) 2|ψ 〉 . When applied to a series of matrix-product states at different bond dimensions obtained from a single-site density-matrix renormalization group (1DMRG) calculation, it allows for the extrapolation of observables towards the zero-error case representing the exact ground state of the system. The calculation of the error measure is split into a sequential part of cost equivalent to two calculations of 〈ψ |H ̂|ψ 〉 and a trivially parallelized part scaling like a single operator application in 2DMRG. The reliability of this error measure is demonstrated by four examples: the L =30 ,S =1 /2 Heisenberg chain, the L =50 Hubbard chain, an electronic model with long-range Coulomb-like interactions, and the Hubbard model on a cylinder with a size of 10 ×4 . Extrapolation in this error measure is shown to be on par with extrapolation in the 2DMRG truncation error or the full variance 〈ψ |(Ĥ-E ) 2|ψ 〉 at a fraction of the computational effort.
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.
Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems.
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.
Aircraft sensor validation monitor and state estimator using artificial intelligence
Kwak, Seung-Keon; Yoon, Hwan-Sik
2006-03-01
A new Sensor Validity Monitoring, Verification, and Accommodation (SVMVA) technique based on an artificial neural network is developed for a self-repairing Flight Control System (FCS). For the proposed system, the Learning Vector Quantization (LVQ) method is employed as the on-line, real time learning, monitoring, and estimation tool. In order to conduct a feasibility study, we applied the developed algorithm to a flight vehicle simulator. The simulation results show that the proposed SVMVA with LVQ can instantly detect the failure of physical sensors and accommodate them for more than 30 minutes. By employing this type of analytical sensor redundancy, a flight vehicle can save power, weight, and space, which are required for installing redundant physical sensors.
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
Applied solid state science advances in materials and device research 2
Wolfe, Raymond
2013-01-01
Applied Solid State Science: Advances in Materials and Device Research, Volume 2 covers topics about complex oxide materials such as the garnets, which dominate the field of magnetoelasticity and are among the most important laser hosts, and sodalite, which is one of the classic photochromic materials. The book discusses the physics of the interactions of electromagnetic, elastic, and spin waves in single crystal magnetic insulators. The text then describes the mechanism on which inorganic photochromic materials are based, as observed in a variety of materials in single crystal, powder, and gl
Directory of Open Access Journals (Sweden)
Dai Wang
2014-03-01
Full Text Available False data injection (FDI is considered to be one of the most dangerous cyber-attacks in smart grids, as it may lead to energy theft from end users, false dispatch in the distribution process, and device breakdown during power generation. In this paper, a novel kind of FDI attack, named tolerable false data injection (TFDI, is constructed. Such attacks exploit the traditional detector’s tolerance of observation errors to bypass the traditional bad data detection. Then, a method based on extended distributed state estimation (EDSE is proposed to detect TFDI in smart grids. The smart grid is decomposed into several subsystems, exploiting graph partition algorithms. Each subsystem is extended outward to include the adjacent buses and tie lines, and generate the extended subsystem. The Chi-squares test is applied to detect the false data in each extended subsystem. Through decomposition, the false data stands out distinctively from normal observation errors and the detection sensitivity is increased. Extensive TFDI attack cases are simulated in the Institute of Electrical and Electronics Engineers (IEEE 14-, 39-, 118- and 300-bus systems. Simulation results show that the detection precision of the EDSE-based method is much higher than that of the traditional method, while the proposed method significantly reduces the associated computational costs.
Lerman, Gilad M; Levy, Uriel
2013-03-13
Great hopes rest on surface plasmon polaritons' (SPPs) potential to bring new functionalities and applications into various branches of optics. In this paper, we demonstrate a pin cushion structure capable of coupling light from free space into SPPs, split them based on the polarization content of the illuminating beam of light, and focus them into small spots. We also show that for a circularly or randomly polarized light, four focal spots will be generated at the center of each quarter circle comprising the pin cushion device. Furthermore, following the relation between the relative intensity of the obtained four focal spots and the relative position of the illuminating beam with respect to the structure, we propose and demonstrate the potential use of our structure as a miniaturized plasmonic version of the well-known four quadrant detector. Additional potential applications may vary from multichannel microscopy and multioptical traps to real time beam tracking systems.
Marom, Gil; Bluestein, Danny
2016-01-01
This paper evaluated the influence of various numerical implementation assumptions on predicting blood damage in cardiovascular devices using Lagrangian methods with Eulerian computational fluid dynamics. The implementation assumptions that were tested included various seeding patterns, stochastic walk model, and simplified trajectory calculations with pathlines. Post processing implementation options that were evaluated included single passage and repeated passages stress accumulation and time averaging. This study demonstrated that the implementation assumptions can significantly affect the resulting stress accumulation, i.e., the blood damage model predictions. Careful considerations should be taken in the use of Lagrangian models. Ultimately, the appropriate assumptions should be considered based the physics of the specific case and sensitivity analysis, similar to the ones presented here, should be employed.
Huang, Z.; Xu, C.
2014-12-01
In laboratory tests of oscillating-water-column (OWC) devices for extracting wave energy from ocean waves, an orifice is often used as the power-takeoff mechanism. Calculations of the energy loss due to vortex shedding and the pneumatic extraction efficiency of the OWC chamber are two challenging issues. Direct measurement of the energy loss due to vortex shedding is difficult. The pneumatic extraction efficiency is often calculated by using a one-point measurement method, in which one pressure senor is used to measure the air pressure variation and one wave gauge is used to measure the instantaneous surface displacement inside the OWC chamber. This method is simple, but a systematic error may be introduced, especially for shorter waves. Based on our recent laboratory and theoretical studies of a pile-supported OWC device, we present a method for estimating the energy loss due to vortex shedding and improving the accuracy in the calculation of pneumatic extraction efficiency using one-point method. The method in this study is designed for an OWC device whose chamber has a circular cross section, but can be extended to other cases where development of an analytical theory is possible.
Directory of Open Access Journals (Sweden)
Daniel Tirelli
2014-01-01
Full Text Available A new passive device for mitigating cable vibrations is proposed and its efficiency is assessed on 45-meter long taut cables through a series of free and forced vibration tests. It consists of a unilateral spring attached perpendicularly to the cable near the anchorage. Because of its ability to change the cable dynamic behaviour through intermittent activation, the device has been called state switched inducer (SSI. The cable behaviour is shown to be deeply modified by the SSI: the forced vibration response is anharmonicc and substantially reduced in amplitude whereas the free vibration decay is largely sped up through a beating phenomenon. The vibration mitigation effect is mainly due to the activation and coupling of various vibration modes, as evidenced in the response spectra of the equipped cable. This first large-scale experimental campaign shows that the SSI outperforms classical passive devices, thus paving the way to a new kind of low-cost vibration mitigation systems which do not rely on dissipation.
Choi, Tae-Hoon; Huh, Jae-Won; Woo, Jae-Hyeon; Kim, Jin-Hun; Jo, Young-Seo; Yoon, Tae-Hoon
2017-05-15
We report an electrically-switchable two-dimensional liquid crystal (LC) phase grating device for window display applications. The device consists of the top and bottom substrates with crossed interdigitated electrodes and vertically-aligned LCs sandwiched between the two substrates. The device, switchable between the transparent and translucent states by applying an electric field, can provide high haze by the strong diffraction effect thanks to a large spatial phase difference with little dependence on the azimuth angle. We found that the device has outstanding features, such as a low operating voltage, high transparency, and wide viewing angle characteristics in the transparent state and high haze in the translucent state. Moreover, we achieved submillisecond switching between transparent and translucent states by employing the overdrive scheme and a vertical trigger pulse.
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
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...... 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....
International Nuclear Information System (INIS)
Toumi, Redouane
1977-01-01
For certain scientific applications, especially in Metrology, a means to define the frequency stability of oscillators and sinusoidal generators is indispensable. At the level of the precision required, the random nature of noises overlying the useful signal introduces an uncertainty on the frequency determination which may be reduced by an adequate statistical treatment of the experimental data. The estimator most commonly used by metrology laboratories to estimate the frequency instability is the square root of Allan's variance. This estimator has the essential property of converging for most of the noises encountered in practice. An outline of the essential theory is followed by an account of the experimental methods and the results of stability tests on a generator-synthesizer (piloted by a quartz oscillator), with respect to a frequency standard (rubidium atomic clock). The limits of the Allan's variance method and the experimental problems involved are examined. This work was carried out at the Metrology Laboratory of the Equipment Management Section of the Saclay Nuclear Research Centre Electronics Services. It shows how a programmed measurement device helps to reduce uncertainties in the estimation of a quantity perturbed by noises. (author) [fr
Liu, Fei; Wang, Jian; Guo, Hong
2016-10-27
Black phosphorus (BP) tunneling field effect transistors (TFETs) using heterojunctions (Hes) are investigated by atomistic quantum transport simulations. It is observed that edge states have a great impact on the transport characteristics of BP He-TFETs, which results in the potential pinning effect and deterioration of gate control. However, the on-state current can be effectively enhanced by using hydrogen to saturate the edge dangling bonds in BP He-TFETs, by which means edge states are quenched. By extending layered BP with a smaller band gap to the channel region and modulating the BP thickness, the device performance of BP He-TFETs can be further optimized and can fulfil the requirements of the international technology road-map for semiconductors (ITRS) 2013 for low power applications. In 15 nm 3L-1L and 4L-1L BP He-TFETs along the armchair direction the on-state currents are over two times larger than the current required by ITRS 2013 and can reach above 10 3 μA μm -1 with the fixed off-state current of 10 pA μm -1 . It is also found that the ambipolar effect can be effectively suppressed in BP He-TFETs.
International Nuclear Information System (INIS)
2009-01-01
The conference covers a wide range of topics especially on ion conducting polymer electrolytes, glassy/crystalline, thin films and ceramic materials, design and synthesis of new materials as well as their details, characterization to equip them with knowledge based related to device concept. The technological applications emerging from these materials are viz. solid state batteries, fuel cells, electro-chromics display devices, sensors, super capacitors, HEV's actuators, bio-medical devices and nano-devices etc.. Papers relevant to INIS are indexed separately
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...
Solid-State Electrochromic Device Consisting of Amorphous WO3 and Various Thin Oxide Layers
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.
The Joint Position-Amplitude Formulation for Hurricane State Estimation
Ravela, S.; Williams, J.; Emanuel, K.
2008-12-01
Classical formulations of data assimilation, whether sequential, ensemble-based or variational, are amplitude adjustment methods. Such approaches can perform poorly when forecast locations of weather systems are displaced from their observations. Compensating position errors by adjusting amplitudes can produce unacceptably 'distorted' states, adversely affecting analysis, verification and subsequent forecasts. There are many sources of position error. It is non-trivial to decompose position error into constituent sources and yet correcting position errors during assimilation can be essential for operationally predicting strong, localized weather events such as tropical cyclones. We will argue and show that if we assume a perfect world where forecast errors do not have position errors and have a Gaussian uncertainty, then in the real world, the bias or variance induced by position errors is the only reason for suboptimal performance of contemporary assimilation methods. Therefore, we propose a method that accounts for both position and amplitude errors using a variational approach. We show that the objective can be solved for position and amplitude decision variables using stochastic methods, thus corresponding with ensemble data assimilation. We then show that if an Euler-Lagrange approximation is made, can solve the objective nearly as well in two steps. This approach is entirely consistent with contemporary data assimilation practice. In the two-step approach, the first step is field alignment, where the current model state is aligned with observations by adjusting a continuous field of local displacements, subject to certain constraints. The second step is amplitude adjustment, where contemporary assimilation approaches are used. We will then demonstrate several choices of constraints on the displacement field, first starting with fluid-like viscous constraints and then proceeding to a multiscale wavelet representation that allows better balance in the
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
Gurova, E. G.; Pustovoy, N. V.
2017-10-01
In this research the method of the calculation of the power losses in DC electromagnet through eddy currents, which are analog of the viscous friction, is presented. The influence of these currents on the operation of the vibroisolator with the electromagnetic stiffness compensator is estimated. The losses of the power by eddy currents are less than 1 per cent of the electromagnet power itself and the compensator totally. The example of the calculation of the losses for eddy currents in steel conductor is also shown.
Design of a two-level power system linear state estimator
Yang, Tao
The availability of synchro-phasor data has raised the possibility of a linear state estimator if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. Moreover, the new digital substations can perform some of the computation at the substation itself resulting in a more accurate two-level state estimator. The objective of this research is to develop a two-level linear state estimator processing synchro-phasor data and estimating the states at both the substation level and the control center level. Both the mathematical algorithms that are different from those in the present state estimation procedure and the layered architecture of databases, communications and application programs that are required to support this two-level linear state estimator are described in this dissertation. Besides, as the availability of phasor measurements at substations will increase gradually, this research also describes how the state estimator can be enhanced to handle both the traditional state estimator and the proposed linear state estimator simultaneously. This provides a way to immediately utilize the benefits in those parts of the system where such phasor measurements become available and provides a pathway to transition to the smart grid of the future. The design procedure of the two-level state estimator is applied to two study systems. The first study system is the IEEE-14 bus system. The second one is the 179 bus Western Electricity Coordinating Council (WECC) system. The static database for the substations is constructed from the power flow data of these systems and the real-time measurement database is produced by a power system dynamic simulating tool (TSAT). Time-skew problems that may be caused by communication delays are also considered and simulated. We used the Network Simulator (NS) tool to simulate a simple communication system and analyse its time delay performance. These
Photo-Induced Multiple-State Memory Behaviour in Non-Volatile Bipolar Resistive-Switching Devices.
Zhang, Xuejiao; Xu, Zhiwei; Sun, Bai; Liu, Jianjun; Cao, Yanyan; Qiao, Haixia; Huang, Yong; Pang, Xiaofeng
2018-04-01
The recent discovery of non-volatile resistive-switching memory is a promising phenomenon for the semiconductor industry and electronic device technology. In our work, CaWO4 nanoparticles were synthesised through a one-step hydrothermal reaction. A resistive-switching memory device with Ag/CaWO4/fluorine-doped tin oxide structure was prepared. This device presents photo-induced multiple-state memory behaviour at room temperature. This study is valuable for exploring multi-functional materials and their applications in photo-controlled multiple-state non-volatile memories.
Sargent, B. Pierre; Maupin, Molly A.; Hinkle, Stephen R.
2008-01-01
The U.S. Geological Survey National Water Use Information Program compiles estimates of fresh ground-water withdrawals in the United States on a 5-year interval. In the year-2000 compilation, withdrawals were reported from principal aquifers and aquifer systems including two general aquifers - Alluvial and Other aquifers. Withdrawals from a widespread aquifer group - stream-valley aquifers - were not specifically identified in the year-2000 compilation, but they are important sources of ground water. Stream-valley aquifers are alluvial aquifers located in the valley of major streams and rivers. Stream-valley aquifers are long but narrow aquifers that are in direct hydraulic connection with associated streams and limited in extent compared to most principal aquifers. Based in large part on information published in U.S. Geological Survey reports, preliminary analysis of withdrawal data and hydrogeologic and surface-water information indicated areas in the United States where possible stream-valley aquifers were located. Further assessment focused on 24 states and the Commonwealth of Puerto Rico. Withdrawals reported from Alluvial aquifers in 16 states and withdrawals reported from Other aquifers in 6 states and the Commonwealth of Puerto Rico were investigated. Two additional States - Arkansas and New Jersey - were investigated because withdrawals reported from other principal aquifers in these two States may be from stream-valley aquifers. Withdrawals from stream-valley aquifers were identified in 20 States and were about 1,560 Mgal/d (million gallons per day), a rate comparable to withdrawals from the 10 most productive principal aquifers in the United States. Of the 1,560 Mgal/d of withdrawals attributed to stream-valley aquifers, 1,240 Mgal/d were disaggregated from Alluvial aquifers, 150 Mgal/d from glacial sand and gravel aquifers, 116 Mgal/d from Other aquifers, 28.1 Mgal/d from Pennsylvanian aquifers, and 24.9 Mgal/d from the Mississippi River Valley alluvial
Boland, J. S., III
1975-01-01
A general simulation program is presented (GSP) involving nonlinear state estimation for space vehicle flight navigation systems. A complete explanation of the iterative guidance mode guidance law, derivation of the dynamics, coordinate frames, and state estimation routines are given so as to fully clarify the assumptions and approximations involved so that simulation results can be placed in their proper perspective. A complete set of computer acronyms and their definitions as well as explanations of the subroutines used in the GSP simulator are included. To facilitate input/output, a complete set of compatable numbers, with units, are included to aid in data development. Format specifications, output data phrase meanings and purposes, and computer card data input are clearly spelled out. A large number of simulation and analytical studies were used to determine the validity of the simulator itself as well as various data runs.
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
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
International Nuclear Information System (INIS)
Horodecki, Pawel
2003-01-01
Possibility of some nonlinear-like operations in quantum mechanics are studied. Some general formula for real linear maps are derived. With the results we show how to perform physically separability tests based on any linear contraction (on product states) that either is real or Hermitian. We also show how to estimate either product or linear combinations of quantum states without knowledge about the states themselves. This can be viewed as a sort of quantum computing on quantum states algebra
Hypersonic entry vehicle state estimation using nonlinearity-based adaptive cubature Kalman filters
Sun, Tao; Xin, Ming
2017-05-01
Guidance, navigation, and control of a hypersonic vehicle landing on the Mars rely on precise state feedback information, which is obtained from state estimation. The high uncertainty and nonlinearity of the entry dynamics make the estimation a very challenging problem. In this paper, a new adaptive cubature Kalman filter is proposed for state trajectory estimation of a hypersonic entry vehicle. This new adaptive estimation strategy is based on the measure of nonlinearity of the stochastic system. According to the severity of nonlinearity along the trajectory, the high degree cubature rule or the conventional third degree cubature rule is adaptively used in the cubature Kalman filter. This strategy has the benefit of attaining higher estimation accuracy only when necessary without causing excessive computation load. The simulation results demonstrate that the proposed adaptive filter exhibits better performance than the conventional third-degree cubature Kalman filter while maintaining the same performance as the uniform high degree cubature Kalman filter but with lower computation complexity.
DEFF Research Database (Denmark)
Alvarez, David; Silva, Filipe Miguel Faria da; Mombello, Enrique E.
2018-01-01
Dynamic line rating has emerged as a solution for reducing congestion in overhead lines, allowing the optimization of power systems assets. This technique is based on direct and/or indirect monitoring of conductor temperature. Different devices and methods have been developed to sense conductor t...
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
-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......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...
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.
Estimates of the Lawful Permanent Resident Population in the United States: January 2014
Department of Homeland Security — This report presents estimates of the lawful permanent resident (LPR) population living in the United States on January 1, 2014. The LPR population includes persons...
Estimates of the Lawful Permanent Resident Population in the United States: January 2013
Department of Homeland Security — This report presents estimates of the lawful permanent resident (LPR) population living in the United States on January 1, 2013. The LPR population includes persons...
Reaching Those in Need: Estimates of State SNAP Participation Rates in 2014
Department of Agriculture — This report – part of an annual series – presents estimates of the percentage of eligible persons, by State, who participated in the U.S. Department of Agriculture’s...
DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING
National Aeronautics and Space Administration — DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING SUBHASISH MOHANTY*, ADITI CHATTOPADHYAY, JOHN N. RAJADAS, AND CLYDE...
National Research Council Canada - National Science Library
Sullivan, Michael J
2005-01-01
This thesis develops a state estimation algorithm for the Centrifuge Rotor (CR) system where only relative measurements are available with limited knowledge of both rotor imbalance disturbances and International Space Station (ISS...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2012
Department of Homeland Security — This report provides estimates of the size of the unauthorized immigrant population residing in the United States as of January 2012 by period of entry, region and...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2009
Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2009 by period of entry, region and country of...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2007
Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2007 by period of entry, region and country of...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2008
Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2008 by period of entry, region and country of...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2010
Department of Homeland Security — This report provides estimates of the size of the unauthorized immigrant population residing in the United States as of January 2010 by period of entry, region and...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2006
Department of Homeland Security — This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2006 by period of entry, region and country of...
Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2011
Department of Homeland Security — This report provides estimates of the size of the unauthorized immigrant population residing in the United States as of January 2011 by period of entry, region and...
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.
Couto, Luis D.; Kinnaert, Michel
2017-01-01
Accurate state estimation of large-scale lithium-ion battery packs is necessary for the advanced control of batteries, which could potentially increase their lifetime through e.g. reconfiguration. To tackle this problem, an enhanced reduced-order electrochemical model is used here. This model allows considering a wider operating range and thermal coupling between cells, the latter turning out to be significant. The resulting nonlinear model is exploited for state estimation through unscented ...
Dual extended Kalman filter for combined estimation of vehicle state and road friction
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.
Drug use and AIDS: estimating injection prevalence in a rural state.
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.
State and Substate Estimates of Nonmedical Use of Prescription Pain Relievers
... 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 presented in Figure ...
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Jørgensen, John Bagterp; Rawlings, James B.
2015-01-01
In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least s...
Estimation and asymptotic theory for transition probabilities in markov renewal multi-state models
Spitoni, Cristian|info:eu-repo/dai/nl/304625957; Verduijn, Marion; Putter, Hein
2014-01-01
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 delta
New cost estimates for carbon sequestration through afforestation in the United States
Anne Sofie Elburg Nielsen; Andrew J. Plantinga; Ralph J. Alig
2014-01-01
This report provides new cost estimates for carbon sequestration through afforestation in the United States. We extend existing studies of carbon sequestration costs in several important ways, while ensuring the transparency of our approach. We clearly identify all components of our cost estimates so that other researchers can reconstruct our results as well as use our...
Validation of a model for estimating state and local prevalence of serious mental illness.
Hudson, Christopher G
2009-12-01
This study addresses an ongoing problem in mental health needs assessment. This involves estimating the prevalence of an identified problem, specifically serious mental illness (SMI), for local areas in a reliable, valid, and cost-effective manner. The aim of the study is the application and testing of a recently introduced methodology from the field of small area estimation to determining SMI rates in the 48 contiguous US states, and in local areas of Massachusetts. It uses 'regression synthetic estimation fitted using area-level covariates', to estimate a model using data from the 2001-2002 replication of the National Comorbidity Study (n = 5593) and apply it, using 2000 STF-3C Census data, to various state and local areas in the United States. The estimates are then compared with independently collected SMI indicators. The estimates show not only face validity and internal consistency, but also predictive validity. The multiple logistic model has a sensitivity of 21.1% and a specificity of 95.1%, based largely on socio-economic disparities. Pearson r validity coefficients for the area estimates range from 0.43 to 0.75. The model generates a national estimate of SMI adults of 5.5%; for the 48 states, rates ranging from 4.7% to 7.0%; and for Massachusetts towns and cities, 1.1% to 7.5%.
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.
Solid-state electrochromic devices using pTMC/PEO blends as polymer electrolytes
International Nuclear Information System (INIS)
Barbosa, P.C.; Rodrigues, L.C.; Silva, M.M.; Smith, M.J.; Parola, A.J.; Pina, F.; Pinheiro, Carlos
2010-01-01
Flexible, transparent and self-supporting electrolyte films based on poly(trimethylene carbonate)/poly(ethylene oxide) (p(TMC)/PEO) interpenetrating networks doped with LiClO 4 were prepared by the solvent casting technique. These novel solid polymer electrolyte (SPE) systems were characterized by measurements of conductivity, cyclic voltammetry, differential scanning calorimetry and thermogravimetry. The incorporation of solid electrolytes as components of electrochromic devices can offer certain operational advantages in real-world applications. In this study, all-solid-state electrochromic cells were characterized, using Prussian blue (PB) and poly-(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT) as complementary electrochromic compounds on poly(ethyleneterphthalate) (PET) coated with indium tin oxide (ITO) as flexible electrodes. Assembled devices with PET/ITO/PB/SPE/PEDOT/ITO/PET 'sandwich-like' structure were assembled and successfully cycled between light and dark blue, corresponding to the additive optical transitions for PB and PEDOT electrochromic layers. The cells required long cycle times (>600 s) to reach full color switch and have modest stability towards prolonged cycling tests. The use of short duration cycling permitted the observation of changes in the coloration-bleaching performance in cells with different electrolyte compositions.
David J. Nowak; Eric J. Greenfield
2010-01-01
The 2001 National Land Cover Database (NLCD) provides 30-m resolution estimates of percentage tree canopy and percentage impervious cover for the conterminous United States. Previous estimates that compared NLCD tree canopy and impervious cover estimates with photo-interpreted cover estimates within selected counties and places revealed that NLCD underestimates tree...
The importance of Fe surface states for spintronic devices based on magnetic tunnel junctions
Energy Technology Data Exchange (ETDEWEB)
Chantis, Athanasios N [Los Alamos National Laboratory
2008-01-01
In this article we give a review of our recent theoretical studies of the influence of Fe(001) surface (interface) states on spin-polarized electron transport across magnetic tunnel junctions with Fe electrodes. We show that minority-spin surface (interface) states are responsible for at least two effects which are important for spin electronics. First, they can produce a sizable tunneling anisotropic magnetoresistance in magnetic tunnel junctions with a single Fe electrode. The effect is driven by a Rashba shift of the resonant surface band when the magnetization changes direction. This can introduce a new class of spintronic devices, namely, tunneling magnetoresistance junctions with a single ferromagnetic electrode. Second, in Fe/GaAs(001) magnetic tunnel junctions minority-spin interface states produce a strong dependence of the tunneling current spin polarization on applied electrical bias. A dramatic sign reversal within a voltage range of just a few tenths of an eV is predicted. This explains the observed sign reversal of spin polarization in recent experiments of electrical spin injection in Fe/GaAs(001) and related reversal of tunneling magnetoresistance through vertical Fe/GaAs/Fe trilayers.
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.
An open source framework for tracking and state estimation ('Stone Soup')
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,
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.
State Estimates of the Northern Philippine Sea Circulation Including Ocean Acoustic Travel Times
Cornuelle, B. D.; Gopalakrishnan, G.; Mazloff, M. R.; Worcester, P. F.; Dzieciuch, M. A.
2016-02-01
The North Pacific Acoustic Laboratory (NPAL) Philippine Sea experiment deployed a variety of instruments in the northern Philippine Sea during April 2010 through April 2011, including 6 acoustic transceivers for reciprocal measurements of travel times between instruments. Five of the transceivers were moored in a pentagon approximately 660 km in diameter with the sixth transceiver mooring in the center. A seventh mooring approximately 130 km northwest of the center supported a Distributed Vertical Line Array (DVLA) which carried 149 acoustic receivers with thermistors covering the depths between 200 m and 5500 m. The goals of the experiment included studying the energetic westward-propagating eddies which travel through the region, their effect on underwater sound propagation, and the impact of acoustic measurements on estimates of the time-evolving ocean state. Observed travel-time time series were compared with travel times computed from ocean state estimates made using an eddy-active regional implementation of the MITgcm that were constrained by satellite sea surface height and sea surface temperature observations and by temperature and salinity profiles from Argo, CTDs, and XBTs but not by the acoustic data. The similarities cross-validate the state estimates, while the differences provide a simple estimate of the novel information present in the travel times. The ocean state estimates were then re-computed to fit the acoustic travel times as integrals of the sound speed, and therefore temperature and salinity, along the ray paths. Over the approximately 1 year experiment, the state estimate was able to match the travel times within their error bars and did not significantly increase the misfits with the other observations. Comparisons of the state estimates with and without the travel-time data showed significant changes to the temperature and salinity were made to fit the acoustic observations. The state estimates using the acoustic data compare favorably
Evaluation of Communication Network State Estimators for Adaptive Power-Balancing
DEFF Research Database (Denmark)
Findrik, Mislav; Pedersen, Rasmus; Sloth, Christoffer
2017-01-01
Smart Grid applications are going to reach the LV grid assets and households in order to efficiently use the resources in distribution grids. A cost effective way to connect these devices is to utilize the existing network infrastructure or to utilize Power-Line Com- munication (PLC). In this work...... compared two network estimation algorithms which are used for adaptive gain scheduling of the LVGC controller yielding better quality-of-control....
Frontier of Fusion Research: Path to the Steady State Fusion Reactor by Large Helical Device
Motojima, Osamu
2006-12-01
The ITER, the International Thermonuclear Experimental Reactor, which will be built in Cadarache in France, has finally started this year, 2006. Since the thermal energy produced by fusion reactions divided by the external heating power, i.e., the Q value, will be larger than 10, this is a big step of the fusion research for half a century trying to tame the nuclear fusion for the 6.5 Billion people on the Earth. The source of the Sun's power is lasting steadily and safely for 8 Billion years. As a potentially safe environmentally friendly and economically competitive energy source, fusion should provide a sustainable future energy supply for all mankind for ten thousands of years. At the frontier of fusion research important milestones are recently marked on a long road toward a true prototype fusion reactor. In its own merits, research into harnessing turbulent burning plasmas and thereby controlling fusion reaction, is one of the grand challenges of complex systems science. After a brief overview of a status of world fusion projects, a focus is given on fusion research at the National Institute for Fusion Science (NIFS) in Japan, which is playing a role of the Inter University Institute, the coordinating Center of Excellence for academic fusion research and by the Large Helical Device (LHD), the world's largest superconducting heliotron device, as a National Users' facility. The current status of LHD project is presented focusing on the experimental program and the recent achievements in basic parameters and in steady state operations. Since, its start in a year 1998, a remarkable progress has presently resulted in the temperature of 140 Million degree, the highest density of 500 Thousand Billion/cc with the internal density barrier (IDB) and the highest steady average beta of 4.5% in helical plasma devices and the largest total input energy of 1.6 GJ, in all magnetic confinement fusion devices. Finally, a perspective is given of the ITER Broad Approach program
Directory of Open Access Journals (Sweden)
Daniel B Kramer
Full Text Available Policymakers and regulators in the United States (US and the European Union (EU are weighing reforms to their medical device approval and post-market surveillance systems. Data may be available that identify strengths and weakness of the approaches to medical device regulation in these settings.We performed a systematic review to find empirical studies evaluating medical device regulation in the US or EU. We searched Medline using two nested categories that included medical devices and glossary terms attributable to the US Food and Drug Administration and the EU, following PRISMA guidelines for systematic reviews. We supplemented this search with a review of the US Government Accountability Office online database for reports on US Food and Drug Administration device regulation, consultations with local experts in the field, manual reference mining of selected articles, and Google searches using the same key terms used in the Medline search. We found studies of premarket evaluation and timing (n = 9, studies of device recalls (n = 8, and surveys of device manufacturers (n = 3. These studies provide evidence of quality problems in pre-market submissions in the US, provide conflicting views of device safety based largely on recall data, and relay perceptions of some industry leaders from self-surveys.Few studies have quantitatively assessed medical device regulation in either the US or EU. Existing studies of US and EU device approval and post-market evaluation performance suggest that policy reforms are necessary for both systems, including improving classification of devices in the US and promoting transparency and post-market oversight in the EU. Assessment of regulatory performance in both settings is limited by lack of data on post-approval safety outcomes. Changes to these device approval and post-marketing systems must be accompanied by ongoing research to ensure that there is better assessment of what works in either setting.
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
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.
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....... dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered...
Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering
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
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
describing the process was simplified from a combined ASM1-Delft model. Three examples were investigated: operation at steady state, operation at steady state with a random white-noise in the measurements and operation with a ramp disturbance. In each case, the estimation was quite accurate even...
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...
H∞state estimation of stochastic memristor-based neural networks with time-varying delays.
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.
Simulation, State Estimation and Control of Nonlinear Superheater Attemporator using Neural Networks
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Sørensen, O.
2000-01-01
This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model...... of the process, then another network is trained to act as a combined state and parameter estimator for the process. The observer network incorporates smoothing of the parameter estimates in the form of regularization. A pole placement controller is designed which takes advantage of the sample......-by-sample linearizations and state estimates provided by the observer network. Simulation studies show that the nonlinear observer-based control loop performs better than a similar control loop based on a linear observer....
Simulation, State Estimation and Control of Nonlinear Superheater Attemporator using Neural Networks
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Sørensen, O.
1999-01-01
This paper considers the use of neural networks for nonlinear state estimation, system identification and control. As a case study we use data taken from a nonlinear injection valve for a superheater attemporator at a power plant. One neural network is trained as a nonlinear simulation model...... of the process, then another network is trained to act as a combined state and parameter estimator for the process. The observer network incorporates smoothing of the parameter estimates in the form of regularization. A pole placement controller is designed which takes advantage of the sample......-by-sample linearizations and state estimates provided by the observer network. Simulation studies show that the nonlinear observer-based control loop performs better than a similar control loop based on a linear observer....
Remediating Non-Positive Definite State Covariances for Collision Probability Estimation
Hall, Doyle T.; Hejduk, Matthew D.; Johnson, Lauren C.
2017-01-01
The NASA Conjunction Assessment Risk Analysis team estimates the probability of collision (Pc) for a set of Earth-orbiting satellites. The Pc estimation software processes satellite position+velocity states and their associated covariance matri-ces. On occasion, the software encounters non-positive definite (NPD) state co-variances, which can adversely affect or prevent the Pc estimation process. Inter-polation inaccuracies appear to account for the majority of such covariances, alt-hough other mechanisms contribute also. This paper investigates the origin of NPD state covariance matrices, three different methods for remediating these co-variances when and if necessary, and the associated effects on the Pc estimation process.
Sea state estimation from an advancing ship – A comparative study using sea trial data
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Stredulinsky, David C.
2012-01-01
and a buoy is clear, although the ship is moving with a forward speed and, in general, is characterised by a more complex underwater geometry. Thus, it is possible to obtain an estimate of the wave spectrum at the location of an advancing ship by processing its wave-induced responses similar to the situation......Onboard sea state estimation is relevant for evaluation of ship operations at sea. Means to obtain the sea state at a fixed position include a traditional wave rider buoy, where motion measurements of the buoy are processed to give the (directional) wave spectrum. The analogy between a ship...... of a traditional wave rider buoy. The paper studies the ‘wave buoy analogy’, and a large set of full-scale motion measurements is considered. It is shown that the wave buoy analogy gives fairly accurate estimates of integrated sea state parameters when compared to corresponding estimates from real wave rider buoys...
Liberal, Iñigo; Engheta, Nader
2018-02-01
Quantum emitters interacting through a waveguide setup have been proposed as a promising platform for basic research on light-matter interactions and quantum information processing. We propose to augment waveguide setups with the use of multiport devices. Specifically, we demonstrate theoretically the possibility of exciting N -qubit subradiant, maximally entangled, states with the use of suitably designed N -port devices. Our general methodology is then applied based on two different devices: an epsilon-and-mu-near-zero waveguide hub and a nonreciprocal circulator. A sensitivity analysis is carried out to assess the robustness of the system against a number of nonidealities. These findings link and merge the designs of devices for quantum state engineering with classical communication network methodologies.
Yin, J.; Shen, Y.; Liu, X. T.; Zeng, G. J.; Liu, D. C.
2017-11-01
The traditional current integral method for the state-of-charge (SOC) estimation has an unusable estimation accuracy because of the current measuring error. This paper proposed a closed-loop temperature compensation method to improve the SOC estimation accuracy of current integral method by eliminating temperature drift. Through circuit simulation result in Multisim, the stability of current measuring accuracy is improved by more than 10 times. In a designed 70 charge-discharge experimental circle, the SOC estimation error with temperature compensation had 30 times less than error in normal situation without compensation.
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...... parameters—are carried out for a large container vessel. The study shows that filtering has an influence on the estimations, since high-frequency components of the wave excitations are not estimated as accurately as lower frequency components....
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.
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...
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.
Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models
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.
Dynamic State Estimation and Parameter Calibration of DFIG based on Ensemble Kalman Filter
Energy Technology Data Exchange (ETDEWEB)
Fan, Rui; Huang, Zhenyu; Wang, Shaobu; Diao, Ruisheng; Meng, Da
2015-07-30
With the growing interest in the application of wind energy, doubly fed induction generator (DFIG) plays an essential role in the industry nowadays. To deal with the increasing stochastic variations introduced by intermittent wind resource and responsive loads, dynamic state estimation (DSE) are introduced in any power system associated with DFIGs. However, sometimes this dynamic analysis canould not work because the parameters of DFIGs are not accurate enough. To solve the problem, an ensemble Kalman filter (EnKF) method is proposed for the state estimation and parameter calibration tasks. In this paper, a DFIG is modeled and implemented with the EnKF method. Sensitivity analysis is demonstrated regarding the measurement noise, initial state errors and parameter errors. The results indicate this EnKF method has a robust performance on the state estimation and parameter calibration of DFIGs.
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
Yazdi, Alireza Ahmadian; Preite, Roberto; Milton, Ross D.; Hickey, David P.; Minteer, Shelley D.; Xu, Jie
2017-03-01
Enzymatic biobatteries can be implanted in living organisms to exploit the chemical energy stored in physiological fluids. Generally, commonly-used electron donors (such as sugars) are ubiquitous in physiological environments, while electron acceptors such as oxygen are limited due to many factors including solubility, temperature, and pressure. The wide range of solid-state cathodes, however, may replace the need for oxygen breathing electrodes and serve in enzymatic biobatteries for implantable devices. Here, we have fabricated a glucose biobattery suitable for in vivo applications employing a glucose oxidase (GOx) anode coupled to a solid-state Prussian Blue (PB) thin-film cathode. PB is a non-toxic material and its electrochemistry enables fast regeneration if used in a secondary cell. This novel biobattery can effectively operate in a membraneless architecture as PB can reduce the peroxide produced by some oxidase enzymes. The resulting biobattery delivers a maximum power and current density of 44 μW cm-2 and 0.9 mA cm-2 , respectively, which is ca. 37% and 180% higher than an equivalent enzymatic fuel cell equipped with a bilirubin oxidase cathode. Moreover, the biobattery demonstrated a stable performance over 20 cycles of charging and discharging periods with only ca. 3% loss of operating voltage.
Deshmukh, Raj
Following recent advances in networked communication technologies, sensor networks have been employed in a broad range of applications at a lower cost than centrally supervised systems. Their major functionality is to track and monitor dynamic processes using various distributed estimation techniques. Specifically, we conduct a study of the process of concurrence between agents for the state of a system. This process of concurrence is known as `consensus', and is exhibited in the distributed Kalman Consensus Filter (KCF). This estimation algorithm fuses data from different connected sensor agents by achieving two objectives for each sensor: 1) locally estimating the state of the system; and 2) reaching a consensus of the state estimate between neighboring agents through communication. Although the conventional KCF has been proven to have superior performance in terms of stability and scalability, it relies on the approximated suboptimal consensus gain to avoid algorithmic and derivational complexity. Particularly, we seek to address this concern of sub-optimality, and analytically derive the closed form solution to the globally optimal consensus gain, which is characterized by the minimum mean squared error for the estimation process. We then expand the perspective of the system dynamics to evolve in a hybrid fashion. Hybrid dynamical systems can describe a larger class of dynamics, as the state evolution is given as a combination of differential equations and discrete state (mode) transition maps. The latter part of this thesis focuses on developing a distributed hybrid estimation algorithm that builds upon the concept of the multiple model based algorithm for state estimation of stochastic hybrid systems. While previous studies have used Kalman filtering for the bank of estimators that the conventional multiple model based algorithm employs, in this research, we use a distributed network to leverage the redundancy in a network and use the measurement data
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...
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.
Graphene and permalloy integration in functional fluidic and solid-state devices
van den Beld, Wesley Theodorus Eduardus
2016-01-01
The aim of the work of this thesis is to develop novel technologies for functional micro- and nanofluidic devices, as well as exploring the functionality of first examples of such devices. The research thereby is mainly centered round graphene,and involved its synthesis, device fabrication, raman
Proceedings of the workshop on new solid state devices for high energy physics
International Nuclear Information System (INIS)
1987-12-01
This paper contains articles on semiconductor devices used in the detection of high energy particles. Some articles reported: Position sensitive semiconductor devices; Scintillation techniques and optical devices; Radiation damage to detectors; VLSI for physics; and experience with Si detectors in NA32
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.
Directory of Open Access Journals (Sweden)
Haorui Liu
2016-01-01
Full Text Available In the car control systems, it is hard to measure some key vehicle states directly and accurately when running on the road and the cost of the measurement is high as well. To address these problems, a vehicle state estimation method based on the kernel principal component analysis and the improved Elman neural network is proposed. Combining with nonlinear vehicle model of three degrees of freedom (3 DOF, longitudinal, lateral, and yaw motion, this paper applies the method to the soft sensor of the vehicle states. The simulation results of the double lane change tested by Matlab/SIMULINK cosimulation prove the KPCA-IENN algorithm (kernel principal component algorithm and improved Elman neural network to be quick and precise when tracking the vehicle states within the nonlinear area. This algorithm method can meet the software performance requirements of the vehicle states estimation in precision, tracking speed, noise suppression, and other aspects.
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.
Kamphuis, C; Dela Rue, B; Turner, S-A; Petch, S-F
2015-05-01
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 representative milk samples compared with devices used by certified milk recording providers on farms with conventional milking systems (CMS) and (2) devices used on both AMS and CMS comply with accuracy criteria described by the New Zealand Standard and by the International Committee of Animal Recording (ICAR). Milk recording data from 5 AMS farms were collected during 13 milk recording test days between December 2011 and February 2013. Milk yield was estimated by ICAR-approved milk meters on AMS units. Milk samples were collected over a 48-h period and submitted to an off-site certified laboratory for milk composition analysis. Data were also collected manually from 5 to 10 cows per AMS unit; a complete milking of a cow was weighed to serve as gold standard for milk yield, and 3 milk samples per cow milking were collected and analyzed in the laboratory to serve as gold standards for milk composition. A similar procedure was used during 6 milk recording occasions with devices used during conventional milk recording at a CMS research farm. Farm type, breed, season, and region did not appear to affect accuracy of devices used on AMS units. Milk meters used by AMS units complied with ICAR limits in 12.5 and 25% of the milk recording test days for test bucket weights between 2 and 10kg and for test bucket weights >10kg, respectively. These percentages were 52 and 42%, respectively, for devices used on CMS. Analyzing all samples as one milk recording test day, 1.4% fell outside the 20% difference band for AMS compared with 1.1% of the milk samples for CMS. Devices used by AMS complied with ICAR in 73% of the milk recording test days for fat percentage, compared with 42% of the milk
Methods for Estimating Water Withdrawals for Mining in the United States, 2005
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
An FEM-Based State Estimation Approach to Nonlinear Hybrid Positioning Systems
Directory of Open Access Journals (Sweden)
Yu-Xin Zhao
2013-01-01
Full Text Available For hybrid positioning systems (HPSs, the estimator design is a crucial and important problem. In this paper, a finite-element-method- (FEM- based state estimation approach is proposed to HPS. As the weak solution of hybrid stochastic differential model is denoted by the Kolmogorov's forward equation, this paper constructs its interpolating point through the classical fourth-order Runge-Kutta method. Then, it approaches the solution with biquadratic interpolation function to obtain a prior probability density function of the state. A posterior probability density function is gained through Bayesian formula finally. In theory, the proposed scheme has more advantages in the performance of complexity and convergence for low-dimensional systems. By taking an illustrative example, numerical experiment results show that the new state estimator is feasible and has good performance than PF and UKF.
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.
State estimation and control for low-cost unmanned aerial vehicles
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...
Online state-of-health estimation of lithium-ion batteries using Dynamic Bayesian Networks
He, Zhiwei; Gao, Mingyu; Ma, Guojin; Liu, Yuanyuan; Chen, Sanxin
2014-12-01
Li-ion batteries are widely used in energy storage systems, electric vehicles, communication systems, etc. The State of Health (SOH) of batteries is of great importance to the safety of these systems. This paper presents a novel online method for the estimation of the SOH of Lithium (Li)-ion batteries based on Dynamic Bayesian Networks (DBNs). The structure of the DBN model is built according to the experience of experts, with the state of charges used as hidden states and the terminal voltages used as observations in the DBN. Parameters of the DBN model are learned based on training data collected through Li-ion battery aging experiments. A forward algorithm is applied for the inference of the DBN model in order to estimate the SOH in real-time. Experimental results show that the proposed method is effective and efficient in estimating the SOH of Li-ion batteries.
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.
Gilboa, Suzanne M; Devine, Owen J; Kucik, James E; Oster, Matthew E; Riehle-Colarusso, Tiffany; Nembhard, Wendy N; Xu, Ping; Correa, Adolfo; Jenkins, Kathy; Marelli, Ariane J
2016-07-12
Because of advancements in care, there has been a decline in mortality from congenital heart defects (CHDs) over the past several decades. However, there are no current empirical data documenting the number of people living with CHDs in the United States. Our aim was to estimate the CHD prevalence across all age groups in the United States in the year 2010. The age-, sex-, and severity-specific observed prevalence of CHDs in Québec, Canada, in the year 2010 was assumed to equal the CHD prevalence in the non-Hispanic white population in the United States in 2010. A race-ethnicity adjustment factor, reflecting differential survival between racial-ethnic groups through 5 years of age for individuals with a CHD and that in the general US population, was applied to the estimated non-Hispanic white rates to derive CHD prevalence estimates among US non-Hispanic blacks and Hispanics. Confidence intervals for the estimated CHD prevalence rates and case counts were derived from a combination of Taylor series approximations and Monte Carlo simulation. We estimated that ≈2.4 million people (1.4 million adults, 1 million children) were living with CHDs in the United States in 2010. Nearly 300 000 of these individuals had severe CHDs. Our estimates highlight the need for 2 important efforts: planning for health services delivery to meet the needs of the growing population of adults with CHD and the development of surveillance data across the life span to provide empirical estimates of the prevalence of CHD across all age groups in the United States. © 2016 American Heart Association, Inc.
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.
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.
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.
Estimating inpatient hospital prices from state administrative data and hospital financial reports.
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.
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.
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...
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
describing the process was simplified from a combined ASM1-Delft model. Three examples were investigated: operation at steady state, operation at steady state with a random white-noise in the measurements and operation with a ramp disturbance. In each case, the estimation was quite accurate even...... 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....
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
Optimal State Estimation for Discrete-Time Markov Jump Systems with Missing Observations
Directory of Open Access Journals (Sweden)
Qing Sun
2014-01-01
Full Text Available This paper is concerned with the optimal linear estimation for a class of direct-time Markov jump systems with missing observations. An observer-based approach of fault detection and isolation (FDI is investigated as a detection mechanic of fault case. For systems with known information, a conditional prediction of observations is applied and fault observations are replaced and isolated; then, an FDI linear minimum mean square error estimation (LMMSE can be developed by comprehensive utilizing of the correct information offered by systems. A recursive equation of filtering based on the geometric arguments can be obtained. Meanwhile, a stability of the state estimator will be guaranteed under appropriate assumption.
Distributed and decentralized state estimation in gas networks as distributed parameter systems.
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.
Improved extended Kalman filter for state of charge estimation of battery pack
Sepasi, Saeed; Ghorbani, Reza; Liaw, Bor Yann
2014-06-01
It is difficult to model the behavior of the battery pack accurately due to the electrochemical characteristics variations among cells of a battery pack. As a result, accurate state-of-charge (SOC) and state-of-health (SOH) estimation for the battery pack is a case provocation. The estimation process poses more challenges after substantial battery aging. This paper tries to estimate the SOC of a Li-ion battery pack for an electrical vehicle using improved extended Kalman filter (IEKF) which benefits from considering aging phenomenon in the electrical model of cells. In order to assemble a battery pack, we find cells with similar electrochemical characteristics. Model adaptive algorithm is applied on the corresponding cells of a string to minimize cell-to-cell variation's effect. During the operation, the values of electrical model of each cell are updated by the same algorithm to compensate aging effects on SOC estimation error. The mean value of updated cell's model is used for a single unit cell model of the pack used at IEKF to achieve more accurate SOC estimation. The algorithm's fast response and low computational burden, makes on-board estimation practical. The experimental results reveal that the proposed approach's SOC and voltage estimation errors do not exceed 1.5%.
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.
Directory of Open Access Journals (Sweden)
Chen Chai
2017-01-01
Full Text Available Safety effects of Green-Man Countdown Device (GMCD at signalized pedestrian crosswalks are evaluated. Pedestrian behavior at GMCD and non-GMCD crosswalks is observed and analyzed. A microsimulation model is developed based on field observations to estimate safety performance. Simulation outputs allow analysts to assess the impacts of GMCD at various conditions with different geometric layout, traffic and pedestrian volumes, and the green time. According to simulation results, it is found that the safety impact of GMCD is affected by traffic condition as well as different time duration within green-man signal phase. In general, GMCD increases average walking velocity, especially during the last few seconds. The installation of GMCD improves safety performance generally, especially at more crowded crossings. Conflict severity is increased during last 10 s after GMCD installation. Findings from this study suggest that the current practice, which is to install GMCD at more crowded crosswalks or near the school zone, is effective. Moreover, at crosswalks with GMCD, longer all red signal phase is suggested to improve pedestrian safety during intergreen period.
Directory of Open Access Journals (Sweden)
Vacheva Gergana
2017-01-01
Full Text Available While the number of the vehicle actuated with liquid fuels are settled, the count of electric vehicles is increasing. For the present moment most of them are scheduled for daily urban usage. This paper presents an analytical approach for estimation of the impact of electrical vehicle (EV battery charging on the distribution grid. Based on the EV charge profile, load curve and local distributed generation the grid nodes, the time variation of grid parameters is obtained. A set of typical load profiles of EV charging modes is studied and presented. A software implementation and a 24h case study of low voltage distribution network with EV charging devices is presented in order to illustrate the approach and the impacts of EV charging on the grid. In the current paper an approach using variable nonlinear algebraic equations for dynamic time domain analysis of the charge of the electric vehicles is presented. Based on the results, the challenges due to EV charging in distribution networks including renewable energy sources are discussed. This approach is widely applicable for various EV charging and distributed energy resources studies considering control algorithms, grid stability analysis, smart grid power management and other power system analysis problems.
McCoy, Jedidiah; Merlak, Marek; Witanachchi, Sarath
2013-03-01
Increasingly, greenhouse farming and urban agriculture are being looked at as a more efficient and more cost effective way to grow produce. Currently the lights used in greenhouses rely on light sources that emit a broad spectrum of light. However, only light at wavelengths around 460 nm (blue) and 670 nm (red) are absorbed by most plants for photosynthesis. Solid state lighting devices can be engineered to produce light to match the needs of the plant while reducing the energy cost. An investigation into the photoluminescence properties of the nanophosphor La2O3 doped with Bi was done in an effort to produce a phosphor emitting in blue wavelengths. The La2O3:Bi coatings were grown using a microwave plasma growth process. Microwave power and chamber pressure were varied to find the optimum synthesis conditions. Power was varied from 100Watts to 900Watts and chamber pressure was varied from 30Torr to 60Torr. The process utilized O2 and CO2 plasma. The nanophosphors were investigated by X-ray diffraction, electron microscopy, and photoluminescent spectroscopy. Photoluminescence was shown to be higher from samples synthesized in a CO2 plasma.
State-Level Estimates of Obesity-Attributable Costs of Absenteeism
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
International Nuclear Information System (INIS)
Yasuda, Kazunori; Hirai, Kazumasa
1980-01-01
This paper is concerned with the stabilization problem for bilinear systems by means of a linear state feedback. A bilinear system described by the equation x*(t) (*: radical) = Ax(t) + Σ(i -- r) u sub(i)(t)Bx(t) + Cu(t) is stabilizable by using a linear state feedback u = K sup(T)x(t), if the pair (A, C) is controllable; however, it is not generally stabilizable in the large. We, in this paper, give a sufficient condition under which the bilinear system is stabilizable in the large, and estimate quantitatively the extent of a stability region around the equilibrium state in the case that the system is not stabilizable in the large. Moreover, the behavior of the solution whose initial state is in the estimated stability region is considered. It is also shown that the stability region derived here is evaluated on a ground tighter than the previous ones. (author)
Use estimates of in-feed antimicrobials in swine production in the United States.
Apley, Michael D; Bush, Eric J; Morrison, Robert B; Singer, Randall S; Snelson, Harry
2012-03-01
When considering the development of antimicrobial resistance in food animals, comparing gross use estimates of different antimicrobials is of little value due to differences in potencies, duration of activity, relative effect on target and commensal bacteria, and mechanisms of resistance. However, it may be valuable to understand quantities of different antimicrobials used in different ages of swine and for what applications. Therefore, the objective of this project was to construct an estimate of antimicrobial use through the feed in swine production in the United States. Estimates were based on data from the National Animal Health Monitoring System (NAHMS) Swine 2006 Study and from a 2009 survey of swine-exclusive practitioners. Inputs consisted of number of pigs in a production phase, feed intake per day, dose of the antimicrobial in the feed, and duration of administration. Calculations were performed for a total of 102 combinations of antimicrobials (n=17), production phases (n=2), and reasons for use (n=3). Calculations were first conducted on farm-level data, and then extrapolated to the U.S. swine population. Among the nursery phase estimates, chlortetracycline had the largest estimate of use, followed by oxytetracycline and tilmicosin. In the grower/finisher phase, chlortetracycline also had the largest use estimate, followed by tylosin and oxytetracycline. As an annual industry estimate for all phases, chlortetracycline had the highest estimated use at 533,973 kg. The second and third highest estimates were tylosin and oxytetracycline with estimated annual uses of 165,803 kg and 154,956 kg, respectively. The estimates presented here were constructed to accurately reflect available data related to production practices, and to provide an example of a scientific approach to estimating use of compounds in production animals.
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.
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.
Carbon in U.S. forests and wood products, 1987-1997: state-by-state estimates
R.A. Birdsey; G.M. Lewis
2003-01-01
Estimated changes in carbon stocks are reported for the forests and wood products of the 50 U.S. States. Carbon stocks on forest land and in harvested wood products increased between 1987 and 1997 at an annual rate of 190 million metric tons. Most of this increase was in biomass, followed closely by wood products and landfills. Changes in land use since 1987 caused a...
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.
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
Energy Technology Data Exchange (ETDEWEB)
Shen, W.X. [School of Engineering, Monash University Malaysia, 2 Jalan Kolej, Bandar Sunway, 46150 Petaling Jaya, Selangor Darul Ehsan (Malaysia)
2007-02-15
This paper reviews recent definitions of the state of charge (SOC) that are often used to estimate the battery residual available capacity (BRAC) for lead-acid batteries in electric vehicles (EVs) and identifies their shortcomings. Then, the state of available capacity (SOAC), instead of the SOC, is defined to denote the BRAC in EVs, which refers to the percentage of the battery available capacity (BAC) of the discharge current profile for the EV battery at the fully charged state. Based on the experimentation of different discharge current profiles, including theoretical current profiles and practical current profiles under EV driving cycles, the discharged and regenerative capacity distribution is proposed to describe discharge current profiles for the SOAC estimation. Because of the complexity and nonlinearity of the relationship between the SOAC and the capacity distribution at different temperatures, a neural network (NN) is applied to this SOAC estimation. Comparisons between the estimated SOACs by the NN and the calculated SOACs from the experimental data are used for verification. The results confirm that the proposed approach can provide an accurate and effective estimation of the BRAC for lead-acid batteries in EVs. (author)
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.
Improved Stewart platform state estimation using inertial and actuator position measurements
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
Estimation of hand index for male industrial workers of Haryana State
African Journals Online (AJOL)
Hand index derived from measured hand dimensions can be used to estimate differences related to sex, age and race in forensic and legal sciences. It has been calculated as percentage of hand breadth over the hand length; which suggests that the male industrial workers population of state belong to mesocheir group of ...
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.
The Wegner estimate and the integrated density of states for some ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
-estimates on the spectral shift function related to the single-site perturbation. This result allows us to ... where ρ0 and C0 are positive functions that describe the unperturbed density and sound velocity. We assume that ρ0 and .... then the integrated density of states is locally Lipschitz continuous on . Concerning the second ...
Higher-order Multivariable Polynomial Regression to Estimate Human Affective 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.
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.
Wheeled vehicle deceleration as estimation parameter of adaptive brake control system state
Directory of Open Access Journals (Sweden)
Turenko A.
2012-06-01
Full Text Available The method of stability estimation of adaptive control system with signal adjustment based on Lyapunov’s direct method that allows to take into account the nonstationarity of the basic system and non-linearity in the form of limitation on control action restriction as well as error control is stated.
Energy Technology Data Exchange (ETDEWEB)
Piper, S.; Lee, L.K.
1989-06-01
Wind erosion contributes significantly to particulate air pollution in some regions of the Western United States. As a result, wind erosion imposes damages on households in the form of increased interior and exterior cleaning, reduced recreational opportunities, and impaired health. Costs are difficult to estimate because of limited data availability. However, damages appear to be much larger offsite than onsite.
The Wegner estimate and the integrated density of states for some ...
Indian Academy of Sciences (India)
The integrated density of states (IDS) for random operators is an important function describing many physical characteristics of a random system. Properties of the IDS are derived from the Wegner estimate that describes the influence of finite-volume perturbations on a background system. In this paper, we present a simple ...
Comparisons of Means for Estimating Sea States from an Advancing Large Container Ship
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Andersen, Ingrid Marie Vincent; Koning, Jos
2013-01-01
to ship-wave interactions in a seaway. In the paper, sea state estimates are produced by three means: the wave buoy analogy, relying on shipboard response measurements, a wave radar system, and a system providing the instantaneous wave height. The presented results show that for the given data, recorded...
The Wegner Estimate and the Integrated Density of States for some ...
Indian Academy of Sciences (India)
The integrated density of states (IDS) for random operators is an important function describing many physical characteristics of a random system. Properties of the IDS are derived from the Wegner estimate that describes the influence of finite-volume perturbations on a background system. In this paper, we present a simple ...
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 (...
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
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.
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
Zippel, Claus; Bohnet-Joschko, Sabine
2017-08-01
Medical devices play a central role in the diagnosis and treatment of diseases but also bring the potential for adverse events, hazards or malfunction with serious consequences for patients and users. Medical device manufacturers are therefore required by law to monitor the performance of medical devices that have been approved by the competent authorities (post market surveillance). Conducting a nationwide online-survey in the German medical device sector in Q2/2014 in order to explore the current status of the use of post market instruments we obtained a total of 118 complete data sets, for a return rate of 36%. The survey included manufacturers of different sizes, producing medical devices of all risk classes. The post market instruments most frequently reported covered the fields of production monitoring and quality management as well as literature observation, regulatory vigilance systems, customer knowledge management and market observation while Post Market Clinical Follow-up and health services research were being used less for product monitoring. We found significant differences between the different risk classes of medical devices produced and the intensity of use of post market instruments. Differences between company size and the intensity of instruments used were hardly detected. Results may well contribute to the development of device monitoring which is a crucial element of the policy and regulatory system to identify device-related safety issues. Copyright © 2017 Elsevier B.V. All rights reserved.
Optimal Estimate of a Pure Qubit State from Uhlmann-Josza Fidelity
Aoki, Manuel Avila
2012-04-01
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 us to obtaining 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.
Murphy, K. A.
1990-01-01
A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.
Composing Problem Solvers for Simulation Experimentation: A Case Study on Steady State Estimation
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. PMID:24705453
Gu, Yuanyuan; Norman, Richard; Viney, Rosalie
2014-09-01
Using discrete choice experiments (DCEs) to estimate health state utility values has become an important alternative to the conventional methods of Time Trade-Off and Standard Gamble. Studies using DCEs have typically used the conditional logit to estimate the underlying utility function. The conditional logit is known for several limitations. In this paper, we propose two types of models based on the mixed logit: one using preference space and the other using quality-adjusted life year (QALY) space, a concept adapted from the willingness-to-pay literature. These methods are applied to a dataset collected using the EQ-5D. The results showcase the advantages of using QALY space and demonstrate that the preferred QALY space model provides lower estimates of the utility values than the conditional logit, with the divergence increasing with worsening health states. Copyright © 2014 John Wiley & Sons, Ltd.
2017-01-01
This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations. PMID:28459848
Rana, Md Masud
2017-01-01
This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.
Directory of Open Access Journals (Sweden)
Md Masud Rana
Full Text Available This paper proposes an innovative internet of things (IoT based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.
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...
Current state of the regulatory trajectory for whole slide imaging devices in the USA
Directory of Open Access Journals (Sweden)
Esther Abels
2017-01-01
Full Text Available The regulatory field for digital pathology (DP has advanced significantly. A major milestone was accomplished when the FDA allowed the first vendor to market their device for primary diagnostic use in the USA and published in the classification order that this device, and substantially equivalent devices of this generic type, should be classified into class II instead of class III as previously proposed. The Digital Pathology Association (DPA regulatory task force had a major role in the accomplishment of getting the application request for Whole Slide Imaging (WSI Systems recommended for a de novo. This article reviews the past and emerging regulatory environment of WSI for clinical use in the USA. A WSI system with integrated subsystems is defined in the context of medical device regulations. The FDA technical performance assessment guideline is also discussed as well as parameters involved in analytical testing and clinical studies to demonstrate that WSI devices are safe and effective for clinical use.
Guidelines for preparation of State water-use estimates for 2015
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
Directory of Open Access Journals (Sweden)
Housila P. Singh
2015-04-01
Full Text Available In this paper, a simple and obvious procedure is presented that allows to estimate the population proportion Pi possessing sensitive attribute using simple random sampling with replacement (SRSWR. In addition to T, the probability that a respondent truthfully states that he or she bears a sensitive character when experienced in a direct response survey. An efficiency comparison is carried out to investigate in the performance of the proposed method. It is found that the proposed strategy is more efficient than Warner’s (1965 as well as Huang’s (2004 randomized response techniques under some realistic conditions. Numerical illustrations and graphical representations are also given in support of the present study.
Directory of Open Access Journals (Sweden)
Zhang Zhi
2015-12-01
Full Text Available Since the features of low energy consumption and limited power supply are very important for wireless sensor networks (WSNs, the problems of distributed state estimation with quantized innovations are investigated in this paper. In the first place, the assumptions of prior and posterior probability density function (PDF with quantized innovations in the previous papers are analyzed. After that, an innovative Gaussian mixture estimator is proposed. On this basis, this paper presents a Gaussian mixture state estimation algorithm based on quantized innovations for WSNs. In order to evaluate and compare the performance of this kind of state estimation algorithms for WSNs, the posterior Cramér–Rao lower bound (CRLB with quantized innovations is put forward. Performance analysis and simulations show that the proposed Gaussian mixture state estimation algorithm is efficient than the others under the same number of quantization levels and the performance of these algorithms can be benchmarked by the theoretical lower bound.
Toward inventory-based estimates of soil organic carbon in forests of the United States.
Domke, G M; Perry, C H; Walters, B F; Nave, L E; Woodall, C W; Swanston, C W
2017-06-01
Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on Earth; this pool plays a critical role in ecosystem processes and climate change. Given the cost and time required to measure SOC, and particularly changes in SOC, many signatory nations to the United Nations Framework Convention on Climate Change report estimates of SOC stocks and stock changes using default values from the Intergovernmental Panel on Climate Change or country-specific models. In the United States, SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the U.S. Department of Agriculture, Forest Service. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forest land in the conterminous United States and southeast and southcentral coastal Alaska. That said, the FIA program has been using country-specific predictions of SOC based, in part, upon a model using SOC estimates from the State Soil Geographic (STATSGO) database compiled by the Natural Resources Conservation Service. Estimates obtained from the STATSGO database are averages over large map units and are not expected to provide accurate estimates for specific locations, e.g., NFI plots. To improve the accuracy of SOC estimates in U.S. forests, NFI SOC observations were used for the first time to predict SOC density to a depth of 100 cm for all forested NFI plots. Incorporating soil-forming factors along with observations of SOC into a new estimation framework resulted in a 75% (48 ± 0.78 Mg/ha) increase in SOC densities nationally. This substantially increases the contribution of the SOC pool, from approximately 44% (17 Pg) of the total forest ecosystem C stocks to 56% (28 Pg), in the forest C budget of the United States. © 2017 by the Ecological Society of America.
Wexler, Anna
2015-11-01
Several recent articles have called for the regulation of consumer transcranial direct current stimulation (tDCS) devices, which provide low levels of electrical current to the brain. However, most of the discussion to-date has focused on ethical or normative considerations; there has been a notable absence of scholarship regarding the actual legal framework in the United States. This article aims to fill that gap by providing a pragmatic analysis of the consumer tDCS market and relevant laws and regulations. In the five main sections of this manuscript, I take into account (a) the history of the do-it-yourself tDCS movement and the subsequent emergence of direct-to-consumer devices; (b) the statutory language of the Federal Food, Drug and Cosmetic Act and how the definition of a medical device-which focuses on the intended use of the device rather than its mechanism of action-is of paramount importance for discussions of consumer tDCS device regulation; (c) how both the Food and Drug Administration (FDA) and courts have understood the FDA's jurisdiction over medical devices in cases where the meaning of 'intended use' has been challenged; (d) an analysis of consumer tDCS regulatory enforcement action to-date; and (e) the multiple US authorities, other than the FDA, that can regulate consumer brain stimulation devices. Taken together, this paper demonstrates that rather than a 'regulatory gap,' there are multiple, distinct pathways by which consumer tDCS can be regulated in the United States.
Nonlinear State Estimation and Control for Chaos Suppression in MEMS Resonator
Directory of Open Access Journals (Sweden)
Angelo Marcelo Tusset
2013-01-01
Full Text Available During the last decade the chaotic behavior in MEMS resonators have been reported in a number of works. Here, the chaotic behavior of a micro-mechanical resonator is suppressed. The aim is to control the system forcing it to an orbit of the analytical solution obtained by the multiple scales method. The State Dependent Riccati Equation (SDRE and the Optimal Linear Feedback Control (OLFC strategies are used for controlling the trajectory of the system. Additionally, the SDRE technique is used in the state estimator design. The state estimation and the control techniques proved to be effective in controlling the trajectory of the system. Additionally, the robustness of the control strategies are tested considering parametric errors and measurement noise in the control loop.
Gan, L.; Yang, F.; Shi, Y. F.; He, H. L.
2017-11-01
Many occasions related to batteries demand to know how much continuous and instantaneous power can batteries provide such as the rapidly developing electric vehicles. As the large-scale applications of lithium-ion batteries, lithium-ion batteries are used to be our research object. Many experiments are designed to get the lithium-ion battery parameters to ensure the relevance and reliability of the estimation. To evaluate the continuous and instantaneous load capability of a battery called state-of-function (SOF), this paper proposes a fuzzy logic algorithm based on battery state-of-charge(SOC), state-of-health(SOH) and C-rate parameters. Simulation and experimental results indicate that the proposed approach is suitable for battery SOF estimation.
Application of Joint Parameter Identification and State Estimation to a Fault-Tolerant Robot System
DEFF Research Database (Denmark)
Sun, Zhen; Yang, Zhenyu
2011-01-01
, it would further simplify the reconfigurable design task and possibly speed up the system recovery, if the system state information under the new operating circumstance can be available along with faulty parameter information. The joint parameter identification and state estimation using the combined......The joint parameter identification and state estimation technique is applied to develop a fault-tolerant space robot system. The potential faults in the considered system are abrupt parametric faults, which indicate that some system parameters will immediately deviate from their nominal values...... if a fault happens. The concerned system parameters consist of deterministic parts as well as those describing the stochastic features in the system. Due to the purpose for design of reconfigurable control, these deviated system parameters need to be identified as precisely and quickly as possible. Meanwhile...
Basin, M.; Maldonado, J. J.; Zendejo, O.
2016-07-01
This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.
Improving Google Flu Trends estimates for the United States through transformation.
Martin, Leah J; Xu, Biying; Yasui, Yutaka
2014-01-01
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.
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.
Yi, Xiaohui; Shang, Jie; Pan, Liang; Tan, Hongwei; Chen, Bin; Liu, Gang; Huang, Gang; Bernot, Kevin; Guillou, Olivier; Li, Run-Wei
2016-06-22
Switching luminescence of lanthanide-based molecules through an external electric field is considered as a promising approach toward novel functional molecule-based devices. Classic routes use casted films and liquid electrolyte as media for redox reactions. Such protocol, even if efficient, is relatively hard to turn into an effective solid-state device. In this work, we explicitly synthesize lanthanide-based dimers whose luminescent behavior is affected by the presence of Cu(2+) ions. Excellent evaporability of the dimers and utilization of Cu(2+)-based solid-state electrolyte makes it possible to reproduce solution behavior at the solid state. Reversible modulation of Cu(2+) ions transport can be achieved by an electric field in a solid-state device, where lanthanide-related luminescence is driven by an electric field. These findings provide a proof-of-concept alternative approach for electrically driven modulation of solid-state luminescence and show promising potential for information storage media in the future.
Estimate of the area occupied by reforestation programs in Rio de Janeiro state
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Hugo Barbosa Amorim
2012-03-01
Full Text Available This study was based on a preliminary survey and inventory of existing reforestation programs in Rio de Janeiro state, through geoprocessing techniques and collection of field data. The reforested area was found to occupy 18,426.96 ha, which amounts to 0.42% of the territory of the state. Much of reforestation programs consists of eucalyptus (98%, followed by pine plantations (0.8%, and the remainder is distributed among 10 other species. The Médio Paraíba region was found to contribute the most to the reforested area of the state (46.6%. The estimated volume of eucalyptus timber was nearly two million cubic meters. This study helped crystallize the ongoing perception among those militating in the forestry sector of Rio de Janeiro state that the planted area and stock of reforestation timber is still incipient in the state.
Department of Homeland Security — This report presents estimates of the size and characteristics of the resident nonimmigrant population in the United States. The estimates are daily averages for the...
U.S. Department of Health & Human Services — 2010-2015. U.S. Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates are based on the 2010 Census...
U.S. Department of Health & Human Services — 2010-2016. U.S. Census Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States. The estimates are based on the 2010 Census...
Zhang, Xu; Wang, Yujie; Liu, Chang; Chen, Zonghai
2018-02-01
An accurate battery pack state of health (SOH) estimation is important to characterize the dynamic responses of battery pack and ensure the battery work with safety and reliability. However, the different performances in battery discharge/charge characteristics and working conditions in battery pack make the battery pack SOH estimation difficult. In this paper, the battery pack SOH is defined as the change of battery pack maximum energy storage. It contains all the cells' information including battery capacity, the relationship between state of charge (SOC) and open circuit voltage (OCV), and battery inconsistency. To predict the battery pack SOH, the method of particle swarm optimization-genetic algorithm is applied in battery pack model parameters identification. Based on the results, a particle filter is employed in battery SOC and OCV estimation to avoid the noise influence occurring in battery terminal voltage measurement and current drift. Moreover, a recursive least square method is used to update cells' capacity. Finally, the proposed method is verified by the profiles of New European Driving Cycle and dynamic test profiles. The experimental results indicate that the proposed method can estimate the battery states with high accuracy for actual operation. In addition, the factors affecting the change of SOH is analyzed.
Estimating the State of Aerodynamic Flows in the Presence of Modeling Errors
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).
Parameter and state estimation in a Neisseria meningitidis model: A study case of Niger
Bowong, S.; Mountaga, L.; Bah, A.; Tewa, J. J.; Kurths, J.
2016-12-01
Neisseria meningitidis (Nm) is a major cause of bacterial meningitidis outbreaks in Africa and the Middle East. The availability of yearly reported meningitis cases in the African meningitis belt offers the opportunity to analyze the transmission dynamics and the impact of control strategies. In this paper, we propose a method for the estimation of state variables that are not accessible to measurements and an unknown parameter in a Nm model. We suppose that the yearly number of Nm induced mortality and the total population are known inputs, which can be obtained from data, and the yearly number of new Nm cases is the model output. We also suppose that the Nm transmission rate is an unknown parameter. We first show how the recruitment rate into the population can be estimated using real data of the total population and Nm induced mortality. Then, we use an auxiliary system called observer whose solutions converge exponentially to those of the original model. This observer does not use the unknown infection transmission rate but only uses the known inputs and the model output. This allows us to estimate unmeasured state variables such as the number of carriers that play an important role in the transmission of the infection and the total number of infected individuals within a human community. Finally, we also provide a simple method to estimate the unknown Nm transmission rate. In order to validate the estimation results, numerical simulations are conducted using real data of Niger.
Online Kinematic and Dynamic-State Estimation for Constrained Multibody Systems Based on IMUs
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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.
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...... with consideration of voltage performance and load characteristic is developed. Then, a Kalman-Filter-Based state estimation method is proposed to estimate system information instead of using communication facilities, where the estimator of each DG unit can dynamically obtain information of all the DG units as well...... as network voltages just by local voltage and current itself. The proposed estimation method is able to provide accurate states information to support system operation without any communication facilities. Simulation and experimental results are given for validating the proposed small signal model and state...
Estimating mercury emissions resulting from wildfire in forests of the Western United States.
Webster, Jackson P; Kane, Tyler J; Obrist, Daniel; Ryan, Joseph N; Aiken, George R
2016-10-15
Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100±1900kg-Hgy(-1) for the years spanning 2000-2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating (severity burns ranged from 58 to 640μg-Hgkg-fuel(-1). In contrast, low severity burns have emission factors that are estimated to be only 18-34μg-Hgkg-fuel(-1). In this estimate, wildfire is predicted to release 1-30gHgha(-1) from Western United States forest soils while above ground fuels are projected to contribute an additional 0.9 to 7.8gHgha(-1). Land cover types with low biomass (desert scrub) are projected to release less than 1gHgha(-1). Following soil sources, fuel source contributions to total Hg emissions generally followed the order of duff>wood>foliage>litter>branches. Copyright © 2016 Elsevier B.V. All rights reserved.
Thermoelectric Devices: Solid-State Refrigerators and Electrical Generators in the Classroom
Winder, Edmund J.; Ellis, Arthur B.; Lisensky, George C.
1996-10-01
Thermoelectric devices are solid-state devices that convert thermal energy from a temperature gradient into electrical energy (the Seebeck effect) or convert electrical energy into a temperature gradient (the Peltier effect). The first application is used most notably in spacecraft power generation systems (for example, in Voyager I and II) and in thermocouples for temperature measurement, while the second application is largely used in specialized cooling applications. Both applications can be demonstrated in the lecture hall to illustrate thermodynamic principles in a compelling manner. They also provide insight into the workings of a high-tech system that is achieving more widespread consumer use. The most visible consumer use of thermoelectric devices utilizing the Peltier effect is in portable electric food coolers/warmers that plug into an automobile cigarette lighter. Conventional cooling systems such as those used in refrigerators utilize a compressor and a working fluid to transfer heat. Thermal energy is absorbed and released as the working fluid undergoes expansion and compression and changes phase from liquid to vapor and back, respectively (1). Semiconductor thermoelectric coolers (also known as Peltier coolers) offer several advantages over conventional systems. They are entirely solid-state devices, with no moving parts; this makes them rugged, reliable, and quiet. They use no ozone-depleting chlorofluorocarbons, potentially offering a more environmentally responsible alternative to conventional refrigeration. They can be extremely compact, much more so than compressor-based systems. Precise temperature control (finned aluminum heat sinks attached to both sides; one of these has to be detached in order to remove the module from the lid. The heat sink is then reattached to the module, as shown in Figure 1. Figure 1. Thermoelectric module with attached heat sinks, from a disassembled portable food cooler. The smaller heat sink provides cooling to the
State, Parameter, and Unknown Input Estimation Problems in Active Automotive Safety Applications
Phanomchoeng, Gridsada
A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is
ORAL CANCER SITUATION IN THE STATE OF BAHIA: ESTIMATES AND ACTION PERSPECTIVES
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Suélem Maria Santana Pinheiro
2009-04-01
Full Text Available Cancer is actually a challenge to Brazilian Public Health, once the number of new cases is growing in last decades. Some studies show that cancer was responsible for 12% of causa mortis in the World, achieving six millions of deaths per year. The aim of this study was to compare oral cancer estimates for Brasil and Bahia state in the years 2006/2007 and 2008/2009, to see the possible evolution of this pathology in the periods and, at same time, find perspectives of action for disease control. For this objective, it was searched the Instituto Nacional do Cancer database for oral cancer Situação do câncer bucal no Estado da Bahia: estimativas e perspectivas de ação incidence estimates for the cited years, observing segregation for sex variable. This way, it was possible to compare both estimates. It was observed in Brasil an increase in the estimated crude incidence rates per 100.000 individuals, with a value of 3,58 in 2006/2007 going to 3,8 in 2008/2009 for females and 10,91 to 11,00 in males. In the state of Bahia, the estimated crude incidence rates increased 2,86 to 3,25 among females and 7,15 to 7,28 among males. However, specifically for the city of Salvador it was noted a decrease in incidence estimates, once the estimated crude incidence rate was 16,00 in 2006/2007 and 14,20 in 2008/2009 for males and 5,72 to 5,21 in females. Educative actions involving health professionals such as physicians, dentists, nurses, health agents and media campaigns that make possible early diagnosis and adoption of preventive measures, consequently improving survival rates and life quality in affected population.
Estimating earthquake magnitudes from reported intensities in the central and eastern United States
Boyd, Oliver; Cramer, Chris H.
2014-01-01
A new macroseismic intensity prediction equation is derived for the central and eastern United States and is used to estimate the magnitudes of the 1811–1812 New Madrid, Missouri, and 1886 Charleston, South Carolina, earthquakes. This work improves upon previous derivations of intensity prediction equations by including additional intensity data, correcting magnitudes in the intensity datasets to moment magnitude, and accounting for the spatial and temporal population distributions. The new relation leads to moment magnitude estimates for the New Madrid earthquakes that are toward the lower range of previous studies. Depending on the intensity dataset to which the new macroseismic intensity prediction equation is applied, mean estimates for the 16 December 1811, 23 January 1812, and 7 February 1812 mainshocks, and 16 December 1811 dawn aftershock range from 6.9 to 7.1, 6.8 to 7.1, 7.3 to 7.6, and 6.3 to 6.5, respectively. One‐sigma uncertainties on any given estimate could be as high as 0.3–0.4 magnitude units. We also estimate a magnitude of 6.9±0.3 for the 1886 Charleston, South Carolina, earthquake. We find a greater range of magnitude estimates when also accounting for multiple macroseismic intensity prediction equations. The inability to accurately and precisely ascertain magnitude from intensities increases the uncertainty of the central United States earthquake hazard by nearly a factor of two. Relative to the 2008 national seismic hazard maps, our range of possible 1811–1812 New Madrid earthquake magnitudes increases the coefficient of variation of seismic hazard estimates for Memphis, Tennessee, by 35%–42% for ground motions expected to be exceeded with a 2% probability in 50 years and by 27%–35% for ground motions expected to be exceeded with a 10% probability in 50 years.
Estimating the impact of newly arrived foreign-born persons on tuberculosis in the United States.
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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.
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
2015-01-01
Several recent articles have called for the regulation of consumer transcranial direct current stimulation (tDCS) devices, which provide low levels of electrical current to the brain. However, most of the discussion to-date has focused on ethical or normative considerations; there has been a notable absence of scholarship regarding the actual legal framework in the United States. This article aims to fill that gap by providing a pragmatic analysis of the consumer tDCS market and relevant laws and regulations. In the five main sections of this manuscript, I take into account (a) the history of the do-it-yourself tDCS movement and the subsequent emergence of direct-to-consumer devices; (b) the statutory language of the Federal Food, Drug and Cosmetic Act and how the definition of a medical device—which focuses on the intended use of the device rather than its mechanism of action—is of paramount importance for discussions of consumer tDCS device regulation; (c) how both the Food and Drug Administration (FDA) and courts have understood the FDA's jurisdiction over medical devices in cases where the meaning of ‘intended use’ has been challenged; (d) an analysis of consumer tDCS regulatory enforcement action to-date; and (e) the multiple US authorities, other than the FDA, that can regulate consumer brain stimulation devices. Taken together, this paper demonstrates that rather than a ‘regulatory gap,’ there are multiple, distinct pathways by which consumer tDCS can be regulated in the United States. PMID:27774217
Extended Kalman Filter with a Fuzzy Method for Accurate Battery Pack State of Charge Estimation
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Saeed Sepasi
2015-06-01
Full Text Available As the world moves toward greenhouse gas reduction, there is increasingly active work around Li-ion chemistry-based batteries as an energy source for electric vehicles (EVs, hybrid electric vehicles (HEVs and smart grids. In these applications, the battery management system (BMS requires an accurate online estimation of the state of charge (SOC in a battery pack. This estimation is difficult, especially after substantial battery aging. In order to address this problem, this paper utilizes SOC estimation of Li-ion battery packs using a fuzzy-improved extended Kalman filter (fuzzy-IEKF for Li-ion cells, regardless of their age. The proposed approach introduces a fuzzy method with a new class and associated membership function that determines an approximate initial value applied to SOC estimation. Subsequently, the EKF method is used by considering the single unit model for the battery pack to estimate the SOC for following periods of battery use. This approach uses an adaptive model algorithm to update the model for each single cell in the battery pack. To verify the accuracy of the estimation method, tests are done on a LiFePO4 aged battery pack consisting of 120 cells connected in series with a nominal voltage of 432 V.
An Energy-Based Limit State Function for Estimation of Structural Reliability in Shock Environments
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Michael A. Guthrie
2013-01-01
Full Text Available limit state function is developed for the estimation of structural reliability in shock environments. This limit state function uses peak modal strain energies to characterize environmental severity and modal strain energies at failure to characterize the structural capacity. The Hasofer-Lind reliability index is briefly reviewed and its computation for the energy-based limit state function is discussed. Applications to two degree of freedom mass-spring systems and to a simple finite element model are considered. For these examples, computation of the reliability index requires little effort beyond a modal analysis, but still accounts for relevant uncertainties in both the structure and environment. For both examples, the reliability index is observed to agree well with the results of Monte Carlo analysis. In situations where fast, qualitative comparison of several candidate designs is required, the reliability index based on the proposed limit state function provides an attractive metric which can be used to compare and control reliability.
Directory of Open Access Journals (Sweden)
Angelica Cifarelli
2016-11-01
Full Text Available A new architecture of organic memristive device is proposed with a double-layered polyelectrolyte, one of which is a biological system that alone drives the memristive behavior. In the device the Physarum polycephalum was used as living organism, the polyaniline as conducting polymer for the source-drain channel. The key choice for the device functioning was the interposition of a biocompatible solid layer between polyaniline and living organism, that must result both electrochemically inert and able to preserve a good electrical conductivity of the polyaniline, notwithstanding the alkaline pH environment required for the surviving of living being, by avoiding strong acids. Pectin with a high degree of methylation and chitosan were tested as interlayer, but only the first one satisfied the essential requirements. It was demonstrated that only when the living organism was integrated in the device, the current-voltage characteristics showed the hysteretic rectifying trends typical of the memristive devices, which however disappeared if the Physarum polycephalum switched to its sclerotic state. The mould resulted to survive a series of at least three cycles of voltage-current measurements carried out in sequence.
Battery State-of-Charge and Parameter Estimation Algorithm Based on Kalman Filter
DEFF Research Database (Denmark)
Dragicevic, Tomislav; Sucic, Stjepan; Guerrero, Josep M.
2013-01-01
Electrochemical battery is the most widely used energy storage technology, finding its application in various devices ranging from low power consumer electronics to utility back-up power. All types of batteries show highly non-linear behaviour in terms of dependence of internal parameters...... on operating conditions, momentary replenishment and a number of past charge/discharge cycles. A good indicator for the quality of overall customer service in any battery based application is the availability and reliability of these informations, as they point out important runtime variables...... such as the actual state of charge (SOC) and state of health (SOH). Therefore, a modern battery management systems (BMSs) should incorporate functions that accommodate real time tracking of these nonlinearities. For that purpose, Kalman filter based algorithms emerged as a convenient solution due to their ability...
The importance of Fe interface states for ferromagnet-semiconductor based spintronic devices
Chantis, Athanasios
2009-03-01
I present our recent theoretical studies of the bias-controlled spin injection, detection sensitivity and tunneling anisotropic magnetoresistance in ferromagnetic-semiconductor tunnel junctions. Using first-principles electron transport methods we have shown that Fe 3d minority-spin surface (interface) states are responsible for at least two important effects for spin electronics. First, they can produce a sizable Tunneling Anisotropic Magnetoresistance in magnetic tunnel junctions with a single Fe electrode. The effect is driven by a Rashba shift of the resonant surface band when the magnetization changes direction. This can introduce a new class of spintronic devices, namely, Tunneling Magnetoresistance junctions with a single ferromagnetic electrode that can function at room temperatures. Second, in Fe/GaAs(001) magnetic tunnel junctions they produce a strong dependence of the tunneling current spin-polarization on applied electrical bias. A dramatic sign reversal within a voltage range of just a few tenths of an eV is found. This explains the observed sign reversal of spin-polarization in recent experiments of electrical spin injection in Fe/GaAs(001) and related reversal of tunneling magnetoresistcance through vertical Fe/GaAs/Fe trilayers. We also present a theoretical description of electrical spin-detection at a ferromagnet/semiconductor interface. We show that the sensitivity of the spin detector has strong bias dependence which, in the general case, is dramatically different from that of the tunneling current spin-polarization. We show that in realistic ferromagnet/semiconductor junctions this bias dependence can originate from two distinct physical mechanisms: 1) the bias dependence of tunneling current spin-polarization, which is of microscopic origin and depends on the specific properties of the interface, and 2) the macroscopic electron spin transport properties in the semiconductor. Our numerical results show that the magnitude of the voltage signal
Estimation of live birth and population prevalence of Down syndrome in nine U.S. states.
de Graaf, Gert; Buckley, Frank; Dever, Jennifer; Skotko, Brian G
2017-10-01
For all of the U.S. states with sufficient data, we estimated live birth and population prevalences for Down syndrome (DS). As social service resources vary between states, such data are important for public policy discussions and state planning. We predicted the actual and nonselective live birth prevalence, and population prevalence, for DS in nine U.S. states based on publicly available datasets from the Centers for Disease Control and Prevention and the Integrated Public Use Microdata Series. As of 2010, we estimated a population size for people with DS of 4,554 in MA (population prevalence 1 in 1,440), 6,101 in NJ (1 in 1,443), 14,315 in NY (1 in 1,355), 9,739 in IL (1 in 1,319), 4,354 in IN (1 in 1,491), 7,295 in MI (1 in 1,354), 9,099 in FL (1 in 2,071), 3,014 in KY (1 in 1,442), and 3,596 in AZ (1 in 1,784). The number of people living with DS has steadily increased from 1950 until 2010 in these nine U.S. states. Population prevalence would have been higher absent DS-related elective terminations. Racial and ethnic groups, other than non-Hispanic whites, comprise a growing proportion within these DS communities, particularly among younger-aged persons. © 2017 Wiley Periodicals, Inc.
A Review of Sea State Estimation Procedures Based on Measured Vessel Responses
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam
2016-01-01
buoys are not practical, as sea state information in real-time and at the actual geographical position of the ship is needed. On the other hand, the analogy between a ship and a floating buoy naturally suggests to using the ship itself as a wave buoy. This paper presents a status on techniques...... for shipboard SSE using measured vessel responses, resembling the concept of traditional wave rider buoys. Moreover, newly developed ideas for shipboard sea state estimation are introduced. The presented material is all based on the author’s personal experience, developed within extensive work on the subject...
DEFF Research Database (Denmark)
Chen, Xiaoshuang; Lin, Jin; Wan, Can
2016-01-01
State estimation (SE) in distribution networks is not as accurate as that in transmission networks. Traditionally, distribution networks (DNs) are lack of direct measurements due to the limitations of investments and the difficulties of maintenance. Therefore, it is critical to improve the accuracy...... of SE in distribution networks by placing additional physical meters. For state-of-the-art SE models, it is difficult to clearly quantify measurements' influences on SE errors, so the problems of optimal meter placement for reducing SE errors are mostly solved by heuristic or suboptimal algorithms...
Directory of Open Access Journals (Sweden)
Fábio A. Miessi Sanches
2009-03-01
Full Text Available In this paper we set up a model of regional banking competition based on Bresnahan (1982, Lau (1982 and Nakane (2002. The structural model is estimated using data from eight Brazilian states and a dynamic panel. The results show that on average the level of competition in the Brazilian banking system is high, even tough the null of perfect competition can be rejected at the usual significance levels. This result also prevails at the state level: Rio Grande do Sul, São Paulo, Rio de Janeiro, Pernambuco and Minas Gerais have high degree of competition.
Recursive prediction error methods for online estimation in nonlinear state-space models
Directory of Open Access Journals (Sweden)
Dag Ljungquist
1994-04-01
Full Text Available Several recursive algorithms for online, combined state and parameter estimation in nonlinear state-space models are discussed in this paper. Well-known algorithms such as the extended Kalman filter and alternative formulations of the recursive prediction error method are included, as well as a new method based on a line-search strategy. A comparison of the algorithms illustrates that they are very similar although the differences can be important for the online tracking capabilities and robustness. Simulation experiments on a simple nonlinear process show that the performance under certain conditions can be improved by including a line-search strategy.
Practical microwave electron devices
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.
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)
Energy Technology Data Exchange (ETDEWEB)
Zhou, Ning [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Huang, Zhenyu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Meng, Da [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elbert, Stephen T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wang, Shaobu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Diao, Ruisheng [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2014-03-31
With the increasing complexity resulting from uncertainties and stochastic variations introduced by intermittent renewable energy sources, responsive loads, mobile consumption of plug-in vehicles, and new market designs, more and more dynamic behaviors are observed in everyday power system operation. To operate a power system efficiently and reliably, it is critical to adopt a dynamic paradigm so that effective control actions can be taken in time. The dynamic paradigm needs to include three fundamental components: dynamic state estimation; look-ahead dynamic simulation; and dynamic contingency analysis (Figure 1). These three components answer three basic questions: where the system is; where the system is going; and how secure the system is against accidents. The dynamic state estimation provides a solid cornerstone to support the other 2 components and is the focus of this study.
Lee, Justin J; Gondhalekar, Ravi; Doyle, Francis J
2014-12-01
A zone model predictive control (zone-MPC) algorithm that utilizes the Moving Horizon State Estimator (MHSE) is presented. The control application is an artificial pancreas for treating people with type 1 diabetes mellitus. During the meal challenge, the prediction quality of the zone-MPC algorithm with the MHSE was significantly better than when using the current Luenberger observer to provide the state estimate. Consequently, the controller using the MHSE rejected the meal disturbance faster and without inducing extra hypoglycemia risk (e.g., lower postprandial blood glucose peak by 10 mg/dL and higher postprandial minimum blood glucose by 11 mg/dL). The faster rejection of the meal disturbance led to a longer time in the clinically accepted safe region (70-180 mg/dL) by 13%, and this may reduce the likelihood of the complications related to type 1 diabetes mellitus.
Kalman-variant estimators for state of charge in lithium-sulfur batteries
DEFF Research Database (Denmark)
Propp, Karsten; Auger, Daniel J.; Fotouhi, Abbas
2017-01-01
Lithium-sulfur batteries are now commercially available, offering high specific energy density, low production costs and high safety. However, there is no commercially-available battery management system for them, and there are no published methods for determining state of charge in situ....... This paper describes a study to address this gap. The properties and behaviours of lithium-sulfur are briefly introduced, and the applicability of ‘standard’ lithium-ion state-of-charge estimation methods is explored. Open-circuit voltage methods and ‘Coulomb counting’ are found to have a poor fit...... for lithium-sulfur, and model-based methods, particularly recursive Bayesian filters, are identified as showing strong promise. Three recursive Bayesian filters are implemented: an extended Kalman filter (EKF), an unscented Kalman filter (UKF) and a particle filter (PF). These estimators are tested through...
Energy Technology Data Exchange (ETDEWEB)
Chen, Yousu; Glaesemann, Kurt R.; Rice, Mark J.; Huang, Zhenyu
2015-12-31
Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.
Projection-based circular constrained state estimation and fusion over long-haul links
Energy Technology Data Exchange (ETDEWEB)
Liu, Qiang [ORNL; Rao, Nageswara S. [ORNL
2017-07-01
In this paper, we consider a scenario where sensors are deployed over a large geographical area for tracking a target with circular nonlinear constraints on its motion dynamics. The sensor state estimates are sent over long-haul networks to a remote fusion center for fusion. We are interested in different ways to incorporate the constraints into the estimation and fusion process in the presence of communication loss. In particular, we consider closed-form projection-based solutions, including rules for fusing the estimates and for incorporating the constraints, which jointly can guarantee timely fusion often required in realtime systems. We test the performance of these methods in the long-haul tracking environment using a simple example.
Nonlinear neural network for hemodynamic model state and input estimation using fMRI data
Karam, Ayman M.
2014-11-01
Originally inspired by biological neural networks, artificial neural networks (ANNs) are powerful mathematical tools that can solve complex nonlinear problems such as filtering, classification, prediction and more. This paper demonstrates the first successful implementation of ANN, specifically nonlinear autoregressive with exogenous input (NARX) networks, to estimate the hemodynamic states and neural activity from simulated and measured real blood oxygenation level dependent (BOLD) signals. Blocked and event-related BOLD data are used to test the algorithm on real experiments. The proposed method is accurate and robust even in the presence of signal noise and it does not depend on sampling interval. Moreover, the structure of the NARX networks is optimized to yield the best estimate with minimal network architecture. The results of the estimated neural activity are also discussed in terms of their potential use.
The use of externality estimates in the calculation of adders by state PUC regulators
International Nuclear Information System (INIS)
Burtraw, D.; Palmer, K.; Krupnick, A.
1994-01-01
The primary focus of the U. S.-EC study is the development and illustration of methodologies for the estimation of marginal damages and associated externalities that result from the addition of electricity generating capacity in a specific reference environment. This paper describes how this information can be used to guide resource planning by electric utilities and State public utility commissions (PUCs). First, we discuss the 'second-best' policy environment in which PUCs must operate. We then discuss the use of 'adders' which are a policy tool that many PUCs are currently considering. Then, we introduce and estimate a formal model to calibrate these adders, based on estimates of externalities in order to promote economic efficiency in resource planning and investment decisions
State-Space Dynamic Model for Estimation of Radon Entry Rate, based on Kalman Filtering
Czech Academy of Sciences Publication Activity Database
Brabec, Marek; Jílek, K.
2007-01-01
Roč. 98, - (2007), s. 285-297 ISSN 0265-931X Grant - others:GA SÚJB JC_11/2006 Institutional research plan: CEZ:AV0Z10300504 Keywords : air ventilation rate * radon entry rate * state-space modeling * extended Kalman filter * maximum likelihood estimation * prediction error decomposition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.963, year: 2007
Recall of severe hypoglycaemia and self-estimated state of awareness in type 1 diabetes
DEFF Research Database (Denmark)
Pedersen-Bjergaard, Ulrik; Pramming, Stig; Thorsteinsson, Birger
2003-01-01
retrospectively at the end of the study was compared to the prospectively recorded rate during the study period. Self-estimated awareness was explored in questionnaires at baseline and at the end, and assessments were evaluated by the occurrence of severe hypoglycaemic episodes. RESULTS: Almost 90.......001). CONCLUSION: People with type 1 diabetes generally remember severe hypoglycaemic episodes during a one-year period. A simple method is proposed for classifying the state of awareness of hypoglycaemia in clinical practice....
Estimating Renewable Energy Economic Potential in the United States: Methodology and Initial Results
Energy Technology Data Exchange (ETDEWEB)
Brown, Austin [National Renewable Energy Lab. (NREL), Golden, CO (United States); Beiter, Philipp [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heimiller, Donna [National Renewable Energy Lab. (NREL), Golden, CO (United States); Davidson, Carolyn [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Melius, Jennifer [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lopez, Anthony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Hettinger, Dylan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mulcahy, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Porro, Gian [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2016-08-01
The report describes a geospatial analysis method to estimate the economic potential of several renewable resources available for electricity generation in the United States. Economic potential, one measure of renewable generation potential, is defined in this report as the subset of the available resource technical potential where the cost required to generate the electricity (which determines the minimum revenue requirements for development of the resource) is below the revenue available in terms of displaced energy and displaced capacity.
Reconsidering the smart metering data collection frequency for distribution state estimation
Chen, Qipeng; Kaleshi, Dritan; Armour, Simon; Fan, Zhong
2015-01-01
The current UK Smart Metering Technical Specification requires smart meter readings to be collected once a day, primarily to support accurate billing without violating users' privacy. In this paper we consider the use of Smart Metering data for Distribution State Estimation (DSE), and compare the effectiveness of daily data collection strategy with a more frequent, half-hourly SM data collection strategy. We first assess the suitability of using the data for load forecasting at Low Voltage (L...
Directory of Open Access Journals (Sweden)
A.P. Rytik
2009-12-01
Full Text Available Temperature reaction of distant phalanges in the case of the occlusive test has been registered. It has been revealed that the temperature reaction on the occlusive test for the group of patients with disturbances of vessel tone regulation differs from the reaction of norm group. Possible influence of vessel regulation state and volumetric blood supply on the skin temperature dynamics has been estimated. Diagnostic ability of the temperature occlusive test has been investigated
A.P. Rytik; E.V. Miroshnichenko; A.A. Sagaidachnyi; A.V. Skripal; A.A. Protopopov; D.A. Usanov
2009-01-01
Temperature reaction of distant phalanges in the case of the occlusive test has been registered. It has been revealed that the temperature reaction on the occlusive test for the group of patients with disturbances of vessel tone regulation differs from the reaction of norm group. Possible influence of vessel regulation state and volumetric blood supply on the skin temperature dynamics has been estimated. Diagnostic ability of the temperature occlusive test has been investigated
Fotouhi, Abbas; Propp, Karsten; Auger, Daniel J.
2015-01-01
This paper describes a study demonstrating a new method of state-of-charge (SoC) estimation for batteries in real-world electric vehicle applications. This method combines realtime model identification with an adaptive neuro-fuzzy inference system (ANFIS). In the study, investigations were carried down on a small-scale battery pack. An equivalent circuit network model of the pack was developed and validated using pulse-discharge experiments. The pack was then subjected to demands representing...
Catalano, Mario; Lo Casto, Barbara; Migliore, Marco
2008-01-01
The research deals with the use of the stated preference technique (SP) and transport demand modelling to analyse travel mode choice behaviour for commuting urban trips in Palermo, Italy. The principal aim of the study was the calibration of a demand model to forecast the modal split of the urban transport demand, allowing for the possibility of using innovative transport systems like car sharing and car pooling. In order to estimate the demand model parameters, a specific survey was carried ...
Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review
Directory of Open Access Journals (Sweden)
Kara N. Bocan
2016-03-01
Full Text Available Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters and variability (changes over time. Current strategies in adaptive (or tunable systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver.
Sugarcane yield estimation for climatic conditions in the state of Goiás
Directory of Open Access Journals (Sweden)
Jordana Moura Caetano
Full Text Available ABSTRACT Models that estimate potential and depleted crop yield according to climatic variable enable the crop planning and production quantification for a specific region. Therefore, the objective of this study was to compare methods to sugarcane yield estimates grown in the climatic condition in the central part of Goiás, Brazil. So, Agroecological Zone Method (ZAE and the model proposed by Scarpari (S were correlated with real data of sugarcane yield from an experimental area, located in Santo Antônio de Goiás, state of Goiás, Brazil. Data yield refer to the crops of 2008/2009 (sugarcane plant, 2009/2010, 2010/2011 and 2011/2012 (ratoon sugarcane. Yield rates were calculated as a function of atmospheric water demand and water deficit in the area under study. Real and estimated yields were adjusted in function of productivity loss due to cutting stage of sugarcane, using an average reduction in productivity observed in the experimental area and the average reduction in the state of Goiás. The results indicated that the ZAE method, considering the water deficit, displayed good yield estimates for cane-plant (d > 0.90. Water deficit decreased the yield rates (r = -0.8636; α = 0.05 while the thermal sum increased that rate for all evaluated harvests (r > 0.68; α = 0.05.
Estimating mercury emissions resulting from wildfire in forests of the Western United States
Webster, Jackson; Kane, Tyler J.; Obrist, Daniel; Ryan, Joseph N.; Aiken, George R.
2016-01-01
Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100 ± 1900 kg-Hg y− 1 for the years spanning 2000–2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating ( wood > foliage > litter > branches.
Samper, F. Javier; Neuman, Shlomo P.
1989-03-01
This series of three papers describes a cross-validation method to estimate the spatial covariance structure of intrinsic or nonintrinsic random functions from point or spatially averaged data that may be corrupted by noise. Any number of relevant parameters, including nugget effect, can be estimated. The theory, described in this paper, is based on a maximum likelihood approach which treats the cross-validation errors as Gaussian. Various a posteriori statistical tests are used to verify this hypothesis and to show that in many cases, correlation between these errors is weak. The log likelihood criterion is optimized through a combination of conjugate gradient algorithms. An adjoint state theory is used to efficiently calculate the gradient of the estimation criterion, optimize the step size downgradient, and compute a lower bound for the covariance matrix of the estimation errors. Issues related to the identifiability, stability, and uniqueness of the resulting adjoint state maximum likelihood cross-validation (ASMLCV) method are discussed. This paper also describes the manner in which ASMLCV allows one to use model structure identification criteria to select the best covariance model among a given set of alternatives. Practical aspects of ASMLCV and its application to synthetic data are presented in paper 2 (Samper and Neuman, this issue (a)). Applications to real hydrogeological data (transmissivities and groundwater levels) have been presented elsewhere, while hydrochemical and isotopic data are analyzed by ASMLCV in paper 3 (Samper and Neuman, this issue (b)).
Directory of Open Access Journals (Sweden)
Linhui Zhao
2017-12-01
Full Text Available State of charge (SOC is an important evaluation index for lithium-ion batteries (LIBs in electric vehicles (EVs. This paper proposes a nonlinear observer with a new adaptive gain structure for SOC estimation based on a second-order RC model. It is able to dynamically adjust the gains and obtain a better balance between convergence speed and estimation accuracy with less computational time. A sufficient condition is derived to guarantee the uniform asymptotic stability of the observer, and its robustness with respect to disturbances and uncertainties is analyzed with the help of input-to-state stability (ISS theory. A selection guide of the observer gains in practical application is presented. The estimation accuracy and convergence rate of the observer are evaluated and compared with those of extended Kalman filter (EKF based on multi-temperature datasets from two different types of LIB cells. The robustness against different disturbances and uncertainties that may appear in a real vehicle is validated and discussed in detail. The experimental results show that the proposed observer is capable of achieving better performance with less computational time in comparison to EKF for different types of LIB cells under various working conditions. The observer is also capable of estimating SOC accurately for real life conditions according to the validation results of datasets from a battery management system (BMS in an EV battery pack. Furthermore, the observer is simple enough, and is suitable for implementation on embedded hardware for LIB cells of EVs.
Schwartz, Sylvain; Gutty, François; Feugnet, Gilles; Bouyer, Philippe; Pocholle, Jean-Paul
2008-01-01
International audience; We study the suppression of nonlinear interactions in resonant macroscopic quantum devices in the case of the solid-state ring laser gyroscope. These nonlinear interactions are tuned by vibrating the gain medium along the cavity axis. Beat note occurrence under rotation provides a precise measurement of the strength of nonlinear interactions, which turn out to vanish for some discrete values of the amplitude of vibration. Our theoretical description, in very good agree...
Czech Academy of Sciences Publication Activity Database
Bartkiewicz, K.; Lemr, K.; Černoch, Antonín; Miranowicz, A.
2017-01-01
Roč. 95, č. 3 (2017), s. 1-7, č. článku 030102. ISSN 2469-9926 R&D Projects: GA ČR GAP205/12/0382 Institutional support: RVO:68378271 Keywords : Bell nonlocality * fully entangled fraction * entanglement-swapping device * quantum state tomography Subject RIV: BH - Optics, Masers, Lasers OBOR OECD: Optics (including laser optics and quantum optics) Impact factor: 2.925, year: 2016
State Estimation and Forecasting of the Ski-Slope Model Using an Improved Shadowing Filter
Mat Daud, Auni Aslah
In this paper, we present the application of the gradient descent of indeterminism (GDI) shadowing filter to a chaotic system, that is the ski-slope model. The paper focuses on the quality of the estimated states and their usability for forecasting. One main problem is that the existing GDI shadowing filter fails to provide stability to the convergence of the root mean square error and the last point error of the ski-slope model. Furthermore, there are unexpected cases in which the better state estimates give worse forecasts than the worse state estimates. We investigate these unexpected cases in particular and show how the presence of the humps contributes to them. However, the results show that the GDI shadowing filter can successfully be applied to the ski-slope model with only slight modification, that is, by introducing the adaptive step-size to ensure the convergence of indeterminism. We investigate its advantages over fixed step-size and how it can improve the performance of our shadowing filter.
Adaptive nonlinear observer for state and unknown parameter estimation in noisy systems
Vijayaraghavan, Krishna; Valibeygi, Amir
2016-01-01
This paper proposes a novel adaptive observer for Lipschitz nonlinear systems and dissipative nonlinear systems in the presence of disturbances and sensor noise. The observer is based on an H∞ observer that can estimate both the system states and unknown parameters by minimising a cost function consisting of the sum of the square integrals of the estimation errors in the states and unknown parameters. The paper presents necessary and sufficient conditions for the existence of the observer, and the equations for determining observer gains are formulated as linear matrix inequalities (LMIs) that can be solved offline using commercially available LMI solvers. The observer design has also been extended to the case of time-varying unknown parameters. The use of the observer is demonstrated through illustrative examples and the performance is compared with extended Kalman filtering. Compared to previous results on nonlinear observers, the proposed observer is more computationally efficient, and guarantees state and parameter estimation for two very broad classes of nonlinear systems (Lipschitz and dissipative nonlinear systems) in the presence of input disturbances and sensor noise. In addition, the proposed observer does not require online computation of the observer gain.
Anderson, Patrick L; Mahoney, Arthur W; Webster, Robert J
2017-07-01
This paper examines shape sensing for a new class of surgical robot that consists of parallel flexible structures that can be reconfigured inside the human body. Known as CRISP robots, these devices provide access to the human body through needle-sized entry points, yet can be configured into truss-like structures capable of dexterous movement and large force application. They can also be reconfigured as needed during a surgical procedure. Since CRISP robots are elastic, they will deform when subjected to external forces or other perturbations. In this paper, we explore how to combine sensor information with mechanics-based models for CRISP robots to estimate their shapes under applied loads. The end result is a shape sensing framework for CRISP robots that will enable future research on control under applied loads, autonomous motion, force sensing, and other robot behaviors.
Estimates of state-level health-care expenditures associated with disability.
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 of Charge Estimation of Lithium-Ion Batteries Using an Adaptive Cubature Kalman Filter
Directory of Open Access Journals (Sweden)
Bizhong Xia
2015-06-01
Full Text Available Accurate state of charge (SOC estimation is of great significance for a lithium-ion battery to ensure its safe operation and to prevent it from over-charging or over-discharging. However, it is difficult to get an accurate value of SOC since it is an inner sate of a battery cell, which cannot be directly measured. This paper presents an Adaptive Cubature Kalman filter (ACKF-based SOC estimation algorithm for lithium-ion batteries in electric vehicles. Firstly, the lithium-ion battery is modeled using the second-order resistor-capacitor (RC equivalent circuit and parameters of the battery model are determined by the forgetting factor least-squares method. Then, the Adaptive Cubature Kalman filter for battery SOC estimation is introduced and the estimated process is presented. Finally, two typical driving cycles, including the Dynamic Stress Test (DST and New European Driving Cycle (NEDC are applied to evaluate the performance of the proposed method by comparing with the traditional extended Kalman filter (EKF and cubature Kalman filter (CKF algorithms. Experimental results show that the ACKF algorithm has better performance in terms of SOC estimation accuracy, convergence to different initial SOC errors and robustness against voltage measurement noise as compared with the traditional EKF and CKF algorithms.
Inconsistencies Exist in National Estimates of Eye Care Services Utilization in the United States
Directory of Open Access Journals (Sweden)
Fernando A. Wilson
2015-01-01
Full Text Available Background. There are limited research and substantial uncertainty about the level of eye care utilization in the United States. Objectives. Our study estimated eye care utilization using, to our knowledge, every known nationally representative, publicly available database with information on office-based optometry or ophthalmology services. Research Design. We analyzed the following national databases to estimate eye care utilization: the Medical Expenditure Panel Survey (MEPS, National Health Interview Survey (NHIS, Joint Canada/US Survey of Health (JCUSH, Behavioral Risk Factor Surveillance System (BRFSS, and the National Ambulatory Medical Care Survey (NAMCS. Subjects. US adults aged 18 and older. Measures. Self-reported utilization of eye care services. Results. The weighted number of adults seeing or talking with any eye doctor ranges from 87.9 million to 99.5 million, and the number of visits annually ranges from 72.9 million to 142.6 million. There were an estimated 17.2 million optometry visits and 55.8 million ophthalmology visits. Conclusions. The definitions and estimates of eye care services vary widely across national databases, leading to substantial differences in national estimates of eye care utilization.
Chan, Tiffany; Friedman, David S; Bradley, Chris; Massof, Robert
2018-01-01
Updated estimates of the prevalence and incidence rates of low vision and blindness are needed to inform policy makers and develop plans to meet the future demands for low vision rehabilitation services. To provide updated estimates of the incidence and prevalence of low vision and blindness in the United States. Visual acuity measurements as a function of age from the 2007-2008 National Health and Nutrition Examination Survey, with representation of racial and ethnic groups, were used to estimate the prevalence and incidence of visual impairments. Data from 6016 survey participants, ranging in age from younger than 18 years to older than 45 years, were obtained to estimate prevalence rates for different age groups. Incidence and prevalence rates of low vision (best-corrected visual acuity [BCVA] in the better-seeing eye of United States were estimated, using the 2010 US census data by age, from the rate models applied to the census projections for 2017, 2030, and 2050. Data were collected from November 1, 2007, to October 31, 2008. Data analysis took place from March 31, 2016, to March 19, 2017. Prevalence and incidence rates of low vision and blindness in the United States. Of the 6016 people in the study, 1714 (28.4%) were younger than 18 years of age, 2358 (39.1%) were 18 to 44 years of age, and 1944 (32.3%) were 45 years of age or older. There were 2888 male (48%) and 3128 female (52%) participants. The prevalence of low vision and blindness for older adults (≥45 years) in the United States in 2017 is estimated to be 3 894 406 persons (95% CI, 3 034 442-4 862 549 persons) with a BCVA less than 20/40, 1 483 703 persons (95% CI, 968 656-2 370 513 persons) with a BCVA less than 20/60, and 1 082 790 persons (95% CI, 637 771-1 741 864 persons) with a BCVA of 20/200 or less. The estimated 2017 annual incidence (projected from 2010 census data) of low vision and blindness among older adults (≥45 years) in the United States is 481
Implications of User Identification Devices (UIDS) for the United States Navy
2001-09-01
futurist, F. M. Estfandiari as a potential step towards evolution into a posthuman . [TRHU99] A posthuman is a human descendant who has been augmented...with artificial devices to such a degree as to be no longer a ’human’. Many transhumanists want to become posthuman . [TRHU99] Calling 28 transhumans
Wong, Ting-Hong
2017-01-01
Bernstein's theory of the pedagogic device has two under-developed elements as far as its treatments of evaluative rules are concerned. It has never explained the processes through which an assessment's hegemony is erected, and it overlooks the fact that evaluations can also be crucial apparatuses in social selection and exclusion. Using the…
Nobiling, Brandye; Drolet, Judy C.
2012-01-01
Intrauterine devices (IUDs) have not been popular contraceptives in the US for the past 40 years. Recent evidence, however, has shown a slight rebirth in use, from a rate of approximately 2% in 2002 to over 5% in 2008 (Guttmacher Institute, 2010). Empirical evidence is favorable of IUD use in most women, but the still-low usage rate suggests…
Mnemonic Device for Relating the Eight Thermodynamic State Variables: The Energy Pie
Fieberg, Jeffrey E.; Girard, Charles A.
2011-01-01
A mnemonic device, the energy pie, is presented that provides relationships between thermodynamic potentials ("U," "H," "G," and "A") and other sets of variables that carry energy units, "TS" and "PV." Methods are also presented in which the differential expressions for the potentials and the corresponding Maxwell relations follow from the energy…
Advanced topics in control and estimation of state-multiplicative noisy systems
Gershon, Eli
2013-01-01
Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems begins with an introduction and extensive literature survey. The text proceeds to cover solutions of measurement-feedback control and state problems and the formulation of the Bounded Real Lemma for both continuous- and discrete-time systems. The continuous-time reduced-order and stochastic-tracking control problems for delayed systems are then treated. Ideas of nonlinear stability are introduced for infinite-horizon systems, again, in both the continuous- and discrete-time cases. The reader is introduced to six practical examples of noisy state-multiplicative control and filtering associated with various fields of control engineering. The book is rounded out by a three-part appendix containing stochastic tools necessary for a proper appreciation of the text: a basic introduction to nonlinear stochastic differential equations and aspects of switched systems and peak to peak optimal control and filtering. Advanced Topics in Contr...
Directory of Open Access Journals (Sweden)
Christopher J Paciorek
Full Text Available We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statistical methodology used to produce the product from trees recorded by land surveyors. Composition is defined as the proportion of stems larger than approximately 20 cm diameter at breast height for 22 tree taxa, generally at the genus level. The data come from settlement-era public survey records that are transcribed and then aggregated spatially, giving count data. The domain is divided into two regions, eastern (Maine to Ohio and midwestern (Indiana to Minnesota. Public Land Survey point data in the midwestern region (ca. 0.8-km resolution are aggregated to a regular 8 km grid, while data in the eastern region, from Town Proprietor Surveys, are aggregated at the township level in irregularly-shaped local administrative units. The product is based on a Bayesian statistical model fit to the count data that estimates composition on the 8 km grid across the entire domain. The statistical model is designed to handle data from both the regular grid and the irregularly-shaped townships and allows us to estimate composition at locations with no data and to smooth over noise caused by limited counts in locations with data. Critically, the model also allows us to quantify uncertainty in our composition estimates, making the product suitable for applications employing data assimilation. We expect this data product to be useful for understanding the state of vegetation in the northeastern United States prior to large-scale Euro-American settlement. In addition to specific regional questions, the data product can also serve as a baseline against which to investigate how forests and ecosystems change after intensive settlement. The data product is being made available at the NIS data portal as version 1.0.
Directory of Open Access Journals (Sweden)
Andrew Stokes
Full Text Available The goal of this research was to identify the fraction of deaths attributable to diabetes in the United States.We estimated population attributable fractions (PAF for cohorts aged 30-84 who were surveyed in the National Health Interview Survey (NHIS between 1997 and 2009 (N = 282,322 and in the National Health and Nutrition Examination Survey (NHANES between 1999 and 2010 (N = 21,814. Cohort members were followed prospectively for mortality through 2011. We identified diabetes status using self-reported diagnoses in both NHIS and NHANES and using HbA1c in NHANES. Hazard ratios associated with diabetes were estimated using Cox model adjusted for age, sex, race/ethnicity, educational attainment, and smoking status.We found a high degree of consistency between data sets and definitions of diabetes in the hazard ratios, estimates of diabetes prevalence, and estimates of the proportion of deaths attributable to diabetes. The proportion of deaths attributable to diabetes was estimated to be 11.5% using self-reports in NHIS, 11.7% using self-reports in NHANES, and 11.8% using HbA1c in NHANES. Among the sub-groups that we examined, the PAF was highest among obese persons at 19.4%. The proportion of deaths in which diabetes was assigned as the underlying cause of death (3.3-3.7% severely understated the contribution of diabetes to mortality in the United States.Diabetes may represent a more prominent factor in American mortality than is commonly appreciated, reinforcing the need for robust population-level interventions aimed at diabetes prevention and care.
Stokes, Andrew; Preston, Samuel H
2017-01-01
The goal of this research was to identify the fraction of deaths attributable to diabetes in the United States. We estimated population attributable fractions (PAF) for cohorts aged 30-84 who were surveyed in the National Health Interview Survey (NHIS) between 1997 and 2009 (N = 282,322) and in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2010 (N = 21,814). Cohort members were followed prospectively for mortality through 2011. We identified diabetes status using self-reported diagnoses in both NHIS and NHANES and using HbA1c in NHANES. Hazard ratios associated with diabetes were estimated using Cox model adjusted for age, sex, race/ethnicity, educational attainment, and smoking status. We found a high degree of consistency between data sets and definitions of diabetes in the hazard ratios, estimates of diabetes prevalence, and estimates of the proportion of deaths attributable to diabetes. The proportion of deaths attributable to diabetes was estimated to be 11.5% using self-reports in NHIS, 11.7% using self-reports in NHANES, and 11.8% using HbA1c in NHANES. Among the sub-groups that we examined, the PAF was highest among obese persons at 19.4%. The proportion of deaths in which diabetes was assigned as the underlying cause of death (3.3-3.7%) severely understated the contribution of diabetes to mortality in the United States. Diabetes may represent a more prominent factor in American mortality than is commonly appreciated, reinforcing the need for robust population-level interventions aimed at diabetes prevention and care.
Estimating litter carbon stocks on forest land in the United States.
Domke, Grant M; Perry, Charles H; Walters, Brian F; Woodall, Christopher W; Russell, Matthew B; Smith, James E
2016-07-01
Forest ecosystems are the largest terrestrial carbon sink on earth, with more than half of their net primary production moving to the soil via the decomposition of litter biomass. Therefore, changes in the litter carbon (C) pool have important implications for global carbon budgets and carbon emissions reduction targets and negotiations. Litter accounts for an estimated 5% of all forest ecosystem carbon stocks worldwide. Given the cost and time required to measure litter attributes, many of the signatory nations to the United Nations Framework Convention on Climate Change report estimates of litter carbon stocks and stock changes using default values from the Intergovernmental Panel on Climate Change or country-specific models. In the United States, the country-specific model used to predict litter C stocks is sensitive to attributes on each plot in the national forest inventory, but these predictions are not associated with the litter samples collected over the last decade in the national forest inventory. Here we present, for the first time, estimates of litter carbon obtained using more than 5000 field measurements from the national forest inventory of the United States. The field-based estimates mark a 44% reduction (2081±77Tg) in litter carbon stocks nationally when compared to country-specific model predictions reported in previous United Framework Convention on Climate Change submissions. Our work suggests that Intergovernmental Panel on Climate Change defaults and country-specific models used to estimate litter carbon in temperate forest ecosystems may grossly overestimate the contribution of this pool in national carbon budgets. Published by Elsevier B.V.
Directory of Open Access Journals (Sweden)
S. Nie
2011-08-01
Full Text Available The performance of the ensemble Kalman filter (EnKF in soil moisture assimilation applications is investigated in the context of simultaneous state-parameter estimation in the presence of uncertainties from model parameters, soil moisture initial condition and atmospheric forcing. A physically based land surface model is used for this purpose. Using a series of identical twin experiments in two kinds of initial parameter distribution (IPD scenarios, the narrow IPD (NIPD scenario and the wide IPD (WIPD scenario, model-generated near surface soil moisture observations are assimilated to estimate soil moisture state and three hydraulic parameters (the saturated hydraulic conductivity, the saturated soil moisture suction and a soil texture empirical parameter in the model. The estimation of single imperfect parameter is successful with the ensemble mean value of all three estimated parameters converging to their true values respectively in both NIPD and WIPD scenarios. Increasing the number of imperfect parameters leads to a decline in the estimation performance. A wide initial distribution of estimated parameters can produce improved simultaneous multi-parameter estimation performances compared to that of the NIPD scenario. However, when the number of estimated parameters increased to three, not all parameters were estimated successfully for both NIPD and WIPD scenarios. By introducing constraints between estimated hydraulic parameters, the performance of the constrained three-parameter estimation was successful, even if temporally sparse observations were available for assimilation. The constrained estimation method can reduce RMSE much more in soil moisture forecasting compared to the non-constrained estimation method and traditional non-parameter-estimation assimilation method. The benefit of this method in estimating all imperfect parameters simultaneously can be fully demonstrated when the corresponding non-constrained estimation method
Nagpal, A Dave; Singal, Rohit K; Arora, Rakesh C; Lamarche, Yoan
2017-01-01
With more than 60 years of continuous development and improvement, a variety of temporary mechanical circulatory support (MCS) devices and implantation strategies exist, each with unique advantages and disadvantages. A thorough understanding of each available device is essential for optimizing patient outcomes in a fiscally responsible manner. In this state of the art review we examine the entire range of commonly available peripheral and centrally cannulated temporary MCS devices, including intra-aortic balloon pumps, the Impella (Abiomed, Danvers, MA) family of microaxial pumps, the TandemHeart (CardiacAssist Inc, Pittsburg, PA) pump and percutaneous cannulas, centrally cannulated centrifugal pumps such as the CentriMag (Thoratec Corp, Pleasanton, CA/St Jude Medical, St Paul, MN/Abbott Laboratories, Abbott Park, IL) and Rotaflow (Maquet Holding BV & Co KG, Rastatt Germany), and extracorporeal membrane oxygenation. Several factors need detailed consideration when contemplating MCS in any given patient, mandating a balanced, algorithmic approach for these sick patients. In this review we describe our approach to MCS, and emphasize the need for multidisciplinary input to consider patient-related, logistical, and institutional factors. Evidence is summarized and referenced where available, but because of the lack of high-quality evidence, current best practice is described. Future directions for investigation are discussed, which will better define patient and device selection, and optimize MCS-specific patient care protocols. Copyright © 2016 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.
Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks
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Xiaoxue Feng
2014-11-01
Full Text Available Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS, which gets better filtering performance than NILS without constraint.
Variable input observer for state estimation of high-rate dynamics
Hong, Jonathan; Cao, Liang; Laflamme, Simon; Dodson, Jacob
2017-04-01
High-rate systems operating in the 10 μs to 10 ms timescale are likely to experience damaging effects due to rapid environmental changes (e.g., turbulence, ballistic impact). Some of these systems could benefit from real-time state estimation to enable their full potential. Examples of such systems include blast mitigation strategies, automotive airbag technologies, and hypersonic vehicles. Particular challenges in high-rate state estimation include: 1) complex time varying nonlinearities of system (e.g. noise, uncertainty, and disturbance); 2) rapid environmental changes; 3) requirement of high convergence rate. Here, we propose using a Variable Input Observer (VIO) concept to vary the input space as the event unfolds. When systems experience high-rate dynamics, rapid changes in the system occur. To investigate the VIO's potential, a VIO-based neuro-observer is constructed and studied using experimental data collected from a laboratory impact test. Results demonstrate that the input space is unique to different impact conditions, and that adjusting the input space throughout the dynamic event produces better estimations than using a traditional fixed input space strategy.
Brizuela Mendoza, Jorge Aurelio; Astorga Zaragoza, Carlos Manuel; Zavala Río, Arturo; Pattalochi, Leo; Canales Abarca, Francisco
2016-03-01
This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Liu Yurong; Wang Zidong; Liu Xiaohui
2008-01-01
In this Letter, we investigate the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters as well as mode-dependent mixed time-delays. The parameters of the discrete-time neural networks are subject to the switching from one mode to another at different times according to a Markov chain, and the mixed time-delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. New techniques are developed to deal with the mixed time-delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time-delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the existence of the state estimators. We show that both the existence conditions and the explicit expression of the desired estimator can be characterized in terms of the solution to an LMI. A numerical example is exploited to show the usefulness of the derived LMI-based conditions
Perry, C. H.; Domke, G. M.; Walters, B. F.; Smith, J. E.; Woodall, C. W.
2014-12-01
The Forest Inventory and Analysis (FIA) program of the United States Forest Service reports official estimates of national forest floor carbon (FFC) stocks and stock change to national and international parties, the US Environmental Protection Agency (USEPA) and the United Nations Framework Convention on Climate Change (UNFCCC), respectively. These estimates of national FFC stocks are derived from plot-level predictions of FFC density. We suspect the models used to predict plot-level FFC density are less than ideal for several reasons: (a) they are based upon local studies that may not reflect FFC dynamics at the national scale, (b) they are relatively insensitive to climate change, and (c) they reduce the natural variability of the data leading to misplaced confidence in the estimates. However, FIA has measured forest floor attributes since 2001 on a systematic 1/16th subset of a nation-wide array of inventory plots (7 800 of 125 000 plots). Here we address the efficacy of replacing plot-level model predictions with empirical observations of FFC density while assessing the impact of imputing FFC density values to the full plot network on national stock estimates. First, using an equivalence testing framework, we found model predictions of FFC density to differ significantly from the observations in all regions and forest types; the mean difference across all plots was 21 percent (1.81 Mg·ha-1). Furthermore, the model predictions were biased towards the lower end of extant FFC density observations, underestimating it while greatly truncating the range relative to the observations. Second, the optimal imputation approach (k-Nearest Neighbor, k-NN) resulted in values that were equivalent to observations of FFC density across a range of simulated missingness and maintained the high variability seen in the observations. We used the k-NN approach to impute FFC density values to the 94 percent of FIA inventory plots without soil measurements. Third, using the imputed
Dooley, Erin E; Golaszewski, Natalie M; Bartholomew, John B
2017-03-16
Physical activity tracking wearable devices have emerged as an increasingly popular method for consumers to assess their daily activity and calories expended. However, whether these wearable devices are valid at different levels of exercise intensity is unknown. The objective of this study was to examine heart rate (HR) and energy expenditure (EE) validity of 3 popular wrist-worn activity monitors at different exercise intensities. A total of 62 participants (females: 58%, 36/62; nonwhite: 47% [13/62 Hispanic, 8/62 Asian, 7/62 black/ African American, 1/62 other]) wore the Apple Watch, Fitbit Charge HR, and Garmin Forerunner 225. Validity was assessed using 2 criterion devices: HR chest strap and a metabolic cart. Participants completed a 10-minute seated baseline assessment; separate 4-minute stages of light-, moderate-, and vigorous-intensity treadmill exercises; and a 10-minute seated recovery period. Data from devices were compared with each criterion via two-way repeated-measures analysis of variance and Bland-Altman analysis. Differences are expressed in mean absolute percentage error (MAPE). For the Apple Watch, HR MAPE was between 1.14% and 6.70%. HR was not significantly different at the start (P=.78), during baseline (P=.76), or vigorous intensity (P=.84); lower HR readings were measured during light intensity (P=.03), moderate intensity (P=.001), and recovery (P=.004). EE MAPE was between 14.07% and 210.84%. The device measured higher EE at all stages (PApple Watch, and Garmin Forerunner 225. An advantage and novel approach of the study is the examination of HR and EE at specific physical activity intensities. Establishing validity of wearable devices is of particular interest as these devices are being used in weight loss interventions and could impact findings. Future research should investigate why differences between exercise intensities and the devices exist. ©Erin E Dooley, Natalie M Golaszewski, John B Bartholomew. Originally published in JMIR
Refining Estimates of Bird Collision and Electrocution Mortality at Power Lines in the United States
Loss, Scott R.; Will, Tom; Marra, Peter P.
2014-01-01
Collisions and electrocutions at power lines are thought to kill large numbers of birds in the United States annually. However, existing estimates of mortality are either speculative (for electrocution) or based on extrapolation of results from one study to all U.S. power lines (for collision). Because national-scale estimates of mortality and comparisons among threats are likely to be used for prioritizing policy and management strategies and for identifying major research needs, these estimates should be based on systematic and transparent assessment of rigorously collected data. We conducted a quantitative review that incorporated data from 14 studies meeting our inclusion criteria to estimate that between 12 and 64 million birds are killed each year at U.S. power lines, with between 8 and 57 million birds killed by collision and between 0.9 and 11.6 million birds killed by electrocution. Sensitivity analyses indicate that the majority of uncertainty in our estimates arises from variation in mortality rates across studies; this variation is due in part to the small sample of rigorously conducted studies that can be used to estimate mortality. Little information is available to quantify species-specific vulnerability to mortality at power lines; the available literature over-represents particular bird groups and habitats, and most studies only sample and present data for one or a few species. Furthermore, additional research is needed to clarify whether, to what degree, and in what regions populations of different bird species are affected by power line-related mortality. Nonetheless, our data-driven analysis suggests that the amount of bird mortality at U.S. power lines is substantial and that conservation management and policy is necessary to reduce this mortality. PMID:24991997
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%.
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...
Solid state MEMS devices on flexible and semi-transparent silicon (100) platform
Ahmed, Sally
2014-01-01
We report fabrication of MEMS thermal actuators on flexible and semi-transparent silicon fabric released from bulk silicon (100). We fabricated the devices first and then released the top portion of the silicon (≈ 19 μm) which is flexible and semi-transparent. We also performed chemical mechanical polishing to reuse the remaining wafer. A tested thermal actuator with 3 μm wide 240 μm hot arm and 10 μm wide 185 μm long cold arm deflected by 1.7 μm at 1 V. The fabricated thermal actuators exhibit similar performance before and after bending. We believe the demonstrated process will expand the horizon of flexible electronics into MEMS world devices. © 2014 IEEE.
Nonlinear Integral Type Observer Design for State Estimation and Unknown Input Reconstruction
Directory of Open Access Journals (Sweden)
Chao-Chung Peng
2017-01-01
Full Text Available This paper is concerned with model-based robust observer designs for state observation and its application for unknown input reconstruction. Firstly, a sliding mode observer (SMO, which provides exponential convergence of estimation error, is designed for a class of multivariable perturbed systems. Observer gain matrices subject to specific structures are going to be imposed such that the unknown perturbation will not affect estimate precision during the sliding modes; Secondly, to improve discontinuous control induced in the SMO as well as pursue asymptotic estimate precision, a proportional-integral type observer (PIO is further developed. Both the design procedures of the SMO and PIO algorithms are characterized as feasibility issues of linear matrix inequality (LMI and thus the computations of the control parameters can be efficiently solved. Compared with the SMO, it will be demonstrated that the PIO is capable of achieving better estimation precision as long as the unknown inputs are continuous. Finally, a servo-drive flexible robot arm is selected as an example to demonstrate the applications of the robust observer designs.
State of Charge Estimation Based on Microscopic Driving Parameters for Electric Vehicle's Battery
Directory of Open Access Journals (Sweden)
Enjian Yao
2013-01-01
Full Text Available Recently, battery-powered electric vehicle (EV has received wide attention due to less pollution during use, low noise, and high energy efficiency and is highly expected to improve urban air quality and then mitigate energy and environmental pressure. However, the widespread use of EV is still hindered by limited battery capacity and relatively short cruising range. This paper aims to propose a state of charge (SOC estimation method for EV’s battery necessary for route planning and dynamic route guidance, which can help EV drivers to search for the optimal energy-efficient routes and to reduce the risk of running out of electricity before arriving at the destination or charging station. Firstly, by analyzing the variation characteristics of power consumption rate with initial SOC and microscopic driving parameters (instantaneous speed and acceleration, a set of energy consumption rate models are established according to different operation modes. Then, the SOC estimation model is proposed based on the presented EV power consumption model. Finally, by comparing the estimated SOC with the measured SOC, the proposed SOC estimation method is proved to be highly accurate and effective, which can be well used in EV route planning and navigation systems.
Directory of Open Access Journals (Sweden)
Kolosok Irina
2017-01-01
Full Text Available Reliable information on the current state parameters obtained as a result of processing the measurements from systems of the SCADA and WAMS data acquisition and processing through methods of state estimation (SE is a condition that enables to successfully manage an energy power system (EPS. SCADA and WAMS systems themselves, as any technical systems, are subject to failures and faults that lead to distortion and loss of information. The SE procedure enables to find erroneous measurements, therefore, it is a barrier for the distorted information to penetrate into control problems. At the same time, the programming and computing suite (PCS implementing the SE functions may itself provide a wrong decision due to imperfection of the software algorithms and errors. In this study, we propose to use a fault tree to analyze consequences of failures and faults in SCADA and WAMS and in the very SE procedure. Based on the analysis of the obtained measurement information and on the SE results, we determine the state estimation PCS fault tolerance level featuring its reliability.
Estimating the number of competing terminals without a state variation detector in wireless LAN
Lim, Jaechan; Kim, Taejin; Hong, Daehyoung
2013-12-01
Estimating the number of competing terminals n (who wish to transmit a packet at the same time) in the IEEE 802.11 system is important for system throughput performance because optimal back-off window size needs to be selected based on n. Therefore, as a new approach for estimating n, we propose H infinity filter that does not need a state variation detector as opposed to the cases of previously proposed approaches. The state variation detector's flaw is incurring tracking latency in addition to the side effect of increased computational cost. All previously proposed approaches demand the employment of the state variation detector to detect the variation of n in the IEEE 802.11 system. By employing H infinity filter, we show improved throughput performance of the system compared to that of previously proposed approaches (e.g., the Kalman filter and particle filter) based on the improved performance in tracking n. In this paper, we justify the superiority of the proposed approach in the terms of tracking performance, throughput performance, and computational complexity.
2016-09-01
The students accessing the network are responsible for procuring their own device and complying with usage standards as well as maintaining the...capability within the Maine Air Ground Task Force (MAGTF). It also specifically lays out the intent to enhance capability with regard to social media ...the productivity, and situational awareness of individuals to include members of the DOD. The increasing use of social media , smartphones, and
Cohabitation and children's living arrangements: New estimates from the United States.
Kennedy, Sheela; Bumpass, Larry
2008-01-01
This paper uses the 1995 and 2002 waves of the National Survey of Family Growth to examine recent trends in cohabitation in the United States. We find increases in both the prevalence and duration of unmarried cohabitation. Cohabitation continues to transform children's family lives, as children are increasingly born to cohabiting mothers (18% during 1997-2001) or later experience their mother's entry into a cohabiting union. Consequently, we estimate that two-fifths of all children spend some time in a cohabiting family by age 12. Because of substantial missing data in the 2002 NSFG, we are unable to produce new estimates of divorce or of children's time in single-parent families. Nonetheless, our results point to the steady growth of cohabitation and to the evolving role of cohabitation in U.S. family life.
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Jørgensen, John Bagterp; Rawlings, James B.
2015-01-01
In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least...... squares method (ALS). We present a model for the spray drying plant and use this model for simulation as well as for prediction in the E-NMPC. The open-loop optimal control problem in the E-NMPC is solved using the single-shooting method combined with a quasi-Newton Sequential Quadratic programming (SQP......) algorithm and the adjoint method for computation of gradients. We evaluate the economic performance when unmeasured disturbances are present. By simulation, we demonstrate that the E-NMPC improves the profit of spray drying by 17% compared to conventional PI control....
SUBSYSTEM OF MODELS OF ECOLOGICAL MONITORING FOR ESTIMATION OF THE STATE OF ATMOSPHERIC AIR
Directory of Open Access Journals (Sweden)
S. Z. Polischuk
2017-04-01
Full Text Available Purpose. The article is devoted to the improvement of the method of forecasting the quality of atmospheric air when discharging from stationary sources of pollution and from mobile sources of pollution. The choice of the goal is due to the fact that recently the requirements to the quality of the forecast information of the atmospheric air have increased, which entails the modernization of existing forecast methods. The work has improved the unit for assessing and forecasting the state of atmospheric air in a system of regional environmental monitoring to improve the level of environmental safety in the planning and development of territories. The improved unit serves to determine the quality indices of atmospheric air and the state of its resource potential. Methodology. For the decision of the put task the complex method of researches, which consists in the analysis of the systems and generalization of existent researches after the problem of estimation and prognosis of the state of atmospheric air, use of objective method at the construction of the hierarchical system of models, is utilized. For determination of indexes the method of expert estimations is top level used. For the solution of differential equations of aerodynamics and mass transfer uses finite-difference methods. Findings. The structure of prognosis block is developed on atmospheric air in the system of the ecological monitoring. Researches of indexes of quality of atmospheric air and state of its resource potential are executed with the use of the developed models. Originality. The use of a hierarchical series of mathematical models for a comprehensive assessment and prediction of the state of atmospheric air in scenarios of socio-ecological and economic development and urban development activities of the regions is justified, which makes it possible to raise the level of their ecological safety at the stage of carrying out design and prospecting works. Practical value. The
Weber, Ingmar; Fernandez-Luque, Luis
2018-01-01
Background Facebook, the most popular social network with over one billion daily users, provides rich opportunities for its use in the health domain. Though much of Facebook’s data are not available to outsiders, the company provides a tool for estimating the audience of Facebook advertisements, which includes aggregated information on the demographics and interests, such as weight loss or dieting, of Facebook users. This paper explores the potential uses of Facebook ad audience estimates for eHealth by studying the following: (1) for what type of health conditions prevalence estimates can be obtained via social media and (2) what type of marker interests are useful in obtaining such estimates, which can then be used for recruitment within online health interventions. Objective The objective of this study was to understand the limitations and capabilities of using Facebook ad audience estimates for public health monitoring and as a recruitment tool for eHealth interventions. Methods We use the Facebook Marketing application programming interface to correlate estimated sizes of audiences having health-related interests with public health data. Using several study cases, we identify both potential benefits and challenges in using this tool. Results We find several limitations in using Facebook ad audience estimates, for example, using placebo interest estimates to control for background level of user activity on the platform. Some Facebook interests such as plus-size clothing show encouraging levels of correlation (r=.74) across the 50 US states; however, we also sometimes find substantial correlations with the placebo interests such as r=.68 between interest in Technology and Obesity prevalence. Furthermore, we find demographic-specific peculiarities in the interests on health-related topics. Conclusions Facebook’s advertising platform provides aggregate data for more than 190 million US adults. We show how disease-specific marker interests can be used to model
Mejova, Yelena; Weber, Ingmar; Fernandez-Luque, Luis
2018-03-28
Facebook, the most popular social network with over one billion daily users, provides rich opportunities for its use in the health domain. Though much of Facebook's data are not available to outsiders, the company provides a tool for estimating the audience of Facebook advertisements, which includes aggregated information on the demographics and interests, such as weight loss or dieting, of Facebook users. This paper explores the potential uses of Facebook ad audience estimates for eHealth by studying the following: (1) for what type of health conditions prevalence estimates can be obtained via social media and (2) what type of marker interests are useful in obtaining such estimates, which can then be used for recruitment within online health interventions. The objective of this study was to understand the limitations and capabilities of using Facebook ad audience estimates for public health monitoring and as a recruitment tool for eHealth interventions. We use the Facebook Marketing application programming interface to correlate estimated sizes of audiences having health-related interests with public health data. Using several study cases, we identify both potential benefits and challenges in using this tool. We find several limitations in using Facebook ad audience estimates, for example, using placebo interest estimates to control for background level of user activity on the platform. Some Facebook interests such as plus-size clothing show encouraging levels of correlation (r=.74) across the 50 US states; however, we also sometimes find substantial correlations with the placebo interests such as r=.68 between interest in Technology and Obesity prevalence. Furthermore, we find demographic-specific peculiarities in the interests on health-related topics. Facebook's advertising platform provides aggregate data for more than 190 million US adults. We show how disease-specific marker interests can be used to model prevalence rates in a simple and intuitive manner
Park, Wooram; Liu, Yan; Zhou, Yu; Moses, Matthew; Chirikjian, Gregory S
2008-04-11
A nonholonomic system subjected to external noise from the environment, or internal noise in its own actuators, will evolve in a stochastic manner described by an ensemble of trajectories. This ensemble of trajectories is equivalent to the solution of a Fokker-Planck equation that typically evolves on a Lie group. If the most likely state of such a system is to be estimated, and plans for subsequent motions from the current state are to be made so as to move the system to a desired state with high probability, then modeling how the probability density of the system evolves is critical. Methods for solving Fokker-Planck equations that evolve on Lie groups then become important. Such equations can be solved using the operational properties of group Fourier transforms in which irreducible unitary representation (IUR) matrices play a critical role. Therefore, we develop a simple approach for the numerical approximation of all the IUR matrices for two of the groups of most interest in robotics: the rotation group in three-dimensional space, SO(3), and the Euclidean motion group of the plane, SE(2). This approach uses the exponential mapping from the Lie algebras of these groups, and takes advantage of the sparse nature of the Lie algebra representation matrices. Other techniques for density estimation on groups are also explored. The computed densities are applied in the context of probabilistic path planning for kinematic cart in the plane and flexible needle steering in three-dimensional space. In these examples the injection of artificial noise into the computational models (rather than noise in the actual physical systems) serves as a tool to search the configuration spaces and plan paths. Finally, we illustrate how density estimation problems arise in the characterization of physical noise in orientational sensors such as gyroscopes.
International Nuclear Information System (INIS)
Hamilton, D.R.; Evans, C.D.
1986-08-01
The report discusses survey results on aspects of the quality assurance of radio-pharmaceuticals from 180 nuclear-medicine facilities in the United States. Data were collected from facilities in 8 states. Demographic information about nuclear-medicine operations and quality-assurance programs was gathered by state radiation-control-program personnel. The data collected from the survey show an incomplete acceptance of quality-assurance practices for radiopharmaceuticals. Most of the facilities in the survey indicated that, because an inferior radiopharmaceutical was prepared so infrequently, they did not believe it was cost-effective to perform extensive quality-assurance testing. The Center for Devices and Radiological Health hopes that the information from the survey will stimulate nuclear-medicine professionals and their organizations to encourage appropriate testing of all radiopharmaceuticals
International Nuclear Information System (INIS)
Fields, D.E.; Travis, C.C.; Watson, A.P.; McDowell-Boyer, L.M.
1979-12-01
The report represents a compilation of computer codes used to estimate potential human exposures and inhalation doses due to unit releases of 222 Rn from uranium milling sites in western United States. The populations considered for potential exposure to risk from 222 Rn and associated daughters are the inhabitants of North America between 20 0 and 60 0 North latitude. The primary function of these codes is to integrate spatially atmospheric radionuclide concentrations with current population data for the geographic area under consideration. It is expected that these codes will be of assistance to anyone interested in assessing nuclear or nonnuclear population exposures over large geographic areas
State of the art in the estimation of energy prices in the spot market
International Nuclear Information System (INIS)
Botero B, Sergio; Cano C, Jovan A
2007-01-01
Since the start energy markets deregulation in the world, several spot market (short term) price prediction methods have been developed? this article identifies and compares the main methods of prediction used in Colombia and other international markets. With this review it is possible to determine the state of the knowledge in the specific subject and then to look for the development of new forecasting techniques that can contribute to the solution of this problem. The prediction horizon is something that must be taken into account in the review of the several techniques, given that both the magnitude of the final model of estimation, and the time series treatment type, depend on this horizon.
Estimating the Availability of Potential Homes for Unwanted Horses in the United States
Weiss, Emily; Dolan, Emily D.; Mohan-Gibbons, Heather; Gramann, Shannon; Slater, Margaret R.
2017-01-01
Simple Summary There are approximately 200,000 unwanted horses annually in the United States. Many are shipped to slaughter, enter rescue facilities, or are held on federal lands. This study aimed to estimate a potential number of available homes for unwanted horses in order to examine broadly the viability of pursuing re-homing policies as an option for the thousands of unwanted horses in the U.S. The results of this survey suggest there could be an estimated 1.2 million homes who have both the perceived resources and desire to house an unwanted horse. This number exceeds the approximately 200,000 unwanted horses living each year in the United States. These data suggest that efforts to reduce unwanted horses could involve matching such horses with adoptive homes and enhancing opportunities to keep horses in the homes they already have. Abstract There are approximately 200,000 unwanted horses annually in the United States. This study aimed to better understand the potential homes for horses that need to be re-homed. Using an independent survey company through an Omnibus telephone (land and cell) survey, we interviewed a nationally projectable sample of 3036 adults (using both landline and cellular phone numbers) to learn of their interest and capacity to adopt a horse. Potential adopters with interest in horses with medical and/or behavioral problems and self-assessed perceived capacity to adopt, constituted 0.92% of the total sample. Extrapolating the results of this survey using U.S. Census data, suggests there could be an estimated 1.25 million households who have both the self-reported and perceived resources and desire to house an unwanted horse. This number exceeds the estimated number of unwanted horses living each year in the United States. This study points to opportunities and need to increase communication and support between individuals and organizations that have unwanted horses to facilitate re-homing with people in their community willing to adopt
Infinite-Dimensional Boundary Observer for Lithium-Ion Battery State Estimation
DEFF Research Database (Denmark)
Hasan, Agus; Jouffroy, Jerome
2017-01-01
This paper presents boundary observer design for state-of-charge (SOC) estimation of lithium-ion batteries. The lithium-ion battery dynamics are governed by thermal-electrochemical principles, which mathematically modeled by partial differential equations (PDEs). In general, the model is a reaction......-diffusion equation with time-dependent coefficients. A Luenberger observer is developed using infinite-dimensional backstepping method and uses only a single measurement at the boundary of the battery. The observer gains are computed by solving the observer kernel equation. A numerical example is performed to show...
Estimating the Value of Life, Injury, and Travel Time Saved Using a Stated Preference Framework.
Niroomand, Naghmeh; Jenkins, Glenn P
2016-06-01
The incidence of fatality over the period 2010-2014 from automobile accidents in North Cyprus is 2.75 times greater than the average for the EU. With the prospect of North Cyprus entering the EU, many investments will need to be undertaken to improve road safety in order to reach EU benchmarks. The objective of this study is to provide local estimates of the value of a statistical life and injury along with the value of time savings. These are among the parameter values needed for the evaluation of the change in the expected incidence of automotive accidents and time savings brought about by such projects. In this study we conducted a stated choice experiment to identify the preferences and tradeoffs of automobile drivers in North Cyprus for improved travel times, travel costs, and safety. The choice of route was examined using mixed logit models to obtain the marginal utilities associated with each attribute of the routes that consumers choose. These estimates were used to assess the individuals' willingness to pay (WTP) to avoid fatalities and injuries and to save travel time. We then used the results to obtain community-wide estimates of the value of a statistical life (VSL) saved, the value of injury (VI) prevented, and the value per hour of travel time saved. The estimates for the VSL range from €315,293 to €1,117,856 and the estimates of VI from € 5,603 to € 28,186. These values are consistent, after adjusting for differences in incomes, with the median results of similar studies done for EU countries. Copyright © 2016 Elsevier Ltd. All rights reserved.
Improving precipitation estimates over the western United States using GOES-R precipitation data
Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.
2017-12-01
Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.