WorldWideScience

Sample records for models ekf implementation

  1. Structural observability analysis and EKF based parameter estimation of building heating models

    Directory of Open Access Journals (Sweden)

    D.W.U. Perera

    2016-07-01

    Full Text Available Research for enhanced energy-efficient buildings has been given much recognition in the recent years owing to their high energy consumptions. Increasing energy needs can be precisely controlled by practicing advanced controllers for building Heating, Ventilation, and Air-Conditioning (HVAC systems. Advanced controllers require a mathematical building heating model to operate, and these models need to be accurate and computationally efficient. One main concern associated with such models is the accurate estimation of the unknown model parameters. This paper presents the feasibility of implementing a simplified building heating model and the computation of physical parameters using an off-line approach. Structural observability analysis is conducted using graph-theoretic techniques to analyze the observability of the developed system model. Then Extended Kalman Filter (EKF algorithm is utilized for parameter estimates using the real measurements of a single-zone building. The simulation-based results confirm that even with a simple model, the EKF follows the state variables accurately. The predicted parameters vary depending on the inputs and disturbances.

  2. Nonlinear control of a multicomponent distillation process coupled with a binary distillation model as an EKF predictor.

    Science.gov (United States)

    Jana, Amiya Kumar; Ganguly, Saibal; Samanta, Amar Nath

    2006-10-01

    The work is devoted to design the globally linearizing control (GLC) strategy for a multicomponent distillation process. The control system is comprised with a nonlinear transformer, a nonlinear closed-loop state estimator [extended Kalman filter (EKF)], and a linear external controller [conventional proportional integral (PI) controller]. The model of a binary distillation column has been used as a state predictor to avoid huge design complexity of the EKF estimator. The binary components are the light key and the heavy key of the multicomponent system. The proposed GLC-EKF (GLC in conjunction with EKF) control algorithm has been compared with the GLC-ROOLE [GLC coupled with reduced-order open-loop estimator (ROOLE)] and the dual-loop PI controller based on set point tracking and disturbance rejection performance. Despite huge process/predictor mismatch, the superiority of the GLC-EKF has been inspected over the GLC-ROOLE control structure.

  3. Inferring microbial interaction networks from metagenomic data using SgLV-EKF algorithm.

    Science.gov (United States)

    Alshawaqfeh, Mustafa; Serpedin, Erchin; Younes, Ahmad Bani

    2017-03-27

    Inferring the microbial interaction networks (MINs) and modeling their dynamics are critical in understanding the mechanisms of the bacterial ecosystem and designing antibiotic and/or probiotic therapies. Recently, several approaches were proposed to infer MINs using the generalized Lotka-Volterra (gLV) model. Main drawbacks of these models include the fact that these models only consider the measurement noise without taking into consideration the uncertainties in the underlying dynamics. Furthermore, inferring the MIN is characterized by the limited number of observations and nonlinearity in the regulatory mechanisms. Therefore, novel estimation techniques are needed to address these challenges. This work proposes SgLV-EKF: a stochastic gLV model that adopts the extended Kalman filter (EKF) algorithm to model the MIN dynamics. In particular, SgLV-EKF employs a stochastic modeling of the MIN by adding a noise term to the dynamical model to compensate for modeling uncertainties. This stochastic modeling is more realistic than the conventional gLV model which assumes that the MIN dynamics are perfectly governed by the gLV equations. After specifying the stochastic model structure, we propose the EKF to estimate the MIN. SgLV-EKF was compared with two similarity-based algorithms, one algorithm from the integral-based family and two regression-based algorithms, in terms of the achieved performance on two synthetic data-sets and two real data-sets. The first data-set models the randomness in measurement data, whereas, the second data-set incorporates uncertainties in the underlying dynamics. The real data-sets are provided by a recent study pertaining to an antibiotic-mediated Clostridium difficile infection. The experimental results demonstrate that SgLV-EKF outperforms the alternative methods in terms of robustness to measurement noise, modeling errors, and tracking the dynamics of the MIN. Performance analysis demonstrates that the proposed SgLV-EKF algorithm

  4. Feature Selection Criteria for Real Time EKF-SLAM Algorithm

    Directory of Open Access Journals (Sweden)

    Fernando Auat Cheein

    2010-02-01

    Full Text Available This paper presents a seletion procedure for environmet features for the correction stage of a SLAM (Simultaneous Localization and Mapping algorithm based on an Extended Kalman Filter (EKF. This approach decreases the computational time of the correction stage which allows for real and constant-time implementations of the SLAM. The selection procedure consists in chosing the features the SLAM system state covariance is more sensible to. The entire system is implemented on a mobile robot equipped with a range sensor laser. The features extracted from the environment correspond to lines and corners. Experimental results of the real time SLAM algorithm and an analysis of the processing-time consumed by the SLAM with the feature selection procedure proposed are shown. A comparison between the feature selection approach proposed and the classical sequential EKF-SLAM along with an entropy feature selection approach is also performed.

  5. An EKF-SLAM algorithm with consistency properties

    OpenAIRE

    Barrau, Axel; Bonnabel, Silvere

    2015-01-01

    In this paper we address the inconsistency of the EKF-based SLAM algorithm that stems from non-observability of the origin and orientation of the global reference frame. We prove on the non-linear two-dimensional problem with point landmarks observed that this type of inconsistency is remedied using the Invariant EKF, a recently introduced variant ot the EKF meant to account for the symmetries of the state space. Extensive Monte-Carlo runs illustrate the theoretical results.

  6. A hybrid EKF and switching PSO algorithm for joint state and parameter estimation of lateral flow immunoassay models.

    Science.gov (United States)

    Zeng, Nianyin; Wang, Zidong; Li, Yurong; Du, Min; Liu, Xiaohui

    2012-01-01

    In this paper, a hybrid extended Kalman filter (EKF) and switching particle swarm optimization (SPSO) algorithm is proposed for jointly estimating both the parameters and states of the lateral flow immunoassay model through available short time-series measurement. Our proposed method generalizes the well-known EKF algorithm by imposing physical constraints on the system states. Note that the state constraints are encountered very often in practice that give rise to considerable difficulties in system analysis and design. The main purpose of this paper is to handle the dynamic modeling problem with state constraints by combining the extended Kalman filtering and constrained optimization algorithms via the maximization probability method. More specifically, a recently developed SPSO algorithm is used to cope with the constrained optimization problem by converting it into an unconstrained optimization one through adding a penalty term to the objective function. The proposed algorithm is then employed to simultaneously identify the parameters and states of a lateral flow immunoassay model. It is shown that the proposed algorithm gives much improved performance over the traditional EKF method.

  7. EKF composition estimation and GMC control of a reactive distillation column

    Science.gov (United States)

    Tintavon, Sirivimon; Kittisupakorn, Paisan

    2017-08-01

    This research work proposes an extended Kalman filter (EKF) estimator to give estimates of product composition and a generic model controller (GMC) to control the temperature of a reactive distillation column (RDC). One of major difficulties to control the RDC is large time delays of product composition measurement. Therefore, the estimates of the product composition are needed and determined based on available and reliable measured tray temperature via the extended Kalman Filter (EKF). With these estimates, the GMC controller is applied to control the RDC's temperature. The performance of the EKF estimator under the GMC control is evaluated in various disturbances and set point change.

  8. Extended Kalman filter (EKF) application in vitamin C two-step fermentation process.

    Science.gov (United States)

    Wei, D; Yuan, W; Yuan, Z; Yin, G; Chen, M

    1993-01-01

    Based on kinetic model study of vitamin C two-step fermentation, the extended Kalman filter (EKF) theory is conducted for studying the process which is disturbed by white noise to some extent caused by the model, the fermentation system and operation fluctuation. EKF shows that calculated results from estimated process parameters agree with the experimental results considerably better than model prediction without using estimated parameters. Parameter analysis gives a better understanding of the kinetics and provides a basis for state estimation and state prediction.

  9. Low-cost attitude determination system using an extended Kalman filter (EKF) algorithm

    Science.gov (United States)

    Esteves, Fernando M.; Nehmetallah, Georges; Abot, Jandro L.

    2016-05-01

    Attitude determination is one of the most important subsystems in spacecraft, satellite, or scientific balloon mission s, since it can be combined with actuators to provide rate stabilization and pointing accuracy for payloads. In this paper, a low-cost attitude determination system with a precision in the order of arc-seconds that uses low-cost commercial sensors is presented including a set of uncorrelated MEMS gyroscopes, two clinometers, and a magnetometer in a hierarchical manner. The faster and less precise sensors are updated by the slower, but more precise ones through an Extended Kalman Filter (EKF)-based data fusion algorithm. A revision of the EKF algorithm fundamentals and its implementation to the current application, are presented along with an analysis of sensors noise. Finally, the results from the data fusion algorithm implementation are discussed in detail.

  10. Convergence and Consistency Analysis for A 3D Invariant-EKF SLAM

    OpenAIRE

    Zhang, Teng; Wu, Kanzhi; Song, Jingwei; Huang, Shoudong; Dissanayake, Gamini

    2017-01-01

    In this paper, we investigate the convergence and consistency properties of an Invariant-Extended Kalman Filter (RI-EKF) based Simultaneous Localization and Mapping (SLAM) algorithm. Basic convergence properties of this algorithm are proven. These proofs do not require the restrictive assumption that the Jacobians of the motion and observation models need to be evaluated at the ground truth. It is also shown that the output of RI-EKF is invariant under any stochastic rigid body transformation...

  11. Very-low speed control of PMSM based on EKF estimation with closed loop optimized parameters.

    Science.gov (United States)

    Xu, Dong; Zhang, Shaoguang; Liu, Jingmeng

    2013-11-01

    When calculating the speed from the position of permanent magnet synchronous motor (PMSM), the accuracy and real-time are limited by the precision of the sensor. This problem causes crawling and jitter at very-low speed. Using the angle from the position sensor, an extended Kalman filter (EKF) designed in dq-coordinate is presented to solve this problem. The usage of position sensor simplifies the model and improves the accuracy of speed estimation. Specially, a closed loop optimal (CLO) method is devised to overcome the difficulty to adjust the parameters of the EKF. The EKF is the feedback link of speed control, CLO method is derived from the perspective of the speed step response to optimize the measurement covariance matrix and the system covariance matrix of EKF. Simulation and experimental results, comparing the low-speed performance of the EKF and sensor feedback methods, prove the effectiveness of the method to adjust the parameters of EKF and the advantages in eliminating the low speed jitter. © 2013 ISA. Published by ISA. All rights reserved.

  12. Active Fault Diagnosis for Hybrid Systems Based on Sensitivity Analysis and EKF

    DEFF Research Database (Denmark)

    Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas

    2011-01-01

    in the estimation of the corresponding parameter. The fault detection and isolation is done by comparing the nominal parameters with those estimated by Extended Kalman Filter (EKF). In study, Gaussian noise is used as the input disturbance as well as the measurement noise for simulation. The method is implemented...

  13. A unified model for transfer alignment at random misalignment angles based on second-order EKF

    International Nuclear Information System (INIS)

    Cui, Xiao; Qin, Yongyuan; Yan, Gongmin; Liu, Zhenbo; Mei, Chunbo

    2017-01-01

    In the transfer alignment process of inertial navigation systems (INSs), the conventional linear error model based on the small misalignment angle assumption cannot be applied to large misalignment situations. Furthermore, the nonlinear model based on the large misalignment angle suffers from redundant computation with nonlinear filters. This paper presents a unified model for transfer alignment suitable for arbitrary misalignment angles. The alignment problem is transformed into an estimation of the relative attitude between the master INS (MINS) and the slave INS (SINS), by decomposing the attitude matrix of the latter. Based on the Rodriguez parameters, a unified alignment model in the inertial frame with the linear state-space equation and a second order nonlinear measurement equation are established, without making any assumptions about the misalignment angles. Furthermore, we employ the Taylor series expansions on the second-order nonlinear measurement equation to implement the second-order extended Kalman filter (EKF2). Monte-Carlo simulations demonstrate that the initial alignment can be fulfilled within 10 s, with higher accuracy and much smaller computational cost compared with the traditional unscented Kalman filter (UKF) at large misalignment angles. (paper)

  14. A unified model for transfer alignment at random misalignment angles based on second-order EKF

    Science.gov (United States)

    Cui, Xiao; Mei, Chunbo; Qin, Yongyuan; Yan, Gongmin; Liu, Zhenbo

    2017-04-01

    In the transfer alignment process of inertial navigation systems (INSs), the conventional linear error model based on the small misalignment angle assumption cannot be applied to large misalignment situations. Furthermore, the nonlinear model based on the large misalignment angle suffers from redundant computation with nonlinear filters. This paper presents a unified model for transfer alignment suitable for arbitrary misalignment angles. The alignment problem is transformed into an estimation of the relative attitude between the master INS (MINS) and the slave INS (SINS), by decomposing the attitude matrix of the latter. Based on the Rodriguez parameters, a unified alignment model in the inertial frame with the linear state-space equation and a second order nonlinear measurement equation are established, without making any assumptions about the misalignment angles. Furthermore, we employ the Taylor series expansions on the second-order nonlinear measurement equation to implement the second-order extended Kalman filter (EKF2). Monte-Carlo simulations demonstrate that the initial alignment can be fulfilled within 10 s, with higher accuracy and much smaller computational cost compared with the traditional unscented Kalman filter (UKF) at large misalignment angles.

  15. An EKF-based approach for estimating leg stiffness during walking.

    Science.gov (United States)

    Ochoa-Diaz, Claudia; Menegaz, Henrique M; Bó, Antônio P L; Borges, Geovany A

    2013-01-01

    The spring-like behavior is an inherent condition for human walking and running. Since leg stiffness k(leg) is a parameter that cannot be directly measured, many techniques has been proposed in order to estimate it, most of them using force data. This paper intends to address this problem using an Extended Kalman Filter (EKF) based on the Spring-Loaded Inverted Pendulum (SLIP) model. The formulation of the filter only uses as measurement information the Center of Mass (CoM) position and velocity, no a priori information about the stiffness value is known. From simulation results, it is shown that the EKF-based approach can generate a reliable stiffness estimation for walking.

  16. An Enhanced Error Model for EKF-Based Tightly-Coupled Integration of GPS and Land Vehicle's Motion Sensors.

    Science.gov (United States)

    Karamat, Tashfeen B; Atia, Mohamed M; Noureldin, Aboelmagd

    2015-09-22

    Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers' measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer's errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories' data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance.

  17. Mover Position Detection for PMTLM Based on Linear Hall Sensors through EKF Processing.

    Science.gov (United States)

    Yan, Leyang; Zhang, Hui; Ye, Peiqing

    2017-04-06

    Accurate mover position is vital for a permanent magnet tubular linear motor (PMTLM) control system. In this paper, two linear Hall sensors are utilized to detect the mover position. However, Hall sensor signals contain third-order harmonics, creating errors in mover position detection. To filter out the third-order harmonics, a signal processing method based on the extended Kalman filter (EKF) is presented. The limitation of conventional processing method is first analyzed, and then EKF is adopted to detect the mover position. In the EKF model, the amplitude of the fundamental component and the percentage of the harmonic component are taken as state variables, and they can be estimated based solely on the measured sensor signals. Then, the harmonic component can be calculated and eliminated. The proposed method has the advantages of faster convergence, better stability and higher accuracy. Finally, experimental results validate the effectiveness and superiority of the proposed method.

  18. An Enhanced Error Model for EKF-Based Tightly-Coupled Integration of GPS and Land Vehicle’s Motion Sensors

    Science.gov (United States)

    Karamat, Tashfeen B.; Atia, Mohamed M.; Noureldin, Aboelmagd

    2015-01-01

    Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers’ measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer’s errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories’ data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance. PMID:26402680

  19. Dual-EKF-Based Real-Time Celestial Navigation for Lunar Rover

    Directory of Open Access Journals (Sweden)

    Li Xie

    2012-01-01

    Full Text Available A key requirement of lunar rover autonomous navigation is to acquire state information accurately in real-time during its motion and set up a gradual parameter-based nonlinear kinematics model for the rover. In this paper, we propose a dual-extended-Kalman-filter- (dual-EKF- based real-time celestial navigation (RCN method. The proposed method considers the rover position and velocity on the lunar surface as the system parameters and establishes a constant velocity (CV model. In addition, the attitude quaternion is considered as the system state, and the quaternion differential equation is established as the state equation, which incorporates the output of angular rate gyroscope. Therefore, the measurement equation can be established with sun direction vector from the sun sensor and speed observation from the speedometer. The gyro continuous output ensures the algorithm real-time operation. Finally, we use the dual-EKF method to solve the system equations. Simulation results show that the proposed method can acquire the rover position and heading information in real time and greatly improve the navigation accuracy. Our method overcomes the disadvantage of the cumulative error in inertial navigation.

  20. Comparison Study on the Battery SoC Estimation with EKF and UKF Algorithms

    Directory of Open Access Journals (Sweden)

    Hongwen He

    2013-09-01

    Full Text Available The battery state of charge (SoC, whose estimation is one of the basic functions of battery management system (BMS, is a vital input parameter in the energy management and power distribution control of electric vehicles (EVs. In this paper, two methods based on an extended Kalman filter (EKF and unscented Kalman filter (UKF, respectively, are proposed to estimate the SoC of a lithium-ion battery used in EVs. The lithium-ion battery is modeled with the Thevenin model and the model parameters are identified based on experimental data and validated with the Beijing Driving Cycle. Then space equations used for SoC estimation are established. The SoC estimation results with EKF and UKF are compared in aspects of accuracy and convergence. It is concluded that the two algorithms both perform well, while the UKF algorithm is much better with a faster convergence ability and a higher accuracy.

  1. Quaternion normalization in additive EKF for spacecraft attitude determination

    Science.gov (United States)

    Bar-Itzhack, I. Y.; Deutschmann, J.; Markley, F. L.

    1991-01-01

    This work introduces, examines, and compares several quaternion normalization algorithms, which are shown to be an effective stage in the application of the additive extended Kalman filter (EKF) to spacecraft attitude determination, which is based on vector measurements. Two new normalization schemes are introduced. They are compared with one another and with the known brute force normalization scheme, and their efficiency is examined. Simulated satellite data are used to demonstrate the performance of all three schemes. A fourth scheme is suggested for future research. Although the schemes were tested for spacecraft attitude determination, the conclusions are general and hold for attitude determination of any three dimensional body when based on vector measurements, and use an additive EKF for estimation, and the quaternion for specifying the attitude.

  2. Mixed error compensation in a heterodyne interferometer using the iterated dual-EKF algorithm

    International Nuclear Information System (INIS)

    Lee, Woo Ram; Kim, Chang Rai; You, Kwan Ho

    2010-01-01

    The heterodyne laser interferometer has been widely used in the field of precise measurements. The limited measurement accuracy of a heterodyne laser interferometer arises from the periodic nonlinearity caused by non-ideal laser sources and imperfect optical components. In this paper, the iterated dual-EKF algorithm is used to compensate for the error caused by nonlinearity and external noise. With the iterated dual-EKF algorithm, the weight filter estimates the parameter uncertainties in the state equation caused by nonlinearity errors and has a high convergence rate of weight values due to the iteration process. To verify the performance of the proposed compensation algorithm, we present experimental results obtained by using the iterated dual-EKF algorithm and compare them with the results obtained by using a capacitance displacement sensor.

  3. Mixed error compensation in a heterodyne interferometer using the iterated dual-EKF algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Woo Ram; Kim, Chang Rai; You, Kwan Ho [Sungkyunkwan University, Suwon (Korea, Republic of)

    2010-10-15

    The heterodyne laser interferometer has been widely used in the field of precise measurements. The limited measurement accuracy of a heterodyne laser interferometer arises from the periodic nonlinearity caused by non-ideal laser sources and imperfect optical components. In this paper, the iterated dual-EKF algorithm is used to compensate for the error caused by nonlinearity and external noise. With the iterated dual-EKF algorithm, the weight filter estimates the parameter uncertainties in the state equation caused by nonlinearity errors and has a high convergence rate of weight values due to the iteration process. To verify the performance of the proposed compensation algorithm, we present experimental results obtained by using the iterated dual-EKF algorithm and compare them with the results obtained by using a capacitance displacement sensor.

  4. A Sensorless Predictive Current Controlled Boost Converter by Using an EKF with Load Variation Effect Elimination Function.

    Science.gov (United States)

    Tong, Qiaoling; Chen, Chen; Zhang, Qiao; Zou, Xuecheng

    2015-04-28

    To realize accurate current control for a boost converter, a precise measurement of the inductor current is required to achieve high resolution current regulating. Current sensors are widely used to measure the inductor current. However, the current sensors and their processing circuits significantly contribute extra hardware cost, delay and noise to the system. They can also harm the system reliability. Therefore, current sensorless control techniques can bring cost effective and reliable solutions for various boost converter applications. According to the derived accurate model, which contains a number of parasitics, the boost converter is a nonlinear system. An Extended Kalman Filter (EKF) is proposed for inductor current estimation and output voltage filtering. With this approach, the system can have the same advantages as sensored current control mode. To implement EKF, the load value is necessary. However, the load may vary from time to time. This can lead to errors of current estimation and filtered output voltage. To solve this issue, a load variation elimination effect elimination (LVEE) module is added. In addition, a predictive average current controller is used to regulate the current. Compared with conventional voltage controlled system, the transient response is greatly improved since it only takes two switching cycles for the current to reach its reference. Finally, experimental results are presented to verify the stable operation and output tracking capability for large-signal transients of the proposed algorithm.

  5. Switching EKF technique for rotor and stator resistance estimation in speed sensorless control of IMs

    International Nuclear Information System (INIS)

    Barut, Murat; Bogosyan, Seta; Gokasan, Metin

    2007-01-01

    High performance speed sensorless control of induction motors (IMs) calls for estimation and control schemes that offer solutions to parameter uncertainties as well as to difficulties involved with accurate flux/velocity estimation at very low and zero speed. In this study, a new EKF based estimation algorithm is proposed for the solution of both problems and is applied in combination with speed sensorless direct vector control (DVC). The technique is based on the consecutive execution of two EKF algorithms, by switching from one algorithm to another at every n sampling periods. The number of sampling periods, n, is determined based on the desired system performance. The switching EKF approach, thus applied, provides an accurate estimation of an increased number of parameters than would be possible with a single EKF algorithm. The simultaneous and accurate estimation of rotor, R r ' and stator, R s resistances, both in the transient and steady state, is an important challenge in speed sensorless IM control and reported studies achieving satisfactory results are few, if any. With the proposed technique in this study, the sensorless estimation of R r ' and R s is achieved in transient and steady state and in both high and low speed operation while also estimating the unknown load torque, velocity, flux and current components. The performance demonstrated by the simulation results at zero speed, as well as at low and high speed operation is very promising when compared with individual EKF algorithms performing either R r ' or R s estimation or with the few other approaches taken in past studies, which require either signal injection and/or a change of algorithms based on the speed range. The results also motivate utilization of the technique for multiple parameter estimation in a variety of control methods

  6. Generalized Optimal-State-Constraint Extended Kalman Filter (OSC-EKF)

    Science.gov (United States)

    2017-02-01

    algorithms is demonstrated by achieving reasonable consistency and accuracy on a challenging micro aerial vehicle dataset. simultaneous localization...platforms exist,4 and many others have been constructed with low-cost components. Visual-inertial simultaneous localization and mapping (SLAM) and...epipolar constraints. The OSC-EKF used a window size of 10 frames. The SAM problem was constructed using an inverse -depth feature position param

  7. EKF-based fault detection for guided missiles flight control system

    Science.gov (United States)

    Feng, Gang; Yang, Zhiyong; Liu, Yongjin

    2017-03-01

    The guided missiles flight control system is essential for guidance accuracy and kill probability. It is complicated and fragile. Since actuator faults and sensor faults could seriously affect the security and reliability of the system, fault detection for missiles flight control system is of great significance. This paper deals with the problem of fault detection for the closed-loop nonlinear model of the guided missiles flight control system in the presence of disturbance. First, set up the fault model of flight control system, and then design the residual generation based on the extended Kalman filter (EKF) for the Eulerian-discrete fault model. After that, the Chi-square test was selected for the residual evaluation and the fault detention task for guided missiles closed-loop system was accomplished. Finally, simulation results are provided to illustrate the effectiveness of the approach proposed in the case of elevator fault separately.

  8. Superimposed chirped pulse parameter estimation based on the extended Kalman filter (EKF)

    CSIR Research Space (South Africa)

    Olivier, JC

    2009-05-01

    Full Text Available An extended Kalman filter (EKF) is proposed to estimate the frequencies and chirp rate of multiple superimposed chirped pulses. The estimation problem is a difficult one, where maximum likelyhood methods are very complex especially if more than two...

  9. A hybrid algorithm combining EKF and RLS in synchronous estimation of road grade and vehicle' mass for a hybrid electric bus

    Science.gov (United States)

    Sun, Yong; Li, Liang; Yan, Bingjie; Yang, Chao; Tang, Gongyou

    2016-02-01

    This paper proposes a novel hybrid algorithm for simultaneously estimating the vehicle mass and road grade for hybrid electric bus (HEB). First, the road grade in current step is estimated using extended Kalman filter (EKF) with the initial state including velocity and engine torque. Second, the vehicle mass is estimated twice, one with EKF and the other with recursive least square (RLS) using the estimated road grade. A more accurate value of the estimated mass is acquired by weighting the trade-off between EKF and RLS. Finally, the road grade and vehicle mass thus obtained are used as the initial states for the next step, and two variables could be decoupled from the nonlinear vehicle dynamics by performing the above procedure repeatedly. Simulation results show that in different starting conditions, the proposed algorithm provides higher accuracy and faster convergence speed, compared with the results using EKF or RLS alone.

  10. Novel Formulation of Adaptive MPC as EKF Using ANN Model: Multiproduct Semibatch Polymerization Reactor Case Study.

    Science.gov (United States)

    Kamesh, Reddi; Rani, Kalipatnapu Yamuna

    2017-12-01

    In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon. An industrial case study for temperature control of a multiproduct semibatch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANN-EKFMPC strategy at supervisory level as a cascade control configuration along with proportional integral controller [ANN-EKFMPC with PI (ANN-EKFMPC-PI)]. The proposed approach is formulated incorporating all aspects of MPC including move suppression factor for control effort minimization and constraint-handling capability including terminal constraints. The nominal stability analysis and offset-free tracking capabilities of the proposed controller are proved. Its performance is evaluated by comparison with a standard MPC-based cascade control approach using the same adaptive ANN model. The ANN-EKFMPC-PI control configuration has shown better controller performance in terms of temperature tracking, smoother input profiles, as well as constraint-handling ability compared with the ANN-MPC with PI approach for two products in summer and winter. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.

  11. A Practical Method for Implementing an Attitude and Heading Reference System

    Directory of Open Access Journals (Sweden)

    Rodrigo Munguía

    2014-04-01

    Full Text Available This paper describes a practical and reliable algorithm for implementing an Attitude and Heading Reference System (AHRS. This kind of system is essential for real time vehicle navigation, guidance and control applications. When low cost sensors are used, efficient and robust algorithms are required for performance to be acceptable. The proposed method is based on an Extended Kalman Filter (EKF in a direct configuration. In this case, the filter is explicitly derived from both the kinematic and error models. The selection of this kind of EKF configuration can help in ensuring a tight integration of the method for its use in filter-based localization and mapping systems in autonomous vehicles. Experiments with real data show that the proposed method is able to maintain an accurate and drift-free attitude and heading estimation. An additional result is to show that there is no ostensible reason for preferring that the filter have an indirect configuration over a direct configuration for implementing an AHRS system.

  12. Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations.

    Science.gov (United States)

    Tornøe, Christoffer W; Overgaard, Rune V; Agersø, Henrik; Nielsen, Henrik A; Madsen, Henrik; Jonsson, E Niclas

    2005-08-01

    The objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling. The intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types of noise: a measurement and a system noise term. The measurement noise represents uncorrelated error due to, for example, assay error while the system noise accounts for structural misspecifications, approximations of the dynamical model, and true random physiological fluctuations. Since the system noise accounts for model misspecifications, the SDEs provide a diagnostic tool for model appropriateness. The focus of the article is on the implementation of the Extended Kalman Filter (EKF) in NONMEM for parameter estimation in SDE models. Various applications of SDEs in population PK/PD modeling are illustrated through a systematic model development example using clinical PK data of the gonadotropin releasing hormone (GnRH) antagonist degarelix. The dynamic noise estimates were used to track variations in model parameters and systematically build an absorption model for subcutaneously administered degarelix. The EKF-based algorithm was successfully implemented in NONMEM for parameter estimation in population PK/PD models described by systems of SDEs. The example indicated that it was possible to pinpoint structural model deficiencies, and that valuable information may be obtained by tracking unexplained variations in parameters.

  13. Adaptyvaus 2d pozicionavimo metodo autonominiam robotui tyrimas

    OpenAIRE

    Senvaitis, Vytautas

    2016-01-01

    Overview SLAM algorithm, laser distance scanner working principle, EKF and UKF filters in analytical part. EKF mathematical models are implemented for autonomous robot whit two-wheel drive and for laser distance scanner. EKF and UKF filters are compared. 2D robot positioning with EKF filter are modeled and simulated in MATALB and STM32 microcontroller with DSP library. MATLAB and STM32 are compared in speed test. Analyzing EKF filter working. Design and construct autonomous robot experimental...

  14. An extended Kalman filter approach to non-stationary Bayesian estimation of reduced-order vocal fold model parameters.

    Science.gov (United States)

    Hadwin, Paul J; Peterson, Sean D

    2017-04-01

    The Bayesian framework for parameter inference provides a basis from which subject-specific reduced-order vocal fold models can be generated. Previously, it has been shown that a particle filter technique is capable of producing estimates and associated credibility intervals of time-varying reduced-order vocal fold model parameters. However, the particle filter approach is difficult to implement and has a high computational cost, which can be barriers to clinical adoption. This work presents an alternative estimation strategy based upon Kalman filtering aimed at reducing the computational cost of subject-specific model development. The robustness of this approach to Gaussian and non-Gaussian noise is discussed. The extended Kalman filter (EKF) approach is found to perform very well in comparison with the particle filter technique at dramatically lower computational cost. Based upon the test cases explored, the EKF is comparable in terms of accuracy to the particle filter technique when greater than 6000 particles are employed; if less particles are employed, the EKF actually performs better. For comparable levels of accuracy, the solution time is reduced by 2 orders of magnitude when employing the EKF. By virtue of the approximations used in the EKF, however, the credibility intervals tend to be slightly underpredicted.

  15. A low false negative filter for detecting rare bird species from short video segments using a probable observation data set-based EKF method.

    Science.gov (United States)

    Song, Dezhen; Xu, Yiliang

    2010-09-01

    We report a new filter to assist the search for rare bird species. Since a rare bird only appears in front of a camera with very low occurrence (e.g., less than ten times per year) for very short duration (e.g., less than a fraction of a second), our algorithm must have a very low false negative rate. We verify the bird body axis information with the known bird flying dynamics from the short video segment. Since a regular extended Kalman filter (EKF) cannot converge due to high measurement error and limited data, we develop a novel probable observation data set (PODS)-based EKF method. The new PODS-EKF searches the measurement error range for all probable observation data that ensures the convergence of the corresponding EKF in short time frame. The algorithm has been extensively tested using both simulated inputs and real video data of four representative bird species. In the physical experiments, our algorithm has been tested on rock pigeons and red-tailed hawks with 119 motion sequences. The area under the ROC curve is 95.0%. During the one-year search of ivory-billed woodpeckers, the system reduces the raw video data of 29.41 TB to only 146.7 MB (reduction rate 99.9995%).

  16. Multi-Zone hybrid model for failure detection of the stable ventilation systems

    DEFF Research Database (Denmark)

    Gholami, Mehdi; Schiøler, Henrik; Soltani, Mohsen

    2010-01-01

    In this paper, a conceptual multi-zone model for climate control of a live stock building is elaborated. The main challenge of this research is to estimate the parameters of a nonlinear hybrid model. A recursive estimation algorithm, the Extended Kalman Filter (EKF) is implemented for estimation....... Since the EKF is sensitive to the initial guess, in the following the estimation process is split up into simple parts and approximate parameters are found with a non recursive least squares method in order to provide good initial values. Results based on experiments from a real life stable facility...

  17. Visual EKF-SLAM from Heterogeneous Landmarks.

    Science.gov (United States)

    Esparza-Jiménez, Jorge Othón; Devy, Michel; Gordillo, José L

    2016-04-07

    Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology.

  18. Development of a soft-sensor based on multi-wavelength fluorescence spectroscopy and a dynamic metabolic model for monitoring mammalian cell cultures.

    Science.gov (United States)

    Ohadi, Kaveh; Legge, Raymond L; Budman, Hector M

    2015-01-01

    A soft-sensor based on an Extended Kalman Filter (EKF) that combines data obtained using a fluorescence-based soft-sensor with a dynamic mechanistic model, was investigated as a tool for continuous monitoring of a Chinese hamster ovary (CHO) cell cultivation process. A standalone fluorescence based soft-sensor, which uses a combination of an empirical multivariate statistical model and measured spectra, was designed for predicting key culture variables including viable and dead cells, recombinant protein, glucose, and ammonia concentrations. The standalone fluorescence sensor was then combined with a dynamic mechanistic model within an EKF framework, for improving the prediction accuracy and generating predictions in-between sampling instances. The dynamic model used for the EKF framework was based on a structured metabolic flux analysis and mass balances. In order to calibrate the fluorescence-based empirical model and the dynamic mechanistic model, cells were grown in batch mode with different initial glucose and glutamine concentrations. To mitigate the uncertainty associated with the model structure and parameters, non-stationary disturbances were accounted for in the EKF by parameter-adaptation. It was demonstrated that the implementation of the EKF along with the dynamic model could improve the accuracy of the fluorescence-based predictions at the sampling instances. Additionally, it was shown that the major advantage of the EKF-based soft-sensor, compared to the standalone fluorescence-based counterpart, was its capability to track the temporal evolution of key process variables between measurement instances obtained by the fluorescence-based soft-sensor. This is crucial for designing control strategies of CHO cell cultures with the aim of guaranteeing product quality. © 2014 Wiley Periodicals, Inc.

  19. A comparison of nonlinear filtering approaches in the context of an HIV model.

    Science.gov (United States)

    Banks, H Thomas; Hu, Shuhua; Kenz, Zackary R; Tran, Hien T

    2010-04-01

    In this paper three different filtering methods, the Extended Kalman Filter (EKF), the Gauss-Hermite Filter (GHF), and the Unscented Kalman Filter (UKF), are compared for state-only and coupled state and parameter estimation when used with log state variables of a model of the immunologic response to the human immunodeficiency virus (HIV) in individuals. The filters are implemented to estimate model states as well as model parameters from simulated noisy data, and are compared in terms of estimation accuracy and computational time. Numerical experiments reveal that the GHF is the most computationally expensive algorithm, while the EKF is the least expensive one. In addition, computational experiments suggest that there is little difference in the estimation accuracy between the UKF and GHF. When measurements are taken as frequently as every week to two weeks, the EKF is the superior filter. When measurements are further apart, the UKF is the best choice in the problem under investigation.

  20. Dynamic Modeling and Real-Time Monitoring of Froth Flotation

    Directory of Open Access Journals (Sweden)

    Khushaal Popli

    2015-08-01

    Full Text Available A dynamic fundamental model was developed linking processes from the microscopic scale to the equipment scale for batch froth flotation. State estimation, fault detection, and disturbance identification were implemented using the extended Kalman filter (EKF, which reconciles real-time measurements with dynamic models. The online measurements for the EKF were obtained through image analysis of froth images that were captured and analyzed using the commercial package VisioFroth (Metsor Minerals. The extracted image features were then correlated to recovery using principal component analysis and partial least squares regression. The performance of real-time state estimation and fault detection was validated using batch flotation of pure galena at various operating conditions. The image features that were strongly representative of recovery were identified, and calibration and validation were performed against off-line measurements of recovery. The EKF successfully captured the dynamics of the process by updating the model states and parameters using the online measurements. Finally, disturbances in the air flow rate and impeller speed were introduced into the system, and the dynamic behavior of the flotation process was successfully tracked and the disturbances were identified using state estimation.

  1. Sensorless Control of Late-Stage Offshore DFIG-WT with FSTP Converters by Using EKF to Ride through Hybrid Faults

    Directory of Open Access Journals (Sweden)

    Wei Li

    2017-11-01

    Full Text Available A hybrid fault scenario in a late-stage offshore doubly-fed induction generator (DFIG-based wind turbine (DFIG-WT with converter open-circuit fault and position sensor failure is investigated in this paper. An extended Kalman filter (EKF-based sensorless control strategy is utilized to eliminate the encoder. Based on the detailed analysis of the seventh-order dynamic state space model of DFIG, along with the input voltage signals and measured current signals, the EKF algorithm for DFIG is designed to estimate the rotor speed and position. In addition, the bridge arm open circuit in the back-to-back (BTB power converter of DFIG is taken as a commonly-encountered fault due to the fragility of semiconductor switches. Four-switch three-phase (FSTP topology-based fault-tolerant converters are employed for post-fault operation by considering the minimization of switching losses and reducing the circuit complexity. Moreover, a simplified space vector pulse width modulation (SVPWM technique is proposed to reduce the computational burden, and a voltage balancing scheme is put forward to increase the DC-bus voltage utilization rate. Simulation studies are carried out in MATLAB/Simulink2017a (MathWorks, Natick, MA, USA to demonstrate the validity of the proposed hybrid fault-tolerant strategy for DFIG-WT, with the wind speed fluctuation, measurement noises and grid voltage sag taken into consideration.

  2. Visual EKF-SLAM from Heterogeneous Landmarks †

    Science.gov (United States)

    Esparza-Jiménez, Jorge Othón; Devy, Michel; Gordillo, José L.

    2016-01-01

    Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology. PMID:27070602

  3. Sensorless SPMSM Position Estimation Using Position Estimation Error Suppression Control and EKF in Wide Speed Range

    Directory of Open Access Journals (Sweden)

    Zhanshan Wang

    2014-01-01

    Full Text Available The control of a high performance alternative current (AC motor drive under sensorless operation needs the accurate estimation of rotor position. In this paper, one method of accurately estimating rotor position by using both motor complex number model based position estimation and position estimation error suppression proportion integral (PI controller is proposed for the sensorless control of the surface permanent magnet synchronous motor (SPMSM. In order to guarantee the accuracy of rotor position estimation in the flux-weakening region, one scheme of identifying the permanent magnet flux of SPMSM by extended Kalman filter (EKF is also proposed, which formed the effective combination method to realize the sensorless control of SPMSM with high accuracy. The simulation results demonstrated the validity and feasibility of the proposed position/speed estimation system.

  4. Intelligent classification of electrocardiogram (ECG) signal using extended Kalman Filter (EKF) based neuro fuzzy system.

    Science.gov (United States)

    Meau, Yeong Pong; Ibrahim, Fatimah; Narainasamy, Selvanathan A L; Omar, Razali

    2006-05-01

    This study presents the development of a hybrid system consisting of an ensemble of Extended Kalman Filter (EKF) based Multi Layer Perceptron Network (MLPN) and a one-pass learning Fuzzy Inference System using Look-up Table Scheme for the recognition of electrocardiogram (ECG) signals. This system can distinguish various types of abnormal ECG signals such as Ventricular Premature Cycle (VPC), T wave inversion (TINV), ST segment depression (STDP), and Supraventricular Tachycardia (SVT) from normal sinus rhythm (NSR) ECG signal.

  5. [Study on method of tracking the active cells in image sequences based on EKF-PF].

    Science.gov (United States)

    Tang, Chunming; Liu, Ying

    2013-02-01

    In cell image sequences, due to the nonlinear and nonGaussian motion characteristics of active cells, the accurate prediction and tracking is still an unsolved problem. We applied extended Kalman particle filter (EKF-PF) here in our study, attempting to solve the problem. Firstly we confirmed the existence and positions of the active cells. Then we established a motion model and improved it via adding motion angle estimation. Next we predicted motion parameters, such as displacement, velocity, accelerated velocity and motion angle, in region centers of the cells being tracked. Finally we obtained the motion traces of active cells. There were fourteen active cells in three image sequences which have been tracked. The errors were less than 2.5 pixels when the prediction values were compared with actual values. It showed that the presented algorithm may basically reach the solution of accurate predition and tracking of the active cells.

  6. High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders.

    Science.gov (United States)

    Huang, Haoqian; Chen, Xiyuan; Zhang, Bo; Wang, Jian

    2017-01-01

    The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Joint kinematics estimation using a multi-body kinematics optimisation and an extended Kalman filter, and embedding a soft tissue artefact model.

    Science.gov (United States)

    Bonnet, Vincent; Richard, Vincent; Camomilla, Valentina; Venture, Gentiane; Cappozzo, Aurelio; Dumas, Raphaël

    2017-09-06

    To reduce the impact of the soft tissue artefact (STA) on the estimate of skeletal movement using stereophotogrammetric and skin-marker data, multi-body kinematics optimisation (MKO) and extended Kalman filters (EKF) have been proposed. This paper assessed the feasibility and efficiency of these methods when they embed a mathematical model of the STA and simultaneously estimate the ankle, knee and hip joint kinematics and the model parameters. A STA model was used that provides an estimate of the STA affecting the marker-cluster located on a body segment as a function of the kinematics of the adjacent joints. The MKO and the EKF were implemented with and without the STA model. To assess these methods, intra-cortical pin and skin markers located on the thigh, shank, and foot of three subjects and tracked during the stance phase of running were used. Embedding the STA model in MKO and EKF reduced the average RMS of marker tracking from 12.6 to 1.6mm and from 4.3 to 1.9mm, respectively, showing that a STA model trial-specific calibration is feasible. Nevertheless, with the STA model embedded in MKO, the RMS difference between the estimated and the reference joint kinematics determined from the pin markers slightly increased (from 2.0 to 2.1deg) On the contrary, when the STA model was embedded in the EKF, this RMS difference was slightly reduced (from 2.0 to 1.7deg) thus showing a better potentiality of this method to attenuate STA effects and improve the accuracy of joint kinematics estimate. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression

    International Nuclear Information System (INIS)

    Bukhari, W; Hong, S-M

    2015-01-01

    Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR + , implements a gating function without pre-specifying a particular region of the patient’s breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR + algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR + implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR + in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR + . The experimental results show that the EKF-GPR + algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR + reduces the patient-wise RMS error to 37%, 39% and 42

  9. Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression

    Science.gov (United States)

    Bukhari, W.; Hong, S.-M.

    2015-01-01

    Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR+, implements a gating function without pre-specifying a particular region of the patient’s breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR+ algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR+ implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR+ in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR+. The experimental results show that the EKF-GPR+ algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR+ reduces the patient-wise RMS error to 37%, 39% and 42% in

  10. Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression.

    Science.gov (United States)

    Bukhari, W; Hong, S-M

    2015-01-07

    Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR(+), implements a gating function without pre-specifying a particular region of the patient's breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR(+) algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR(+) implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR(+) in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR(+). The experimental results show that the EKF-GPR(+) algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR(+) reduces the patient-wise RMS error to 37%, 39% and

  11. Model-Based Engine Control Architecture with an Extended Kalman Filter

    Science.gov (United States)

    Csank, Jeffrey T.; Connolly, Joseph W.

    2016-01-01

    This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The nonlinear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

  12. An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

    Science.gov (United States)

    Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

    2009-01-01

    In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

  13. Stochastic differential equations in NONMEM: implementation, application, and comparison with ordinary differential equations

    DEFF Research Database (Denmark)

    Tornøe, Christoffer Wenzel; Overgaard, Rune Viig; Agerso, H.

    2005-01-01

    of noise: a measurement and a system noise term. The measurement noise represents uncorrelated error due to, for example, assay error while the system noise accounts for structural misspecifications, approximations of the dynamical model, and true random physiological fluctuations. Since the system noise...... degarelix. Conclusions. The EKF-based algorithm was successfully implemented in NONMEM for parameter estimation in population PK/PD models described by systems of SDEs. The example indicated that it was possible to pinpoint structural model deficiencies, and that valuable information may be obtained......Purpose. The objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling. Methods. The intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types...

  14. Reactivity estimation during a reactivity-initiated accident using the extended Kalman filter

    International Nuclear Information System (INIS)

    Busquim e Silva, R.; Marques, A.L.F.; Cruz, J.J.; Shirvan, K.; Kazimi, M.S.

    2015-01-01

    Highlights: • The EKF is modeled using sophisticate strategies to make the algorithm robust and accurate. • For a supercritical reactor under RIA, the EKF presents better results compared to IPK method independent of magnitude of the noise loads. • A sensitivity for five distinct carry-over effects indicates that the EKF is less sensitive to the different set of noise. • Although the P3D/R5 simulates the reactivity using a spatial kinetics method, the use of PKRE to model the EKF provides accurate results. • The reactivity’s standard deviation is higher for the IKF method. • Under HZP (slow power response) the IPK reactivity varies widely from positive to negative values (add extra difficulty to controlling the supercritical reactor): the EKF method does not have similar behavior under the same conditions (better controlling the operation). - Abstract: This study implements the extended Kalman filter (EKF) to estimate the nuclear reactor reactivity behavior under a reactivity-initiated accident (RIA). A coupled neutronics/thermal hydraulics code PARCS/RELAP5 (P3D/R5) simulates a control rod assembly ejection (CRE) on a traditional 2272 MWt PWR to generate the reactor power profile. A MATLAB script adds random noise to the simulated reactor power. For comparison, the inverse point kinetics (IPK) deterministic method is also implemented. Three different cases of CRE are simulated and the EKF, IPK and the P3D/R5 reactivity are compared. It was found that the EKF method presents better results compared to the IPK method. Furthermore, under a RIA due to small reactivity insertion and slow power response, the IPK reactivity varies widely from positive to negative, which may add extra difficulty to the task of controlling a supercritical reactor. This feature is also confirmed by a sensitivity analysis for five different noise loads and three distinct noise measurements standard deviations (SD)

  15. Estimation of aircraft aerodynamic derivatives using Extended Kalman Filter

    OpenAIRE

    Curvo, M.

    2000-01-01

    Design of flight control laws, verification of performance predictions, and the implementation of flight simulations are tasks that require a mathematical model of the aircraft dynamics. The dynamical models are characterized by coefficients (aerodynamic derivatives) whose values must be determined from flight tests. This work outlines the use of the Extended Kalman Filter (EKF) in obtaining the aerodynamic derivatives of an aircraft. The EKF shows several advantages over the more traditional...

  16. Localization Improvement in Wireless Sensor Networks Using a New Statistical Channel Model

    DEFF Research Database (Denmark)

    Karimi Alavijeh, Amir; Ramezani, Hossein; Karimi Alavijeh, Ali

    2018-01-01

    of this statistical relationship, we have investigated the localization problem of a hidden node using extended Kalman filter (EKF). Compared to the conventional EKF in which the covariance matrix of measurement noise is fixed, this matrix can be updated online using the proposed model. The experimental...

  17. Density-based Monte Carlo filter and its applications in nonlinear stochastic differential equation models.

    Science.gov (United States)

    Huang, Guanghui; Wan, Jianping; Chen, Hui

    2013-02-01

    Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. State and force observers based on multibody models and the indirect Kalman filter

    Science.gov (United States)

    Sanjurjo, Emilio; Dopico, Daniel; Luaces, Alberto; Naya, Miguel Ángel

    2018-06-01

    The aim of this work is to present two new methods to provide state observers by combining multibody simulations with indirect extended Kalman filters. One of the methods presented provides also input force estimation. The observers have been applied to two mechanism with four different sensor configurations, and compared to other multibody-based observers found in the literature to evaluate their behavior, namely, the unscented Kalman filter (UKF), and the indirect extended Kalman filter with simplified Jacobians (errorEKF). The new methods have some more computational cost than the errorEKF, but still much less than the UKF. Regarding their accuracy, both are better than the errorEKF. The method with input force estimation outperforms also the UKF, while the method without force estimation achieves results almost identical to those of the UKF. All the methods have been implemented as a reusable MATLAB® toolkit which has been released as Open Source in https://github.com/MBDS/mbde-matlab.

  19. Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter

    International Nuclear Information System (INIS)

    Kao, Jim; Flicker, Dawn; Ide, Kayo; Ghil, Michael

    2006-01-01

    This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from a single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand

  20. On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

    Science.gov (United States)

    Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

    2017-10-01

    With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

  1. Development of an extended Kalman filter for the self-sensing application of a spring-biased shape memory alloy wire actuator

    International Nuclear Information System (INIS)

    Gurung, H; Banerjee, A

    2016-01-01

    This report presents the development of an extended Kalman filter (EKF) to harness the self-sensing capability of a shape memory alloy (SMA) wire, actuating a linear spring. The stress and temperature of the SMA wire, constituting the state of the system, are estimated using the EKF, from the measured change in electrical resistance (ER) of the SMA. The estimated stress is used to compute the change in length of the spring, eliminating the need for a displacement sensor. The system model used in the EKF comprises the heat balance equation and the constitutive relation of the SMA wire coupled with the force–displacement behavior of a spring. Both explicit and implicit approaches are adopted to evaluate the system model at each time-update step of the EKF. Next, in the measurement-update step, estimated states are updated based on the measured electrical resistance. It has been observed that for the same time step, the implicit approach consumes less computational time than the explicit method. To verify the implementation, EKF estimated states of the system are compared with those of an established model for different inputs to the SMA wire. An experimental setup is developed to measure the actual spring displacement and ER of the SMA, for any time-varying voltage applied to it. The process noise covariance is decided using a heuristic approach, whereas the measurement noise covariance is obtained experimentally. Finally, the EKF is used to estimate the spring displacement for a given input and the corresponding experimentally obtained ER of the SMA. The qualitative agreement between the EKF estimated displacement with that obtained experimentally reveals the true potential of this approach to harness the self-sensing capability of the SMA. (paper)

  2. Development of an extended Kalman filter for the self-sensing application of a spring-biased shape memory alloy wire actuator

    Science.gov (United States)

    Gurung, H.; Banerjee, A.

    2016-02-01

    This report presents the development of an extended Kalman filter (EKF) to harness the self-sensing capability of a shape memory alloy (SMA) wire, actuating a linear spring. The stress and temperature of the SMA wire, constituting the state of the system, are estimated using the EKF, from the measured change in electrical resistance (ER) of the SMA. The estimated stress is used to compute the change in length of the spring, eliminating the need for a displacement sensor. The system model used in the EKF comprises the heat balance equation and the constitutive relation of the SMA wire coupled with the force-displacement behavior of a spring. Both explicit and implicit approaches are adopted to evaluate the system model at each time-update step of the EKF. Next, in the measurement-update step, estimated states are updated based on the measured electrical resistance. It has been observed that for the same time step, the implicit approach consumes less computational time than the explicit method. To verify the implementation, EKF estimated states of the system are compared with those of an established model for different inputs to the SMA wire. An experimental setup is developed to measure the actual spring displacement and ER of the SMA, for any time-varying voltage applied to it. The process noise covariance is decided using a heuristic approach, whereas the measurement noise covariance is obtained experimentally. Finally, the EKF is used to estimate the spring displacement for a given input and the corresponding experimentally obtained ER of the SMA. The qualitative agreement between the EKF estimated displacement with that obtained experimentally reveals the true potential of this approach to harness the self-sensing capability of the SMA.

  3. A State Space Model for Spatial Updating of Remembered Visual Targets during Eye Movements.

    Science.gov (United States)

    Mohsenzadeh, Yalda; Dash, Suryadeep; Crawford, J Douglas

    2016-01-01

    In the oculomotor system, spatial updating is the ability to aim a saccade toward a remembered visual target position despite intervening eye movements. Although this has been the subject of extensive experimental investigation, there is still no unifying theoretical framework to explain the neural mechanism for this phenomenon, and how it influences visual signals in the brain. Here, we propose a unified state-space model (SSM) to account for the dynamics of spatial updating during two types of eye movement; saccades and smooth pursuit. Our proposed model is a non-linear SSM and implemented through a recurrent radial-basis-function neural network in a dual Extended Kalman filter (EKF) structure. The model parameters and internal states (remembered target position) are estimated sequentially using the EKF method. The proposed model replicates two fundamental experimental observations: continuous gaze-centered updating of visual memory-related activity during smooth pursuit, and predictive remapping of visual memory activity before and during saccades. Moreover, our model makes the new prediction that, when uncertainty of input signals is incorporated in the model, neural population activity and receptive fields expand just before and during saccades. These results suggest that visual remapping and motor updating are part of a common visuomotor mechanism, and that subjective perceptual constancy arises in part from training the visual system on motor tasks.

  4. On Inertial Body Tracking in the Presence of Model Calibration Errors.

    Science.gov (United States)

    Miezal, Markus; Taetz, Bertram; Bleser, Gabriele

    2016-07-22

    In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments-the IMU-to-segment calibrations, subsequently called I2S calibrations-to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and

  5. Hybrid extended particle filter (HEPF) for integrated inertial navigation and global positioning systems

    International Nuclear Information System (INIS)

    Aggarwal, Priyanka; Syed, Zainab; El-Sheimy, Naser

    2009-01-01

    Navigation includes the integration of methodologies and systems for estimating time-varying position, velocity and attitude of moving objects. Navigation incorporating the integrated inertial navigation system (INS) and global positioning system (GPS) generally requires extensive evaluations of nonlinear equations involving double integration. Currently, integrated navigation systems are commonly implemented using the extended Kalman filter (EKF). The EKF assumes a linearized process, measurement models and Gaussian noise distributions. These assumptions are unrealistic for highly nonlinear systems like land vehicle navigation and may cause filter divergence. A particle filter (PF) is developed to enhance integrated INS/GPS system performance as it can easily deal with nonlinearity and non-Gaussian noises. In this paper, a hybrid extended particle filter (HEPF) is developed as an alternative to the well-known EKF to achieve better navigation data accuracy for low-cost microelectromechanical system sensors. The results show that the HEPF performs better than the EKF during GPS outages, especially when simulated outages are located in periods with high vehicle dynamics

  6. Visual-based simultaneous localization and mapping and global positioning system correction for geo-localization of a mobile robot

    International Nuclear Information System (INIS)

    Berrabah, Sid Ahmed; Baudoin, Yvan; Sahli, Hichem

    2011-01-01

    This paper introduces an approach combining visual-based simultaneous localization and mapping (V-SLAM) and global positioning system (GPS) correction for accurate multi-sensor localization of an outdoor mobile robot in geo-referenced maps. The proposed framework combines two extended Kalman filters (EKF); the first one, referred to as the integration filter, is dedicated to the improvement of the GPS localization based on data from an inertial navigation system and wheels' encoders. The second EKF implements the V-SLAM process. The linear and angular velocities in the dynamic model of the V-SLAM EKF filter are given by the GPS/INS/Encoders integration filter. On the other hand, the output of the V-SLAM EKF filter is used to update the dynamics estimation in the integration filter and therefore the geo-referenced localization. This solution increases the accuracy and the robustness of the positioning during GPS outage and allows SLAM in less featured environments

  7. Generator Dynamic Model Validation and Parameter Calibration Using Phasor Measurements at the Point of Connection

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Zhenyu; Du, Pengwei; Kosterev, Dmitry; Yang, Steve

    2013-05-01

    Disturbance data recorded by phasor measurement units (PMU) offers opportunities to improve the integrity of dynamic models. However, manually tuning parameters through play-back events demands significant efforts and engineering experiences. In this paper, a calibration method using the extended Kalman filter (EKF) technique is proposed. The formulation of EKF with parameter calibration is discussed. Case studies are presented to demonstrate its validity. The proposed calibration method is cost-effective, complementary to traditional equipment testing for improving dynamic model quality.

  8. A Bioinspired Neural Model Based Extended Kalman Filter for Robot SLAM

    Directory of Open Access Journals (Sweden)

    Jianjun Ni

    2014-01-01

    Full Text Available Robot simultaneous localization and mapping (SLAM problem is a very important and challenging issue in the robotic field. The main tasks of SLAM include how to reduce the localization error and the estimated error of the landmarks and improve the robustness and accuracy of the algorithms. The extended Kalman filter (EKF based method is one of the most popular methods for SLAM. However, the accuracy of the EKF based SLAM algorithm will be reduced when the noise model is inaccurate. To solve this problem, a novel bioinspired neural model based SLAM approach is proposed in this paper. In the proposed approach, an adaptive EKF based SLAM structure is proposed, and a bioinspired neural model is used to adjust the weights of system noise and observation noise adaptively, which can guarantee the stability of the filter and the accuracy of the SLAM algorithm. The proposed approach can deal with the SLAM problem in various situations, for example, the noise is in abnormal conditions. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach.

  9. Interaction of Lyapunov vectors in the formulation of the nonlinear extension of the Kalman filter.

    Science.gov (United States)

    Palatella, Luigi; Trevisan, Anna

    2015-04-01

    When applied to strongly nonlinear chaotic dynamics the extended Kalman filter (EKF) is prone to divergence due to the difficulty of correctly forecasting the forecast error probability density function. In operational forecasting applications ensemble Kalman filters circumvent this problem with empirical procedures such as covariance inflation. This paper presents an extension of the EKF that includes nonlinear terms in the evolution of the forecast error estimate. This is achieved starting from a particular square-root implementation of the EKF with assimilation confined in the unstable subspace (EKF-AUS), that is, the span of the Lyapunov vectors with non-negative exponents. When the error evolution is nonlinear, the space where it is confined is no more restricted to the unstable and neutral subspace causing filter divergence. The algorithm presented here, denominated EKF-AUS-NL, includes the nonlinear terms in the error dynamics: These result from the nonlinear interaction among the leading Lyapunov vectors and account for all directions where the error growth may take place. Numerical results show that with the nonlinear terms included, filter divergence can be avoided. We test the algorithm on the Lorenz96 model, showing very promising results.

  10. Low-Rank Kalman Filtering in Subsurface Contaminant Transport Models

    KAUST Repository

    El Gharamti, Mohamad

    2010-01-01

    Understanding the geology and the hydrology of the subsurface is important to model the fluid flow and the behavior of the contaminant. It is essential to have an accurate knowledge of the movement of the contaminants in the porous media in order to track them and later extract them from the aquifer. A two-dimensional flow model is studied and then applied on a linear contaminant transport model in the same porous medium. Because of possible different sources of uncertainties, the deterministic model by itself cannot give exact estimations for the future contaminant state. Incorporating observations in the model can guide it to the true state. This is usually done using the Kalman filter (KF) when the system is linear and the extended Kalman filter (EKF) when the system is nonlinear. To overcome the high computational cost required by the KF, we use the singular evolutive Kalman filter (SEKF) and the singular evolutive extended Kalman filter (SEEKF) approximations of the KF operating with low-rank covariance matrices. The SEKF can be implemented on large dimensional contaminant problems while the usage of the KF is not possible. Experimental results show that with perfect and imperfect models, the low rank filters can provide as much accurate estimates as the full KF but at much less computational cost. Localization can help the filter analysis as long as there are enough neighborhood data to the point being analyzed. Estimating the permeabilities of the aquifer is successfully tackled using both the EKF and the SEEKF.

  11. Low-Rank Kalman Filtering in Subsurface Contaminant Transport Models

    KAUST Repository

    El Gharamti, Mohamad

    2010-12-01

    Understanding the geology and the hydrology of the subsurface is important to model the fluid flow and the behavior of the contaminant. It is essential to have an accurate knowledge of the movement of the contaminants in the porous media in order to track them and later extract them from the aquifer. A two-dimensional flow model is studied and then applied on a linear contaminant transport model in the same porous medium. Because of possible different sources of uncertainties, the deterministic model by itself cannot give exact estimations for the future contaminant state. Incorporating observations in the model can guide it to the true state. This is usually done using the Kalman filter (KF) when the system is linear and the extended Kalman filter (EKF) when the system is nonlinear. To overcome the high computational cost required by the KF, we use the singular evolutive Kalman filter (SEKF) and the singular evolutive extended Kalman filter (SEEKF) approximations of the KF operating with low-rank covariance matrices. The SEKF can be implemented on large dimensional contaminant problems while the usage of the KF is not possible. Experimental results show that with perfect and imperfect models, the low rank filters can provide as much accurate estimates as the full KF but at much less computational cost. Localization can help the filter analysis as long as there are enough neighborhood data to the point being analyzed. Estimating the permeabilities of the aquifer is successfully tackled using both the EKF and the SEEKF.

  12. Online transition matrix identification of the state evolution model for the extended Kalman filter in electrical impedance tomography

    International Nuclear Information System (INIS)

    Moura, Fernando S; Aya, Julio C C; Lima, Raul G; Fleury, Agenor T

    2008-01-01

    One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on contour electrical potential measurements caused by an imposed electrical current distribution into the boundary. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, it is observed poor tracking ability of the Extended Kalman Filter (EKF). An analytically developed evolution model is not feasible at this moment. The present work investigates the possibility of identifying the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model is identified using the history of resistivity distribution obtained by a sensitivity matrix based algorithm. To numerically identify the linear evolution model, it is used the Ibrahim Time Domain Method, normally used to identify the transition matrix on structural dynamics. The investigation was performed by numerical simulations of a time varying domain with the addition of noise. Numerical dificulties to compute the transition matrix were solved using a Tikhonov regularization. The EKF numerical simulations suggest that the tracking ability is significantly improved.

  13. EKF-GPR-Based Fingerprint Renovation for Subset-Based Indoor Localization with Adjusted Cosine Similarity.

    Science.gov (United States)

    Yang, Junhua; Li, Yong; Cheng, Wei; Liu, Yang; Liu, Chenxi

    2018-01-22

    Received Signal Strength Indicator (RSSI) localization using fingerprint has become a prevailing approach for indoor localization. However, the fingerprint-collecting work is repetitive and time-consuming. After the original fingerprint radio map is built, it is laborious to upgrade the radio map. In this paper, we describe a Fingerprint Renovation System (FRS) based on crowdsourcing, which avoids the use of manual labour to obtain the up-to-date fingerprint status. Extended Kalman Filter (EKF) and Gaussian Process Regression (GPR) in FRS are combined to calculate the current state based on the original fingerprinting radio map. In this system, a method of subset acquisition also makes an immediate impression to reduce the huge computation caused by too many reference points (RPs). Meanwhile, adjusted cosine similarity (ACS) is employed in the online phase to solve the issue of outliers produced by cosine similarity. Both experiments and analytical simulation in a real Wireless Fidelity (Wi-Fi) environment indicate the usefulness of our system to significant performance improvements. The results show that FRS improves the accuracy by 19.6% in the surveyed area compared to the radio map un-renovated. Moreover, the proposed subset algorithm can bring less computation.

  14. Fast, Automated, Photo realistic, 3D Modeling of Building Interiors

    Science.gov (United States)

    2016-09-12

    runtime of the proposed EKF estimator is only linear in the acquisition time. Secondly, by including in our EKF estimator the laser scanner’s spatial...that the runtime of the proposed EKF estimator is only linear in the acquisition time. Secondly, by including in our EKF estimator the laser...34Berkeley Based Startups Win Big at ARPA-E" Indoor Reality was among three winners of a start-up pitch competition to a panel of four investors

  15. Active Fault Detection and Isolation for Hybrid Systems

    DEFF Research Database (Denmark)

    Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas

    2009-01-01

    An algorithm for active fault detection and isolation is proposed. In order to observe the failure hidden due to the normal operation of the controllers or the systems, an optimization problem based on minimization of test signal is used. The optimization based method imposes the normal and faulty...... models predicted outputs such that their discrepancies are observable by passive fault diagnosis technique. Isolation of different faults is done by implementation a bank of Extended Kalman Filter (EKF) where the convergence criterion for EKF is confirmed by Genetic Algorithm (GA). The method is applied...

  16. ECG Denoising Using Marginalized Particle Extended Kalman Filter With an Automatic Particle Weighting Strategy.

    Science.gov (United States)

    Hesar, Hamed Danandeh; Mohebbi, Maryam

    2017-05-01

    In this paper, a model-based Bayesian filtering framework called the "marginalized particle-extended Kalman filter (MP-EKF) algorithm" is proposed for electrocardiogram (ECG) denoising. This algorithm does not have the extended Kalman filter (EKF) shortcoming in handling non-Gaussian nonstationary situations because of its nonlinear framework. In addition, it has less computational complexity compared with particle filter. This filter improves ECG denoising performance by implementing marginalized particle filter framework while reducing its computational complexity using EKF framework. An automatic particle weighting strategy is also proposed here that controls the reliance of our framework to the acquired measurements. We evaluated the proposed filter on several normal ECGs selected from MIT-BIH normal sinus rhythm database. To do so, artificial white Gaussian and colored noises as well as nonstationary real muscle artifact (MA) noise over a range of low SNRs from 10 to -5 dB were added to these normal ECG segments. The benchmark methods were the EKF and extended Kalman smoother (EKS) algorithms which are the first model-based Bayesian algorithms introduced in the field of ECG denoising. From SNR viewpoint, the experiments showed that in the presence of Gaussian white noise, the proposed framework outperforms the EKF and EKS algorithms in lower input SNRs where the measurements and state model are not reliable. Owing to its nonlinear framework and particle weighting strategy, the proposed algorithm attained better results at all input SNRs in non-Gaussian nonstationary situations (such as presence of pink noise, brown noise, and real MA). In addition, the impact of the proposed filtering method on the distortion of diagnostic features of the ECG was investigated and compared with EKF/EKS methods using an ECG diagnostic distortion measure called the "Multi-Scale Entropy Based Weighted Distortion Measure" or MSEWPRD. The results revealed that our proposed

  17. Variable-State-Dimension Kalman-based Filter for orientation determination using inertial and magnetic sensors.

    Science.gov (United States)

    Sabatini, Angelo Maria

    2012-01-01

    In this paper a quaternion-based Variable-State-Dimension Extended Kalman Filter (VSD-EKF) is developed for estimating the three-dimensional orientation of a rigid body using the measurements from an Inertial Measurement Unit (IMU) integrated with a triaxial magnetic sensor. Gyro bias and magnetic disturbances are modeled and compensated by including them in the filter state vector. The VSD-EKF switches between a quiescent EKF, where the magnetic disturbance is modeled as a first-order Gauss-Markov stochastic process (GM-1), and a higher-order EKF where extra state components are introduced to model the time-rate of change of the magnetic field as a GM-1 stochastic process, namely the magnetic disturbance is modeled as a second-order Gauss-Markov stochastic process (GM-2). Experimental validation tests show the effectiveness of the VSD-EKF, as compared to either the quiescent EKF or the higher-order EKF when they run separately.

  18. Variable-State-Dimension Kalman-Based Filter for Orientation Determination Using Inertial and Magnetic Sensors

    Directory of Open Access Journals (Sweden)

    Angelo Maria Sabatini

    2012-06-01

    Full Text Available In this paper a quaternion-based Variable-State-Dimension Extended Kalman Filter (VSD-EKF is developed for estimating the three-dimensional orientation of a rigid body using the measurements from an Inertial Measurement Unit (IMU integrated with a triaxial magnetic sensor. Gyro bias and magnetic disturbances are modeled and compensated by including them in the filter state vector. The VSD-EKF switches between a quiescent EKF, where the magnetic disturbance is modeled as a first-order Gauss-Markov stochastic process (GM-1, and a higher-order EKF where extra state components are introduced to model the time-rate of change of the magnetic field as a GM-1 stochastic process, namely the magnetic disturbance is modeled as a second-order Gauss-Markov stochastic process (GM-2. Experimental validation tests show the effectiveness of the VSD-EKF, as compared to either the quiescent EKF or the higher-order EKF when they run separately.

  19. Development of hydrological models and surface process modelization Study case in High Mountain slopes

    International Nuclear Information System (INIS)

    Loaiza, Juan Carlos; Pauwels, Valentijn R

    2011-01-01

    Hydrological models are useful because allow to predict fluxes into the hydrological systems, which is useful to predict foods and violent phenomenon associated to water fluxes, especially in materials under a high meteorization level. The combination of these models with meteorological predictions, especially with rainfall models, allow to model water behavior into the soil. On most of cases, this type of models is really sensible to evapotranspiration. On climatic studies, the superficial processes have to be represented adequately. Calibration and validation of these models is necessary to obtain reliable results. This paper is a practical exercise of application of complete hydrological information at detailed scale in a high mountain catchment, considering the soil use and types more representatives. The information of soil moisture, infiltration, runoff and rainfall is used to calibrate and validate TOPLATS hydrological model to simulate the behavior of soil moisture. The finds show that is possible to implement an hydrological model by means of soil moisture information use and an equation of calibration by Extended Kalman Filter (EKF).

  20. Model Calibration of Exciter and PSS Using Extended Kalman Filter

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit; Du, Pengwei; Huang, Zhenyu

    2012-07-26

    Power system modeling and controls continue to become more complex with the advent of smart grid technologies and large-scale deployment of renewable energy resources. As demonstrated in recent studies, inaccurate system models could lead to large-scale blackouts, thereby motivating the need for model calibration. Current methods of model calibration rely on manual tuning based on engineering experience, are time consuming and could yield inaccurate parameter estimates. In this paper, the Extended Kalman Filter (EKF) is used as a tool to calibrate exciter and Power System Stabilizer (PSS) models of a particular type of machine in the Western Electricity Coordinating Council (WECC). The EKF-based parameter estimation is a recursive prediction-correction process which uses the mismatch between simulation and measurement to adjust the model parameters at every time step. Numerical simulations using actual field test data demonstrate the effectiveness of the proposed approach in calibrating the parameters.

  1. Offline estimation of decay time for an optical cavity with a low pass filter cavity model.

    Science.gov (United States)

    Kallapur, Abhijit G; Boyson, Toby K; Petersen, Ian R; Harb, Charles C

    2012-08-01

    This Letter presents offline estimation results for the decay-time constant for an experimental Fabry-Perot optical cavity for cavity ring-down spectroscopy (CRDS). The cavity dynamics are modeled in terms of a low pass filter (LPF) with unity DC gain. This model is used by an extended Kalman filter (EKF) along with the recorded light intensity at the output of the cavity in order to estimate the decay-time constant. The estimation results using the LPF cavity model are compared to those obtained using the quadrature model for the cavity presented in previous work by Kallapur et al. The estimation process derived using the LPF model comprises two states as opposed to three states in the quadrature model. When considering the EKF, this means propagating two states and a (2×2) covariance matrix using the LPF model, as opposed to propagating three states and a (3×3) covariance matrix using the quadrature model. This gives the former model a computational advantage over the latter and leads to faster execution times for the corresponding EKF. It is shown in this Letter that the LPF model for the cavity with two filter states is computationally more efficient, converges faster, and is hence a more suitable method than the three-state quadrature model presented in previous work for real-time estimation of the decay-time constant for the cavity.

  2. Real-time prediction and gating of respiratory motion in 3D space using extended Kalman filters and Gaussian process regression network

    Science.gov (United States)

    Bukhari, W.; Hong, S.-M.

    2016-03-01

    The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the radiation treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting respiratory motion in 3D space and realizing a gating function without pre-specifying a particular phase of the patient’s breathing cycle. The algorithm, named EKF-GPRN+ , first employs an extended Kalman filter (EKF) independently along each coordinate to predict the respiratory motion and then uses a Gaussian process regression network (GPRN) to correct the prediction error of the EKF in 3D space. The GPRN is a nonparametric Bayesian algorithm for modeling input-dependent correlations between the output variables in multi-output regression. Inference in GPRN is intractable and we employ variational inference with mean field approximation to compute an approximate predictive mean and predictive covariance matrix. The approximate predictive mean is used to correct the prediction error of the EKF. The trace of the approximate predictive covariance matrix is utilized to capture the uncertainty in EKF-GPRN+ prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification enables us to pause the treatment beam over such instances. EKF-GPRN+ implements a gating function by using simple calculations based on the trace of the predictive covariance matrix. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPRN+ . The experimental results show that the EKF-GPRN+ algorithm reduces the patient-wise prediction error to 38%, 40% and 40% in root-mean-square, compared to no prediction, at lookahead lengths of 192 ms, 384 ms and 576 ms, respectively. The EKF-GPRN+ algorithm can further reduce the prediction error by employing the gating function, albeit

  3. Real-time prediction and gating of respiratory motion in 3D space using extended Kalman filters and Gaussian process regression network

    International Nuclear Information System (INIS)

    Bukhari, W; Hong, S-M

    2016-01-01

    The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the radiation treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting respiratory motion in 3D space and realizing a gating function without pre-specifying a particular phase of the patient’s breathing cycle. The algorithm, named EKF-GPRN +  , first employs an extended Kalman filter (EKF) independently along each coordinate to predict the respiratory motion and then uses a Gaussian process regression network (GPRN) to correct the prediction error of the EKF in 3D space. The GPRN is a nonparametric Bayesian algorithm for modeling input-dependent correlations between the output variables in multi-output regression. Inference in GPRN is intractable and we employ variational inference with mean field approximation to compute an approximate predictive mean and predictive covariance matrix. The approximate predictive mean is used to correct the prediction error of the EKF. The trace of the approximate predictive covariance matrix is utilized to capture the uncertainty in EKF-GPRN + prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification enables us to pause the treatment beam over such instances. EKF-GPRN + implements a gating function by using simple calculations based on the trace of the predictive covariance matrix. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPRN +  . The experimental results show that the EKF-GPRN + algorithm reduces the patient-wise prediction error to 38%, 40% and 40% in root-mean-square, compared to no prediction, at lookahead lengths of 192 ms, 384 ms and 576 ms, respectively. The EKF-GPRN + algorithm can further reduce the prediction error by employing the gating function

  4. Single-resolution and multiresolution extended-Kalman-filter-based reconstruction approaches to optical refraction tomography.

    Science.gov (United States)

    Naik, Naren; Vasu, R M; Ananthasayanam, M R

    2010-02-20

    The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances.

  5. An Expectation-Maximization Method for Calibrating Synchronous Machine Models

    Energy Technology Data Exchange (ETDEWEB)

    Meng, Da; Zhou, Ning; Lu, Shuai; Lin, Guang

    2013-07-21

    The accuracy of a power system dynamic model is essential to its secure and efficient operation. Lower confidence in model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, this paper proposes an expectation-maximization (EM) method to calibrate the synchronous machine model using phasor measurement unit (PMU) data. First, an extended Kalman filter (EKF) is applied to estimate the dynamic states using measurement data. Then, the parameters are calculated based on the estimated states using maximum likelihood estimation (MLE) method. The EM method iterates over the preceding two steps to improve estimation accuracy. The proposed EM method’s performance is evaluated using a single-machine infinite bus system and compared with a method where both state and parameters are estimated using an EKF method. Sensitivity studies of the parameter calibration using EM method are also presented to show the robustness of the proposed method for different levels of measurement noise and initial parameter uncertainty.

  6. Integrated Sensing & Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier & Syngas Cooler. Topical Rerport for Phase III

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Aditya

    2011-02-17

    This Topical Report for the final Phase III of the program summarizes the results from the Task 3 of the program. In this task, the separately designed extended Kalman Filter (EKF) and model predictive controls (MPC) with ideal sensing, developed in Phase II, were integrated to achieve the overall sensing and control system for the gasification section of an IGCC plant. The EKF and MPC algorithms were updated and re-tuned to achieve closed-loop system stability as well as good steady-state and transient control response. In particular, the performance of the integrated EKF and MPC solution was tested extensively through multiple simulation studies to achieve improved steady-state as well as transient performance, with coal as well as coal-petcoke blended fuel, in the presence of unknown modeling errors as well as sensor errors (noise and bias). The simulation studies demonstrated significant improvements in steady state and transient operation performance, similar to that achieved by MPC with ideal sensors in Phase II of the program.

  7. Ridge Regression Signal Processing

    Science.gov (United States)

    Kuhl, Mark R.

    1990-01-01

    The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

  8. Approximate effect of parameter pseudonoise intensity on rate of convergence for EKF parameter estimators. [Extended Kalman Filter

    Science.gov (United States)

    Hill, Bryon K.; Walker, Bruce K.

    1991-01-01

    When using parameter estimation methods based on extended Kalman filter (EKF) theory, it is common practice to assume that the unknown parameter values behave like a random process, such as a random walk, in order to guarantee their identifiability by the filter. The present work is the result of an ongoing effort to quantitatively describe the effect that the assumption of a fictitious noise (called pseudonoise) driving the unknown parameter values has on the parameter estimate convergence rate in filter-based parameter estimators. The initial approach is to examine a first-order system described by one state variable with one parameter to be estimated. The intent is to derive analytical results for this simple system that might offer insight into the effect of the pseudonoise assumption for more complex systems. Such results would make it possible to predict the estimator error convergence behavior as a function of the assumed pseudonoise intensity, and this leads to the natural application of the results to the design of filter-based parameter estimators. The results obtained show that the analytical description of the convergence behavior is very difficult.

  9. Estimating particle number size distributions from multi-instrument observations with Kalman Filtering

    Energy Technology Data Exchange (ETDEWEB)

    Viskari, T.

    2012-07-01

    Atmospheric aerosol particles have several important effects on the environment and human society. The exact impact of aerosol particles is largely determined by their particle size distributions. However, no single instrument is able to measure the whole range of the particle size distribution. Estimating a particle size distribution from multiple simultaneous measurements remains a challenge in aerosol physical research. Current methods to combine different measurements require assumptions concerning the overlapping measurement ranges and have difficulties in accounting for measurement uncertainties. In this thesis, Extended Kalman Filter (EKF) is presented as a promising method to estimate particle number size distributions from multiple simultaneous measurements. The particle number size distribution estimated by EKF includes information from prior particle number size distributions as propagated by a dynamical model and is based on the reliabilities of the applied information sources. Known physical processes and dynamically evolving error covariances constrain the estimate both over time and particle size. The method was tested with measurements from Differential Mobility Particle Sizer (DMPS), Aerodynamic Particle Sizer (APS) and nephelometer. The particle number concentration was chosen as the state of interest. The initial EKF implementation presented here includes simplifications, yet the results are positive and the estimate successfully incorporated information from the chosen instruments. For particle sizes smaller than 4 micrometers, the estimate fits the available measurements and smooths the particle number size distribution over both time and particle diameter. The estimate has difficulties with particles larger than 4 micrometers due to issues with both measurements and the dynamical model in that particle size range. The EKF implementation appears to reduce the impact of measurement noise on the estimate, but has a delayed reaction to sudden

  10. Comparison of reactivity estimation performance between two extended Kalman filtering schemes

    International Nuclear Information System (INIS)

    Peng, Xingjie; Cai, Yun; Li, Qing; Wang, Kan

    2016-01-01

    Highlights: • The performances of two EKF schemes using different Jacobian matrices are compared. • Numerical simulations are used for the validation and comparison of these two EKF schemes. • The simulation results show that the EKF scheme adopted by this paper performs better than the one adopted by previous literatures. - Abstract: The extended Kalman filtering (EKF) technique has been utilized in the estimation of reactivity which is a significantly important parameter to indicate the status of the nuclear reactor. In this paper, the performances of two EKF schemes using different Jacobian matrices are compared. Numerical simulations are used for the validation and comparison of these two EKF schemes, and the results show that the Jacobian matrix obtained directly from the discrete-time state model performs better than the one which is the discretization form of the Jacobian matrix obtained from the continuous-time state model.

  11. Cross sectional efficient estimation of stochastic volatility short rate models

    NARCIS (Netherlands)

    Danilov, Dmitri; Mandal, Pranab K.

    2002-01-01

    We consider the problem of estimation of term structure of interest rates. Filtering theory approach is very natural here with the underlying setup being non-linear and non-Gaussian. Earlier works make use of Extended Kalman Filter (EKF). However, the EKF in this situation leads to inconsistent

  12. Performance Enhancement of Pharmacokinetic Diffuse Fluorescence Tomography by Use of Adaptive Extended Kalman Filtering.

    Science.gov (United States)

    Wang, Xin; Wu, Linhui; Yi, Xi; Zhang, Yanqi; Zhang, Limin; Zhao, Huijuan; Gao, Feng

    2015-01-01

    Due to both the physiological and morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic diffuse fluorescence tomography (DFT) can provide contrast-enhanced and comprehensive information for tumor diagnosis and staging. In this regime, the extended Kalman filtering (EKF) based method shows numerous advantages including accurate modeling, online estimation of multiparameters, and universal applicability to any optical fluorophore. Nevertheless the performance of the conventional EKF highly hinges on the exact and inaccessible prior knowledge about the initial values. To address the above issues, an adaptive-EKF scheme is proposed based on a two-compartmental model for the enhancement, which utilizes a variable forgetting-factor to compensate the inaccuracy of the initial states and emphasize the effect of the current data. It is demonstrated using two-dimensional simulative investigations on a circular domain that the proposed adaptive-EKF can obtain preferable estimation of the pharmacokinetic-rates to the conventional-EKF and the enhanced-EKF in terms of quantitativeness, noise robustness, and initialization independence. Further three-dimensional numerical experiments on a digital mouse model validate the efficacy of the method as applied in realistic biological systems.

  13. Implementing a new governance model.

    Science.gov (United States)

    Stanley-Clarke, Nicky; Sanders, Jackie; Munford, Robyn

    2016-05-16

    Purpose - The purpose of this paper is to discuss the lessons learnt from the process of implementing a new model of governance within Living Well, a New Zealand statutory mental health agency. Design/methodology/approach - It presents the findings from an organisational case study that involved qualitative interviews, meeting observations and document analysis. Archetype theory provided the analytical framework for the research enabling an analysis of both the formal structures and informal value systems that influenced the implementation of the governance model. Findings - The research found that the move to a new governance model did not proceed as planned. It highlighted the importance of staff commitment, the complexity of adopting a new philosophical approach and the undue influence of key personalities as key determining factors in the implementation process. The findings suggest that planners and managers within statutory mental health agencies need to consider the implications of any proposed governance change on existing roles and relationships, thinking strategically about how to secure professional commitment to change. Practical implications - There are ongoing pressures within statutory mental health agencies to improve the efficiency and effectiveness of organisational structures and systems. This paper has implications for how planners and managers think about the process of implementing new governance models within the statutory mental health environment in order to increase the likelihood of sustaining and embedding new approaches to service delivery. Originality/value - The paper presents insights into the process of implementing new governance models within a statutory mental health agency in New Zealand that has relevance for other jurisdictions.

  14. Cross sectional efficient estimation of stochastic volatility short rate models

    NARCIS (Netherlands)

    Danilov, Dmitri; Mandal, Pranab K.

    2001-01-01

    We consider the problem of estimation of term structure of interest rates. Filtering theory approach is very natural here with the underlying setup being non-linear and non-Gaussian. Earlier works make use of Extended Kalman Filter (EKF). However, as indicated by de Jong (2000), the EKF in this

  15. CSR Model Implementation from School Stakeholder Perspectives

    Science.gov (United States)

    Herrmann, Suzannah

    2006-01-01

    Despite comprehensive school reform (CSR) model developers' best intentions to make school stakeholders adhere strictly to the implementation of model components, school stakeholders implementing CSR models inevitably make adaptations to the CSR model. Adaptations are made to CSR models because school stakeholders internalize CSR model practices…

  16. Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake

    Science.gov (United States)

    Molenaar, Peter; Harsh, Saurabh; Freeman, Kenneth; Xie, Jinyu; Gold, Carol; Rovine, Mike; Ulbrecht, Jan

    2014-01-01

    An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control. PMID:24876585

  17. Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods

    Directory of Open Access Journals (Sweden)

    Renxin Xiao

    2016-03-01

    Full Text Available In order to properly manage lithium-ion batteries of electric vehicles (EVs, it is essential to build the battery model and estimate the state of charge (SOC. In this paper, the fractional order forms of Thevenin and partnership for a new generation of vehicles (PNGV models are built, of which the model parameters including the fractional orders and the corresponding resistance and capacitance values are simultaneously identified based on genetic algorithm (GA. The relationships between different model parameters and SOC are established and analyzed. The calculation precisions of the fractional order model (FOM and integral order model (IOM are validated and compared under hybrid test cycles. Finally, extended Kalman filter (EKF is employed to estimate the SOC based on different models. The results prove that the FOMs can simulate the output voltage more accurately and the fractional order EKF (FOEKF can estimate the SOC more precisely under dynamic conditions.

  18. Brain-inspired Stochastic Models and Implementations

    KAUST Repository

    Al-Shedivat, Maruan

    2015-05-12

    One of the approaches to building artificial intelligence (AI) is to decipher the princi- ples of the brain function and to employ similar mechanisms for solving cognitive tasks, such as visual perception or natural language understanding, using machines. The recent breakthrough, named deep learning, demonstrated that large multi-layer networks of arti- ficial neural-like computing units attain remarkable performance on some of these tasks. Nevertheless, such artificial networks remain to be very loosely inspired by the brain, which rich structures and mechanisms may further suggest new algorithms or even new paradigms of computation. In this thesis, we explore brain-inspired probabilistic mechanisms, such as neural and synaptic stochasticity, in the context of generative models. The two questions we ask here are: (i) what kind of models can describe a neural learning system built of stochastic components? and (ii) how can we implement such systems e ̆ciently? To give specific answers, we consider two well known models and the corresponding neural architectures: the Naive Bayes model implemented with a winner-take-all spiking neural network and the Boltzmann machine implemented in a spiking or non-spiking fashion. We propose and analyze an e ̆cient neuromorphic implementation of the stochastic neu- ral firing mechanism and study the e ̄ects of synaptic unreliability on learning generative energy-based models implemented with neural networks.

  19. Implementation of advanced inbound models

    OpenAIRE

    Koskinen, Juha

    2016-01-01

    The present Master’s Thesis was assigned by company operating in telecommuni-cations industry. The target of the Master’s Thesis was to understand what the biggest benefits are in implementing advanced inbound models into use and why it sometimes takes a longer time to finalize the implementation than planned. In addition the thesis aimed at clarifying how the usage of advanced inbound models should be measured and what the key performance indicators are that can verify the information. The g...

  20. Filtering in hybrid dynamic Bayesian networks

    DEFF Research Database (Denmark)

    Andersen, Morten Nonboe; Andersen, Rasmus Ørum; Wheeler, Kevin

    2004-01-01

    for inference. We extend the experiment and perform approximate inference using The Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Furthermore, we combine these techniques in a 'non-strict' Rao-Blackwellisation framework and apply it to the watertank system. We show that UKF and UKF in a PF...... framework outperform the generic PF, EKF and EKF in a PF framework with respect to accuracy and robustness in terms of estimation RMSE (root-mean-square error). Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. We also show...... that the choice of network structure is very important for the performance of the generic PF and the EKF algorithms, but not for the UKF algorithms. Furthermore, we investigate the influence of data noise in the watertank simulation. Theory and implementation is based on the theory presented in (v.d. Merwe et al...

  1. Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach.

    Science.gov (United States)

    Wang, Qian; Molenaar, Peter; Harsh, Saurabh; Freeman, Kenneth; Xie, Jinyu; Gold, Carol; Rovine, Mike; Ulbrecht, Jan

    2014-03-01

    An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control. © 2014 Diabetes Technology Society.

  2. Modeling of nonlinear biological phenomena modeled by S-systems.

    Science.gov (United States)

    Mansouri, Majdi M; Nounou, Hazem N; Nounou, Mohamed N; Datta, Aniruddha A

    2014-03-01

    A central challenge in computational modeling of biological systems is the determination of the model parameters. In such cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. For example, time-series dynamic genomic data can be used to develop models representing dynamic genetic regulatory networks, which can be used to design intervention strategies to cure major diseases and to better understand the behavior of biological systems. Unfortunately, biological measurements are usually highly infected by errors that hide the important characteristics in the data. Therefore, these noisy measurements need to be filtered to enhance their usefulness in practice. This paper addresses the problem of state and parameter estimation of biological phenomena modeled by S-systems using Bayesian approaches, where the nonlinear observed system is assumed to progress according to a probabilistic state space model. The performances of various conventional and state-of-the-art state estimation techniques are compared. These techniques include the extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and the developed variational Bayesian filter (VBF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the enzyme CadA, the model cadBA, the cadaverine Cadav and the lysine Lys for a model of the Cad System in Escherichia coli (CSEC)) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of the number of estimated model parameters on the accuracy and convergence of these

  3. Data assimilation with an extended Kalman filter for impact-produced shock-wave dynamics

    International Nuclear Information System (INIS)

    Kao, Jim; Flicker, Dawn; Henninger, Rudy; Frey, Sarah; Ghil, Michael; Ide, Kayo

    2004-01-01

    Model assimilation of data strives to determine optimally the state of an evolving physical system from a limited number of observations. The present study represents the first attempt of applying the extended Kalman filter (EKF) method of data assimilation to shock-wave dynamics induced by a high-speed impact. EKF solves the full nonlinear state evolution and estimates its associated error-covariance matrix in time. The state variables obtained by the blending of past model evolution with currently available data, along with their associated minimized errors (or uncertainties), are then used as initial conditions for further prediction until the next time at which data becomes available. In this study, a one-dimensional (1D) finite-difference code is used along with data measured from a 1D flyer plate experiment. An ensemble simulation suggests that the nonlinearity of the modeled system can be reasonably tracked by EKF. The results demonstrate that the EKF assimilation of a limited amount of pressure data, measured at the middle of the target plate alone, helps track the evolution of all the state variables. The fidelity of EKF is further investigated with numerically generated synthetic data from so-called 'identical-twin experiments', in which the true state is known and various measurement techniques and strategies can be made easily simulated. We find that the EKF method can effectively assimilate the density fields, which are distributed sparsely in time to mimic radiographic data, into the modeled system

  4. Neural Model with Particle Swarm Optimization Kalman Learning for Forecasting in Smart Grids

    Directory of Open Access Journals (Sweden)

    Alma Y. Alanis

    2013-01-01

    Full Text Available This paper discusses a novel training algorithm for a neural network architecture applied to time series prediction with smart grids applications. The proposed training algorithm is based on an extended Kalman filter (EKF improved using particle swarm optimization (PSO to compute the design parameters. The EKF-PSO-based algorithm is employed to update the synaptic weights of the neural network. The size of the regression vector is determined by means of the Cao methodology. The proposed structure captures more efficiently the complex nature of the wind speed, energy generation, and electrical load demand time series that are constantly monitorated in a smart grid benchmark. The proposed model is trained and tested using real data values in order to show the applicability of the proposed scheme.

  5. Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model

    Science.gov (United States)

    Gustafson, David H; Hawkins, Robert P; Brennan, Patricia F; Dinauer, Susan; Johnson, Pauley R; Siegler, Tracy

    2010-01-01

    Objective To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements. Design Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases. Measurements Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes. Results Two of the seven factors, ‘organizational motivation’ and ‘meeting user needs,’ were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome. Limitations The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study. Conclusion The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term. PMID:20962135

  6. A cognition-based method to ease the computational load for an extended Kalman filter.

    Science.gov (United States)

    Li, Yanpeng; Li, Xiang; Deng, Bin; Wang, Hongqiang; Qin, Yuliang

    2014-12-03

    The extended Kalman filter (EKF) is the nonlinear model of a Kalman filter (KF). It is a useful parameter estimation method when the observation model and/or the state transition model is not a linear function. However, the computational requirements in EKF are a difficulty for the system. With the help of cognition-based designation and the Taylor expansion method, a novel algorithm is proposed to ease the computational load for EKF in azimuth predicting and localizing under a nonlinear observation model. When there are nonlinear functions and inverse calculations for matrices, this method makes use of the major components (according to current performance and the performance requirements) in the Taylor expansion. As a result, the computational load is greatly lowered and the performance is ensured. Simulation results show that the proposed measure will deliver filtering output with a similar precision compared to the regular EKF. At the same time, the computational load is substantially lowered.

  7. The extended Kalman filter for forecast of algal bloom dynamics.

    Science.gov (United States)

    Mao, J Q; Lee, Joseph H W; Choi, K W

    2009-09-01

    A deterministic ecosystem model is combined with an extended Kalman filter (EKF) to produce short term forecasts of algal bloom and dissolved oxygen dynamics in a marine fish culture zone (FCZ). The weakly flushed FCZ is modelled as a well-mixed system; the tidal exchange with the outer bay is lumped into a flushing rate that is numerically determined from a three-dimensional hydrodynamic model. The ecosystem model incorporates phytoplankton growth kinetics, nutrient uptake, photosynthetic production, nutrient sources from organic fish farm loads, and nutrient exchange with a sediment bed layer. High frequency field observations of chlorophyll, dissolved oxygen (DO) and hydro-meteorological parameters (sampling interval Deltat=1 day, 2h, 1h, respectively) and bi-weekly nutrient data are assimilated into the model to produce the combined state estimate accounting for the uncertainties. In addition to the water quality state variables, the EKF incorporates dynamic estimation of algal growth rate and settling velocity. The effectiveness of the EKF data assimilation is studied for a wide range of sampling intervals and prediction lead-times. The chlorophyll and dissolved oxygen estimated by the EKF are compared with field data of seven algal bloom events observed at Lamma Island, Hong Kong. The results show that the EKF estimate well captures the nonlinear error evolution in time; the chlorophyll level can be satisfactorily predicted by the filtered model estimate with a mean absolute error of around 1-2 microg/L. Predictions with 1-2 day lead-time are highly correlated with the observations (r=0.7-0.9); the correlation stays at a high level for a lead-time of 3 days (r=0.6-0.7). Estimated algal growth and settling rates are in accord with field observations; the more frequent DO data can compensate for less frequent algal biomass measurements. The present study is the first time the EKF is successfully applied to forecast an entire algal bloom cycle, suggesting the

  8. Embedded systems development from functional models to implementations

    CERN Document Server

    Zeng, Haibo; Natale, Marco; Marwedel, Peter

    2014-01-01

    This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems.  The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results.     Describes integration of heterogeneous models; Discusses synthesis of task model implementations and code implementations; Compares model-based design vs. model-driven approaches; Explains how to enforce correctness by construction in the functional and time domains; Includes optimization techniques for control performance.

  9. Real-time prediction of respiratory motion using a cascade structure of an extended Kalman filter and support vector regression.

    Science.gov (United States)

    Hong, S-M; Bukhari, W

    2014-07-07

    The motion of thoracic and abdominal tumours induced by respiratory motion often exceeds 20 mm, and can significantly compromise dose conformality. Motion-adaptive radiotherapy aims to deliver a conformal dose distribution to the tumour with minimal normal tissue exposure by compensating for the tumour motion. This adaptive radiotherapy, however, requires the prediction of the tumour movement that can occur over the system latency period. In general, motion prediction approaches can be classified into two groups: model-based and model-free. Model-based approaches utilize a motion model in predicting respiratory motion. These approaches are computationally efficient and responsive to irregular changes in respiratory motion. Model-free approaches do not assume an explicit model of motion dynamics, and predict future positions by learning from previous observations. Artificial neural networks (ANNs) and support vector regression (SVR) are examples of model-free approaches. In this article, we present a prediction algorithm that combines a model-based and a model-free approach in a cascade structure. The algorithm, which we call EKF-SVR, first employs a model-based algorithm (named LCM-EKF) to predict the respiratory motion, and then uses a model-free SVR algorithm to estimate and correct the error of the LCM-EKF prediction. Extensive numerical experiments based on a large database of 304 respiratory motion traces are performed. The experimental results demonstrate that the EKF-SVR algorithm successfully reduces the prediction error of the LCM-EKF, and outperforms the model-free ANN and SVR algorithms in terms of prediction accuracy across lookahead lengths of 192, 384, and 576 ms.

  10. Estimation of State of Charge of Lithium-Ion Batteries Used in HEV Using Robust Extended Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Suleiman M. Sharkh

    2012-04-01

    Full Text Available A robust extended Kalman filter (EKF is proposed as a method for estimation of the state of charge (SOC of lithium-ion batteries used in hybrid electric vehicles (HEVs. An equivalent circuit model of the battery, including its electromotive force (EMF hysteresis characteristics and polarization characteristics is used. The effect of the robust EKF gain coefficient on SOC estimation is analyzed, and an optimized gain coefficient is determined to restrain battery terminal voltage from fluctuating. Experimental and simulation results are presented. SOC estimates using the standard EKF are compared with the proposed robust EKF algorithm to demonstrate the accuracy and precision of the latter for SOC estimation.

  11. Towards a CPN-Based Modelling Approach for Reconciling Verification and Implementation of Protocol Models

    DEFF Research Database (Denmark)

    Simonsen, Kent Inge; Kristensen, Lars Michael

    2013-01-01

    Formal modelling of protocols is often aimed at one specific purpose such as verification or automatically generating an implementation. This leads to models that are useful for one purpose, but not for others. Being able to derive models for verification and implementation from a single model...... is beneficial both in terms of reduced total modelling effort and confidence that the verification results are valid also for the implementation model. In this paper we introduce the concept of a descriptive specification model and an approach based on refining a descriptive model to target both verification...... how this model can be refined to target both verification and implementation....

  12. Estimation of aerosol particle number distribution with Kalman Filtering – Part 2: Simultaneous use of DMPS, APS and nephelometer measurements

    Directory of Open Access Journals (Sweden)

    T. Viskari

    2012-12-01

    Full Text Available Extended Kalman Filter (EKF is used to estimate particle size distributions from observations. The focus here is on the practical application of EKF to simultaneously merge information from different types of experimental instruments. Every 10 min, the prior state estimate is updated with size-segregating measurements from Differential Mobility Particle Sizer (DMPS and Aerodynamic Particle Sizer (APS as well as integrating measurements from a nephelometer. Error covariances are approximate in our EKF implementation. The observation operator assumes a constant particle density and refractive index. The state estimates are compared to particle size distributions that are a composite of DMPS and APS measurements. The impact of each instrument on the size distribution estimate is studied. Kalman Filtering of DMPS and APS yielded a temporally consistent state estimate. This state estimate is continuous over the overlapping size range of DMPS and APS. Inclusion of the integrating measurements further reduces the effect of measurement noise. Even with the present approximations, EKF is shown to be a very promising method to estimate particle size distribution with observations from different types of instruments.

  13. Simple implementation of general dark energy models

    International Nuclear Information System (INIS)

    Bloomfield, Jolyon K.; Pearson, Jonathan A.

    2014-01-01

    We present a formalism for the numerical implementation of general theories of dark energy, combining the computational simplicity of the equation of state for perturbations approach with the generality of the effective field theory approach. An effective fluid description is employed, based on a general action describing single-scalar field models. The formalism is developed from first principles, and constructed keeping the goal of a simple implementation into CAMB in mind. Benefits of this approach include its straightforward implementation, the generality of the underlying theory, the fact that the evolved variables are physical quantities, and that model-independent phenomenological descriptions may be straightforwardly investigated. We hope this formulation will provide a powerful tool for the comparison of theoretical models of dark energy with observational data

  14. Square Root Unscented Kalman Filters for State Estimation of Induction Motor Drives

    DEFF Research Database (Denmark)

    Lascu, Cristian; Jafarzadeh, Saeed; Fadali, M.Sami

    2013-01-01

    This paper investigates the application, design, and implementation of the square root unscented Kalman filter (UKF) (SRUKF) for induction motor (IM) sensorless drives. The UKF uses nonlinear unscented transforms (UTs) in the prediction step in order to preserve the stochastic characteristics...... of a nonlinear system. The advantage of using the UT is its ability to capture the nonlinear behavior of the system, unlike the extended Kalman filter (EKF) that uses linearized models. The SRUKF implements the UKF using square root filtering to reduce computational errors. We discuss the theoretical aspects...

  15. Developing an active implementation model for a chronic disease management program.

    Science.gov (United States)

    Smidth, Margrethe; Christensen, Morten Bondo; Olesen, Frede; Vedsted, Peter

    2013-04-01

    Introduction and diffusion of new disease management programs in healthcare is usually slow, but active theory-driven implementation seems to outperform other implementation strategies. However, we have only scarce evidence on the feasibility and real effect of such strategies in complex primary care settings where municipalities, general practitioners and hospitals should work together. The Central Denmark Region recently implemented a disease management program for chronic obstructive pulmonary disease (COPD) which presented an opportunity to test an active implementation model against the usual implementation model. The aim of the present paper is to describe the development of an active implementation model using the Medical Research Council's model for complex interventions and the Chronic Care Model. We used the Medical Research Council's five-stage model for developing complex interventions to design an implementation model for a disease management program for COPD. First, literature on implementing change in general practice was scrutinised and empirical knowledge was assessed for suitability. In phase I, the intervention was developed; and in phases II and III, it was tested in a block- and cluster-randomised study. In phase IV, we evaluated the feasibility for others to use our active implementation model. The Chronic Care Model was identified as a model for designing efficient implementation elements. These elements were combined into a multifaceted intervention, and a timeline for the trial in a randomised study was decided upon in accordance with the five stages in the Medical Research Council's model; this was captured in a PaTPlot, which allowed us to focus on the structure and the timing of the intervention. The implementation strategies identified as efficient were use of the Breakthrough Series, academic detailing, provision of patient material and meetings between providers. The active implementation model was tested in a randomised trial

  16. An Adaptive Particle Weighting Strategy for ECG Denoising Using Marginalized Particle Extended Kalman Filter: An Evaluation in Arrhythmia Contexts.

    Science.gov (United States)

    Hesar, Hamed Danandeh; Mohebbi, Maryam

    2017-11-01

    Model-based Bayesian frameworks have a common problem in processing electrocardiogram (ECG) signals with sudden morphological changes. This situation often happens in the case of arrhythmias where ECGs do not obey the predefined state models. To solve this problem, in this paper, a model-based Bayesian denoising framework is proposed using marginalized particle-extended Kalman filter (MP-EKF), variational mode decomposition, and a novel fuzzy-based adaptive particle weighting strategy. This strategy helps MP-EKF to perform well even when the morphology of signal does not comply with the predefined dynamic model. In addition, this strategy adapts MP-EKF's behavior to the acquired measurements in different input signal to noise ratios (SNRs). At low input SNRs, this strategy decreases the particles' trust level to the measurements while increasing their trust level to a synthetic ECG constructed with the feature parameters of ECG dynamic model. At high input SNRs, the particles' trust level to the measurements is increased and the trust level to synthetic ECG is decreased. The proposed method was evaluated on MIT-BIH normal sinus rhythm database and compared with EKF/EKS frameworks and previously proposed MP-EKF. It was also evaluated on ECG segments extracted from MIT-BIH arrhythmia database, which contained ventricular and atrial arrhythmia. The results showed that the proposed algorithm had a noticeable superiority over benchmark methods from both SNR improvement and multiscale entropy based weighted distortion (MSEWPRD) viewpoints at low input SNRs.

  17. ECG denoising and fiducial point extraction using an extended Kalman filtering framework with linear and nonlinear phase observations.

    Science.gov (United States)

    Akhbari, Mahsa; Shamsollahi, Mohammad B; Jutten, Christian; Armoundas, Antonis A; Sayadi, Omid

    2016-02-01

    In this paper we propose an efficient method for denoising and extracting fiducial point (FP) of ECG signals. The method is based on a nonlinear dynamic model which uses Gaussian functions to model ECG waveforms. For estimating the model parameters, we use an extended Kalman filter (EKF). In this framework called EKF25, all the parameters of Gaussian functions as well as the ECG waveforms (P-wave, QRS complex and T-wave) in the ECG dynamical model, are considered as state variables. In this paper, the dynamic time warping method is used to estimate the nonlinear ECG phase observation. We compare this new approach with linear phase observation models. Using linear and nonlinear EKF25 for ECG denoising and nonlinear EKF25 for fiducial point extraction and ECG interval analysis are the main contributions of this paper. Performance comparison with other EKF-based techniques shows that the proposed method results in higher output SNR with an average SNR improvement of 12 dB for an input SNR of -8 dB. To evaluate the FP extraction performance, we compare the proposed method with a method based on partially collapsed Gibbs sampler and an established EKF-based method. The mean absolute error and the root mean square error of all FPs, across all databases are 14 ms and 22 ms, respectively, for our proposed method, with an advantage when using a nonlinear phase observation. These errors are significantly smaller than errors obtained with other methods. For ECG interval analysis, with an absolute mean error and a root mean square error of about 22 ms and 29 ms, the proposed method achieves better accuracy and smaller variability with respect to other methods.

  18. The Business Excellence Model for CSR Implementation?

    Directory of Open Access Journals (Sweden)

    Neergaard Peter

    2014-11-01

    Full Text Available Most of the Fortune 500 companies address Corporate Social Responsibility (CSR on their websites. However, CSR remains a fluffy concept difficult to implement in organization. The European Business Excellence Model has since the introduction in 1992 served as a powerful tool for integrating quality in organizations. CSR was first introduced in the model in 2002. From 2004 the European Foundation for Quality Management (EFQM has been eager to promote the model as an effective tool for implementing CSR.. The article discusses the potentials of the model for this end and illustrates how a 2006 European Award winning company has used the model to integrate CSR. The company adapted the Business Excellence model to improve performance, stimulate innovation and consensus.

  19. Implementation strategies for collaborative primary care-mental health models.

    Science.gov (United States)

    Franx, Gerdien; Dixon, Lisa; Wensing, Michel; Pincus, Harold

    2013-09-01

    Extensive research exists that collaborative primary care-mental health models can improve care and outcomes for patients. These programs are currently being implemented throughout the United States and beyond. The purpose of this study is to review the literature and to generate an overview of strategies currently used to implement such models in daily practice. Six overlapping strategies to implement collaborative primary care-mental health models were described in 18 selected studies. We identified interactive educational strategies, quality improvement change processes, technological support tools, stakeholder engagement in the design and execution of implementation plans, organizational changes in terms of expanding the task of nurses and financial strategies such as additional collaboration fees and pay for performance incentives. Considering the overwhelming evidence about the effectiveness of primary care-mental health models, there is a lack of good studies focusing on their implementation strategies. In practice, these strategies are multifaceted and locally defined, as a result of intensive and required stakeholder engagement. Although many barriers still exist, the implementation of collaborative models could have a chance to succeed in the United States, where new service delivery and payment models, such as the Patient-Centered Medical Home, the Health Home and the Accountable Care Organization, are being promoted.

  20. Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler

    Energy Technology Data Exchange (ETDEWEB)

    Aditya Kumar

    2010-12-30

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC

  1. Analysis and comparison of extended and unscented Kalman filtering methods for spacecraft attitude determination

    OpenAIRE

    Diaz, Orlando X.

    2010-01-01

    Approved for public release; distribution is unlimited Two methods of estimating the attitude position of a spacecraft are examined in this thesis: the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). In particular, the UnScented QUaternion Estimator (USQUE) derived from [4] is implemented into a spacecraft model. For generalizations about the each of the filters, a simple problem is initially solved. These solutions display typical characteristics of each filter type. T...

  2. Extended Kalman filtering for the detection of damage in linear mechanical structures

    Science.gov (United States)

    Liu, X.; Escamilla-Ambrosio, P. J.; Lieven, N. A. J.

    2009-09-01

    This paper addresses the problem of assessing the location and extent of damage in a vibrating structure by means of vibration measurements. Frequency domain identification methods (e.g. finite element model updating) have been widely used in this area while time domain methods such as the extended Kalman filter (EKF) method, are more sparsely represented. The difficulty of applying EKF in mechanical system damage identification and localisation lies in: the high computational cost, the dependence of estimation results on the initial estimation error covariance matrix P(0), the initial value of parameters to be estimated, and on the statistics of measurement noise R and process noise Q. To resolve these problems in the EKF, a multiple model adaptive estimator consisting of a bank of EKF in modal domain was designed, each filter in the bank is based on different P(0). The algorithm was iterated by using the weighted global iteration method. A fuzzy logic model was incorporated in each filter to estimate the variance of the measurement noise R. The application of the method is illustrated by simulated and real examples.

  3. Application of Unscented Kalman Filter in Satellite Orbit Simulation

    Institute of Scientific and Technical Information of China (English)

    ZHAO Dongming; CAI Zhiwu

    2006-01-01

    A new estimate method is proposed, which takes advantage of the unscented transform method, thus the true mean and covariance are approximated more accurately. The new method can be applied to non-linear systems without the linearization process necessary for the EKF, and it does not demand a Gaussian distribution of noise and what's more, its ease of implementation and more accurate estimation features enables it to demonstrate its good performance in the experiment of satellite orbit simulation. Numerical experiments show that the application of the unscented Kalman filter is more effective than the EKF.

  4. A quantum-implementable neural network model

    Science.gov (United States)

    Chen, Jialin; Wang, Lingli; Charbon, Edoardo

    2017-10-01

    A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.

  5. A New State of Charge Estimation Method for LiFePO4 Battery Packs Used in Robots

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-04-15

    The accurate state of charge (SOC) estimation of the LiFePO4 battery packs used in robot applications is required for better battery life cycle, performance, reliability, and economic issues. In this paper, a new SOC estimation method, ''Modified ECE + EKF'', is proposed. The method is the combination of the modified Equivalent Coulombic Efficiency (ECE) method and the Extended Kalman Filter (EKF) method. It is based on the zero-state hysteresis battery model, and adopts the EKF method to correct the initial value used in the Ah counting method. Experimental results show that the proposed technique is superior to the traditional techniques, such as ECE + EKF and ECE + Unscented Kalman Filter (UKF), and the accuracy of estimation is within 1%.

  6. Implementing a trustworthy cost-accounting model.

    Science.gov (United States)

    Spence, Jay; Seargeant, Dan

    2015-03-01

    Hospitals and health systems can develop an effective cost-accounting model and maximize the effectiveness of their cost-accounting teams by focusing on six key areas: Implementing an enhanced data model. Reconciling data efficiently. Accommodating multiple cost-modeling techniques. Improving transparency of cost allocations. Securing department manager participation. Providing essential education and training to staff members and stakeholders.

  7. Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Ines Baccouche

    2017-05-01

    Full Text Available Accurate modeling of the nonlinear relationship between the open circuit voltage (OCV and the state of charge (SOC is required for adaptive SOC estimation during the lithium-ion (Li-ion battery operation. Online SOC estimation should meet several constraints, such as the computational cost, the number of parameters, as well as the accuracy of the model. In this paper, these challenges are considered by proposing an improved simplified and accurate OCV model of a nickel manganese cobalt (NMC Li-ion battery, based on an empirical analytical characterization approach. In fact, composed of double exponential and simple quadratic functions containing only five parameters, the proposed model accurately follows the experimental curve with a minor fitting error of 1 mV. The model is also valid at a wide temperature range and takes into account the voltage hysteresis of the OCV. Using this model in SOC estimation by the extended Kalman filter (EKF contributes to minimizing the execution time and to reducing the SOC estimation error to only 3% compared to other existing models where the estimation error is about 5%. Experiments are also performed to prove that the proposed OCV model incorporated in the EKF estimator exhibits good reliability and precision under various loading profiles and temperatures.

  8. An improved PNGV modeling and SOC estimation for lithium iron phosphate batteries

    Science.gov (United States)

    Li, Peng

    2017-11-01

    Because lithium iron phosphate battery has many advantages, it has been used more and more widely in the field of electric vehicle. The lithium iron phosphate battery, presents the improved PNGV model, and the batteries charge discharge characteristics and pulse charge discharge experiments, identification of parameters of the battery model by interpolation and least square fitting method, to achieve a more accurate modeling of lithium iron phosphate battery, and the extended Calman filter algorithm (EKF) is completed state nuclear power battery (SOC) estimate.

  9. Participative management and shared leadership: implementing a model.

    Science.gov (United States)

    Noonan, D

    1995-01-01

    The author identifies the development, implementation and outcomes of a task subgroup model of management that provides a mechanism for shared leadership, planning, decision making, implementation and evaluation by staff, patients and families on a program level. The conceptual model and its operationalization are outlined within the context of the rehabilitation program at the Providence Centre in Scarborough, Ontario.

  10. Leader-Follower Tracking System for Agricultural Vehicles: Fusion of Laser and Odometry Positioning Using Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Zhang Lin Huan

    2015-03-01

    Full Text Available The aim of this research was to develop a safe human-driven and autonomous leader-follower tracking system for an autonomous tractor. To enable the tracking system, a laser range finder (LRF-based landmark detection system was designed to observe the relative position between a leader and a follower used in agricultural operations. The virtual follower-based formation-tracking algorithm was developed to minimize tracking errors and ensure safety. An extended Kalman filter (EKF was implemented for fusing LRF and odometry position to ensure stability of tracking in noisy farmland conditions. Simulations were conducted for tracking the leader in small and large sinusoidal curved paths. Simulated results verified high accuracy of formation tracking, stable velocity, and regulated steering angle of the follower. The tracking method confirmed the follower could follow the leader with a required formation safely and steadily in noisy conditions. The EKF helped to improve observation accuracy, velocity, and steering angle stability of the follower. As a result of the improved accuracy of observation and motion action, the tracking performance for lateral, longitudinal, and heading were also improved after the EKF was implemented in the tracking system.

  11. 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...

  12. A Quantised State Systems Approach for Jacobian Free Extended Kalman Filtering

    DEFF Research Database (Denmark)

    Alminde, Lars; Bendtsen, Jan Dimon; Stoustrup, Jakob

    2007-01-01

    Model based methods for control of intelligent autonomous systems rely on a state estimate being available. One of the most common methods to obtain a state estimate for non-linear systems is the Extended Kalman Filter (EKF) algorithm. In order to apply the EKF an expression must be available...

  13. Lyapunov vectors and assimilation in the unstable subspace: theory and applications

    International Nuclear Information System (INIS)

    Palatella, Luigi; Carrassi, Alberto; Trevisan, Anna

    2013-01-01

    Based on a limited number of noisy observations, estimation algorithms provide a complete description of the state of a system at current time. Estimation algorithms that go under the name of assimilation in the unstable subspace (AUS) exploit the nonlinear stability properties of the forecasting model in their formulation. Errors that grow due to sensitivity to initial conditions are efficiently removed by confining the analysis solution in the unstable and neutral subspace of the system, the subspace spanned by Lyapunov vectors with positive and zero exponents, while the observational noise does not disturb the system along the stable directions. The formulation of the AUS approach in the context of four-dimensional variational assimilation (4DVar-AUS) and the extended Kalman filter (EKF-AUS) and its application to chaotic models is reviewed. In both instances, the AUS algorithms are at least as efficient but simpler to implement and computationally less demanding than their original counterparts. As predicted by the theory when error dynamics is linear, the optimal subspace dimension for 4DVar-AUS is given by the number of positive and null Lyapunov exponents, while the EKF-AUS algorithm, using the same unstable and neutral subspace, recovers the solution of the full EKF algorithm, but dealing with error covariance matrices of a much smaller dimension and significantly reducing the computational burden. Examples of the application to a simplified model of the atmospheric circulation and to the optimal velocity model for traffic dynamics are given. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (paper)

  14. Streamflow data assimilation in SWAT model using Extended Kalman Filter

    Science.gov (United States)

    Sun, Leqiang; Nistor, Ioan; Seidou, Ousmane

    2015-12-01

    The Extended Kalman Filter (EKF) is coupled with the Soil and Water Assessment Tools (SWAT) model in the streamflow assimilation of the upstream Senegal River in West Africa. Given the large number of distributed variables in SWAT, only the average watershed scale variables are included in the state vector and the Hydrological Response Unit (HRU) scale variables are updated with the a posteriori/a priori ratio of their watershed scale counterparts. The Jacobian matrix is calculated numerically by perturbing the state variables. Both the soil moisture and CN2 are significantly updated in the wet season, yet they have opposite update patterns. A case study for a large flood forecast shows that for up to seven days, the streamflow forecast is moderately improved using the EKF-subsequent open loop scheme but significantly improved with a newly designed quasi-error update scheme. The former has better performances in the flood rising period while the latter has better performances in the recession period. For both schemes, the streamflow forecast is improved more significantly when the lead time is shorter.

  15. A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy

    International Nuclear Information System (INIS)

    Wang, Yujie; Zhang, Chenbin; Chen, Zonghai

    2015-01-01

    Highlights: • Build a multi-model switching SOC estimate method for Li-ion batteries. • Build an improved interpretative structural modeling method for model switching. • The feedback strategy of bus delay is applied to improve the real-time performance. • The EKF method is used for SOC estimation to improve the estimated accuracy. - Abstract: The accurate state-of-charge (SOC) estimation and real-time performance are critical evaluation indexes for Li-ion battery management systems (BMS). High accuracy algorithms often take long program execution time (PET) in the resource-constrained embedded application systems, which will undoubtedly lead to the decrease of the time slots of other processes, thereby reduce the overall performance of BMS. Considering the resource optimization and the computational load balance, this paper proposes a multi-model switching SOC estimation method for Li-ion batteries. Four typical battery models are employed to build a close-loop SOC estimation system. The extended Kalman filter (EKF) method is employed to eliminate the effect of the current noise and improve the accuracy of SOC. The experiments under dynamic current conditions are conducted to verify the accuracy and real-time performance of the proposed method. The experimental results indicate that accurate estimation results and reasonable PET can be obtained by the proposed method

  16. Expectations and implementations of the flipped classroom model in undergraduate mathematics courses

    Science.gov (United States)

    Naccarato, Emilie; Karakok, Gulden

    2015-10-01

    The flipped classroom model is being used more frequently in undergraduate mathematics courses. As with any new teaching model, in-depth investigations of both various implementation styles and how the new model improves student learning are needed. Currently, many practitioners have been sharing their implementations of this model. However, there has not yet been an investigation of the various implementations of the model to discern general trends in this movement. With this research goal in mind, we conducted a study exploring various implementations of the flipped classroom model by interviewing 19 faculty members who experienced using this model at 14 different institutes. Results indicate that participants had similar motivations for implementation; however, subsequent implementations were different. In addition, we share participants' perspectives on (a) student learning of pre-requisite, procedural and conceptual knowledge, and (b) how this particular model promotes such knowledge developments. Finally, we provide suggestions for future implementations and research regarding this particular teaching model.

  17. Adaptive streaming applications : analysis and implementation models

    NARCIS (Netherlands)

    Zhai, Jiali Teddy

    2015-01-01

    This thesis presents a highly automated design framework, called DaedalusRT, and several novel techniques. As the foundation of the DaedalusRT design framework, two types of dataflow Models-of-Computation (MoC) are used, one as timing analysis model and another one as the implementation model. The

  18. Detection of broken rotor bars in induction motors using nonlinear Kalman filters.

    Science.gov (United States)

    Karami, Farzaneh; Poshtan, Javad; Poshtan, Majid

    2010-04-01

    This paper presents a model-based fault detection approach for induction motors. A new filtering technique using Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) is utilized as a state estimation tool for on-line detection of broken bars in induction motors based on rotor parameter value estimation from stator current and voltage processing. The hypothesis on which the detection is based is that the failure events are detected by jumps in the estimated parameter values of the model. Both UKF and EKF are used to estimate the value of rotor resistance. Upon breaking a bar the estimated rotor resistance is increased instantly, thus providing two values of resistance after and before bar breakage. In order to compare the estimation performance of the EKF and UKF, both observers are designed for the same motor model and run with the same covariance matrices under the same conditions. Computer simulations are carried out for a squirrel cage induction motor. The results show the superiority of UKF over EKF in nonlinear system (such as induction motors) as it provides better estimates for rotor fault detection. Copyright 2010. Published by Elsevier Ltd.

  19. Continuous correction of differential path length factor in near-infrared spectroscopy.

    Science.gov (United States)

    Talukdar, Tanveer; Moore, Jason H; Diamond, Solomon G

    2013-05-01

    In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively correct for artificially introduced errors in DPF and to reduce the cross-talk error in simulation. With experimental CW-NIRS data, the hemodynamic estimates from EKF differ significantly from the WLSQ (p EKF method compared to WLSQ in three physiologically relevant spectral bands 0.04 to 0.15 Hz, 0.15 to 0.4 Hz and 0.4 to 2.0 Hz (p EKF method.

  20. A Generalized Framework for Modeling Next Generation 911 Implementations.

    Energy Technology Data Exchange (ETDEWEB)

    Kelic, Andjelka; Aamir, Munaf Syed; Kelic, Andjelka; Jrad, Ahmad M.; Mitchell, Roger

    2018-02-01

    This document summarizes the current state of Sandia 911 modeling capabilities and then addresses key aspects of Next Generation 911 (NG911) architectures for expansion of existing models. Analysis of three NG911 implementations was used to inform heuristics , associated key data requirements , and assumptions needed to capture NG911 architectures in the existing models . Modeling of NG911 necessitates careful consideration of its complexity and the diversity of implementations. Draft heuristics for constructing NG911 models are pres ented based on the analysis along with a summary of current challenges and ways to improve future NG911 modeling efforts . We found that NG911 relies on E nhanced 911 (E911) assets such as 911 selective routers to route calls originating from traditional tel ephony service which are a majority of 911 calls . We also found that the diversity and transitional nature of NG911 implementations necessitates significant and frequent data collection to ensure that adequate model s are available for crisis action support .

  1. Using Annotated Conceptual Models to Derive Information System Implementations

    Directory of Open Access Journals (Sweden)

    Anthony Berglas

    1994-05-01

    Full Text Available Producing production quality information systems from conceptual descriptions is a time consuming process that employs many of the world's programmers. Although most of this programming is fairly routine, the process has not been amenable to simple automation because conceptual models do not provide sufficient parameters to make all the implementation decisions that are required, and numerous special cases arise in practice. Most commercial CASE tools address these problems by essentially implementing a waterfall model in which the development proceeds from analysis through design, layout and coding phases in a partially automated manner, but the analyst/programmer must heavily edit each intermediate stage. This paper demonstrates that by recognising the nature of information systems, it is possible to specify applications completely using a conceptual model that has een annotated with additional parameters that guide automated implementation. More importantly, it will be argued that a manageable number of annotations are sufficient to implement realistic applications, and techniques will be described that enabled the author's commercial CASE tool, the Intelligent Develope to automated implementation without requiring complex theorem proving technology.

  2. Estimation of soil hydraulic information through the assimilation of values of the surface moisture: extended approximations (unscented)

    International Nuclear Information System (INIS)

    Medina, Hanoi; Hernández, Yunay; Batista, Giovanni Chirico; Romano, Nunzio

    2008-01-01

    Effective estimation of soil hydraulic information through the assimilation of surface moisture values, demand the use of approximations necessarily related to highly nonlinear models. The Kalman Filter 'Unscented' ( UKF ) has emerged in the literature as a safe and easy technique to implement than the most rudimentary, but more widely used, Kalman Filter 'Linear' (EKF ), for these purposes. However, the efficiency of these techniques depends not only on the approach itself, but also the numerical scheme that supports it. This work is aimed to demonstrate the advantages and disadvantages encountered during implementation of the UKF and EKF in the scheme of numerical solution of the Richards equation to obtain statements and soil parameters by assimilating surface moisture values. Numerical solutions evaluated were implemented using a finite difference scheme. The results demonstrate that a Crack -Nicolson linearized scheme is much more efficient in terms of security and time that based on an explicit scheme and safer than a UKF based on a traditional implicit numerical scheme for estimating profile soil moisture. The latter approach leads to a systematic bias in the solution 'unscented' when the central state is close to saturation. In the dual estimate (state- parameter), certain physical and mathematical parameter constraints, coupled with the bias in the estimates, resulted in substantial difficulties in the practical implementation of this technique using the UKF, or a solution that combines elements of both techniques Kalman filter

  3. Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control

    Directory of Open Access Journals (Sweden)

    Tsonyo Slavov

    2011-07-01

    Full Text Available This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For the aim an extended Kalman filter (EKF is designed. To achieve good closed-loop system performance genetic algorithm (GA based optimal controller tuning procedure is applied. A standard binary encoding GA is applied. The GA parameters and operators are specified for the considered here problem. As a result the optimal PID controller settings are obtained. The simulation experiments of the control systems based on SP with EKF and without EKF are performed. The results show that the control system based on SP with EKF has a better performance than the one without EKF. For a short time the controller sets the control variable and maintains it at the desired set point during the cultivation process. As a result, a high biomass concentration of 48.3 g·l-1 is obtained at the end of the process.

  4. Assimilation of lake water surface temperature observations using an extended Kalman filter

    Directory of Open Access Journals (Sweden)

    Ekaterina Kourzeneva

    2014-10-01

    Full Text Available A new extended Kalman filter (EKF-based algorithm to assimilate lake water surface temperature (LWST observations into the lake model/parameterisation scheme Freshwater Lake (FLake has been developed. The data assimilation algorithm has been implemented into the stand-alone offline version of FLake. The mixed and non-mixed regimes in lakes are treated separately by the EKF algorithm. The timing of the ice period is indicated implicitly: no ice if water surface temperature is measured. Numerical experiments are performed using operational in-situ observations for 27 lakes and merged observations (in-situ plus satellite for 4 lakes in Finland. Experiments are analysed, potential problems are discussed, and the role of early spring observations is studied. In general, results of experiments are promising: (1 the impact of observations (calculated as the normalised reduction of the LWST root mean square error comparing to the free model run is more than 90% and (2 in cross-validation (when observations are partly assimilated, partly used for validation the normalised reduction of the LWST error standard deviation is more than 65%. The new data assimilation algorithm will allow prognostic variables in the lake parameterisation scheme to be initialised in operational numerical weather prediction models and the effects of model errors to be corrected by using LWST observations.

  5. Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM

    Directory of Open Access Journals (Sweden)

    Nur Aqilah Othman

    2015-01-01

    Full Text Available Extended Kalman filter (EKF is often employed in determining the position of mobile robot and landmarks in simultaneous localization and mapping (SLAM. Nonetheless, there are some disadvantages of using EKF, namely, the requirement of Gaussian distribution for the state and noises, as well as the fact that it requires the smallest possible initial state covariance. This has led researchers to find alternative ways to mitigate the aforementioned shortcomings. Therefore, this study is conducted to propose an alternative technique by implementing H∞ filter in SLAM instead of EKF. In implementing H∞ filter in SLAM, the parameters of the filter especially γ need to be properly defined to prevent finite escape time problem. Hence, this study proposes a sufficient condition for the estimation purposes. Two distinct cases of initial state covariance are analysed considering an indoor environment to ensure the best solution for SLAM problem exists along with considerations of process and measurement noises statistical behaviour. If the prescribed conditions are not satisfied, then the estimation would exhibit unbounded uncertainties and consequently results in erroneous inference about the robot and landmarks estimation. The simulation results have shown the reliability and consistency as suggested by the theoretical analysis and our previous findings.

  6. Implementation of SNS Model for Intrusion Prevention in Wireless Local Area Network

    DEFF Research Database (Denmark)

    Isah, Abdullahi

    The thesis has proposed and implemented a so-called SNS (Social network security) model for intrusion prevention in the Wireless Local Area Network of an organization. An experimental design was used to implement and test the model at a university in Nigeria.......The thesis has proposed and implemented a so-called SNS (Social network security) model for intrusion prevention in the Wireless Local Area Network of an organization. An experimental design was used to implement and test the model at a university in Nigeria....

  7. Numerical implementation of a transverse-isotropic inelastic, work-hardening constitutive model

    International Nuclear Information System (INIS)

    Baladi, G.Y.

    1978-01-01

    The numerical implementation of a transverse-isotropic inelastic, work-hardening plastic constitutive model is documented. A brief review of the model is presented first to facilitate the understanding of its numerical implementation. This model is formulated in terms of 'pseudo' stress invariants, so that the incremental stress-strain relationship can be readily incorporated into existing finite-difference or infinite-element computer codes. The anisotropic model reduces to its isotropic counterpart without any changes in the mathematical formulation or in the numerical implementation (algorithm) of the model. A typical example of the model and its behavior in uniaxial strain and triaxial compression is presented. (Auth.)

  8. Filter Tuning Using the Chi-Squared Statistic

    Science.gov (United States)

    Lilly-Salkowski, Tyler

    2017-01-01

    measurements from the NASA space network (SN), which can be affected by the assumed accuracy of the TDRS satellite state at the time of the measurement.The force modelling in the EKF is also an important factor that affects the propagation accuracy and covariance sizing. The dominant force in the LEO orbit regime is the drag force caused by atmospheric drag. Accurate accounting of the drag force is especially important for the accuracy of the propagated state. The implementation of a box and wing model to improve drag estimation accuracy, and its overall effect on the covariance state is explored.The process of tuning the EKF for Aqua and Aura support is described, including examination of the measurement errors of available observation types (Doppler and range), and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-square statistic, calculated based of the ODTK EKF solutions, are assessed versus accepted norms for the orbit regime.

  9. Aerosol cluster impact and break-up: model and implementation

    International Nuclear Information System (INIS)

    Lechman, Jeremy B.

    2010-01-01

    In this report a model for simulating aerosol cluster impact with rigid walls is presented. The model is based on JKR adhesion theory and is implemented as an enhancement to the granular (DEM) package within the LAMMPS code. The theory behind the model is outlined and preliminary results are shown. Modeling the interactions of small particles is relevant to a number of applications (e.g., soils, powders, colloidal suspensions, etc.). Modeling the behavior of aerosol particles during agglomeration and cluster dynamics upon impact with a wall is of particular interest. In this report we describe preliminary efforts to develop and implement physical models for aerosol particle interactions. Future work will consist of deploying these models to simulate aerosol cluster behavior upon impact with a rigid wall for the purpose of developing relationships for impact speed and probability of stick/bounce/break-up as well as to assess the distribution of cluster sizes if break-up occurs. These relationships will be developed consistent with the need for inputs into system-level codes. Section 2 gives background and details on the physical model as well as implementations issues. Section 3 presents some preliminary results which lead to discussion in Section 4 of future plans.

  10. Implementation of the Strengths Model at an area mental health service.

    Science.gov (United States)

    Chopra, Prem; Hamilton, Bridget; Castle, David; Smith, Jenny; Mileshkin, Cris; Deans, Michael; Wynne, Brad; Prigg, Glenn; Toomey, Nigel; Wilson, Michael

    2009-06-01

    The objectives of this paper are to provide an overview of recovery-focused models of care and discuss the implementation of the Strengths Model at St. Vincent's Mental Health Melbourne (SVMH), Victoria, Australia. The implementation of the Strengths Model at SVMH is discussed with particular emphasis on the process of implementation, service implications, practical challenges and dilemmas that have arisen, and proposed evaluation. Recovery-focused care is feasible and can enhance current practice of mental health services.

  11. The Business Excellence Model for CSR Implementation?

    DEFF Research Database (Denmark)

    Neergaard, Peter; Gjerdrum Pedersen, Esben Rahbek

    2012-01-01

    Most of the Fortune 500 companies address Corporate Social Responsibility (CSR) on their websites. However, CSR remains a fluffy concept difficult to implement in organization. The European Business Excellence Model has since the introduction in 1992 served as a powerful tool for integrating...... European Award winning company has used the model to integrate CSR. The company adapted the Business Excellence model to improve performance, stimulate innovation and consensus....

  12. Models meet data: Challenges and opportunities in implementing land management in Earth system models.

    Science.gov (United States)

    Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Kuemmerle, Tobias; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Naudts, Kim

    2018-04-01

    As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land-cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices-forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire-for (1) their importance on the Earth system, (2) the possibility of implementing them in state-of-the-art ESMs, and (3) availability of required input data. Matching these criteria, we identify "low-hanging fruits" for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs. © 2017 John Wiley & Sons Ltd.

  13. Roadmap for Lean implementation in Indian automotive component manufacturing industry: comparative study of UNIDO Model and ISM Model

    Science.gov (United States)

    Jadhav, J. R.; Mantha, S. S.; Rane, S. B.

    2015-06-01

    The demands for automobiles increased drastically in last two and half decades in India. Many global automobile manufacturers and Tier-1 suppliers have already set up research, development and manufacturing facilities in India. The Indian automotive component industry started implementing Lean practices to fulfill the demand of these customers. United Nations Industrial Development Organization (UNIDO) has taken proactive approach in association with Automotive Component Manufacturers Association of India (ACMA) and the Government of India to assist Indian SMEs in various clusters since 1999 to make them globally competitive. The primary objectives of this research are to study the UNIDO-ACMA Model as well as ISM Model of Lean implementation and validate the ISM Model by comparing with UNIDO-ACMA Model. It also aims at presenting a roadmap for Lean implementation in Indian automotive component industry. This paper is based on secondary data which include the research articles, web articles, doctoral thesis, survey reports and books on automotive industry in the field of Lean, JIT and ISM. ISM Model for Lean practice bundles was developed by authors in consultation with Lean practitioners. The UNIDO-ACMA Model has six stages whereas ISM Model has eight phases for Lean implementation. The ISM-based Lean implementation model is validated through high degree of similarity with UNIDO-ACMA Model. The major contribution of this paper is the proposed ISM Model for sustainable Lean implementation. The ISM-based Lean implementation framework presents greater insight of implementation process at more microlevel as compared to UNIDO-ACMA Model.

  14. Implementation of the Interteaching Model: Implications for Staff

    Science.gov (United States)

    Chester, Andrea; Kienhuis, Mandy; Wilson, Peter

    2015-01-01

    This article describes the process of implementing a teaching innovation, the interteaching model, in a second-year psychology course. Interteaching is an evidence-based model that uses guided independent learning and reciprocal peer-tutoring to enhance student engagement and learning. The model shifts the focus from lectures to tutorials:…

  15. Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

    International Nuclear Information System (INIS)

    Barut, Murat

    2010-01-01

    This study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner; thus, it has superiority over the previous EKF schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good.

  16. Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

    Energy Technology Data Exchange (ETDEWEB)

    Barut, Murat, E-mail: muratbarut27@yahoo.co [Nigde University, Department of Electrical and Electronics Engineering, 51245 Nigde (Turkey)

    2010-10-15

    This study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner; thus, it has superiority over the previous EKF schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good.

  17. Relative Status Determination for Spacecraft Relative Motion Based on Dual Quaternion

    Directory of Open Access Journals (Sweden)

    Jun Sun

    2014-01-01

    Full Text Available For the two-satellite formation, the relative motion and attitude determination algorithm is a key component that affects the flight quality and mission efficiency. The relative status determination algorithm is proposed based on the Extended Kalman Filter (EKF and the system state optimal estimate linearization. Aiming at the relative motion of the spacecraft formation navigation problem, the spacecraft relative kinematics and dynamics model are derived from the dual quaternion in the algorithm. Then taking advantage of EKF technique, combining with the dual quaternion integrated dynamic models, considering the navigation algorithm using the fusion measurement by the gyroscope and star sensors, the relative status determination algorithm is designed. At last the simulation is done to verify the feasibility of the algorithm. The simulation results show that the EKF algorithm has faster convergence speed and higher accuracy.

  18. Numerical Implementation of the Hoek-Brown Material Model with Strain Hardening

    DEFF Research Database (Denmark)

    Sørensen, Emil Smed; Clausen, Johan; Damkilde, Lars

    2013-01-01

    A numerical implementation of the Hoek-Brown criterion is presented, which is capable of modeling important aspects of the different post-failure behaviors observed in jointed rock mass. This is done by varying the material parameters based on the accumulated plastic strains. The implementation i....... The constitutive model is demonstrated on a simulation of a tunnel excavation and the results are compared with an analytical solution for a tunnel excavation in elastic-brittle rock material.......A numerical implementation of the Hoek-Brown criterion is presented, which is capable of modeling important aspects of the different post-failure behaviors observed in jointed rock mass. This is done by varying the material parameters based on the accumulated plastic strains. The implementation...

  19. Ottawa Model of Implementation Leadership and Implementation Leadership Scale: mapping concepts for developing and evaluating theory-based leadership interventions.

    Science.gov (United States)

    Gifford, Wendy; Graham, Ian D; Ehrhart, Mark G; Davies, Barbara L; Aarons, Gregory A

    2017-01-01

    Leadership in health care is instrumental to creating a supportive organizational environment and positive staff attitudes for implementing evidence-based practices to improve patient care and outcomes. The purpose of this study is to demonstrate the alignment of the Ottawa Model of Implementation Leadership (O-MILe), a theoretical model for developing implementation leadership, with the Implementation Leadership Scale (ILS), an empirically validated tool for measuring implementation leadership. A secondary objective is to describe the methodological process for aligning concepts of a theoretical model with an independently established measurement tool for evaluating theory-based interventions. Modified template analysis was conducted to deductively map items of the ILS onto concepts of the O-MILe. An iterative process was used in which the model and scale developers (n=5) appraised the relevance, conceptual clarity, and fit of each ILS items with the O-MILe concepts through individual feedback and group discussions until consensus was reached. All 12 items of the ILS correspond to at least one O-MILe concept, demonstrating compatibility of the ILS as a measurement tool for the O-MILe theoretical constructs. The O-MILe provides a theoretical basis for developing implementation leadership, and the ILS is a compatible tool for measuring leadership based on the O-MILe. Used together, the O-MILe and ILS provide an evidence- and theory-based approach for developing and measuring leadership for implementing evidence-based practices in health care. Template analysis offers a convenient approach for determining the compatibility of independently developed evaluation tools to test theoretical models.

  20. Ottawa Model of Implementation Leadership and Implementation Leadership Scale: mapping concepts for developing and evaluating theory-based leadership interventions

    Science.gov (United States)

    Gifford, Wendy; Graham, Ian D; Ehrhart, Mark G; Davies, Barbara L; Aarons, Gregory A

    2017-01-01

    Purpose Leadership in health care is instrumental to creating a supportive organizational environment and positive staff attitudes for implementing evidence-based practices to improve patient care and outcomes. The purpose of this study is to demonstrate the alignment of the Ottawa Model of Implementation Leadership (O-MILe), a theoretical model for developing implementation leadership, with the Implementation Leadership Scale (ILS), an empirically validated tool for measuring implementation leadership. A secondary objective is to describe the methodological process for aligning concepts of a theoretical model with an independently established measurement tool for evaluating theory-based interventions. Methods Modified template analysis was conducted to deductively map items of the ILS onto concepts of the O-MILe. An iterative process was used in which the model and scale developers (n=5) appraised the relevance, conceptual clarity, and fit of each ILS items with the O-MILe concepts through individual feedback and group discussions until consensus was reached. Results All 12 items of the ILS correspond to at least one O-MILe concept, demonstrating compatibility of the ILS as a measurement tool for the O-MILe theoretical constructs. Conclusion The O-MILe provides a theoretical basis for developing implementation leadership, and the ILS is a compatible tool for measuring leadership based on the O-MILe. Used together, the O-MILe and ILS provide an evidence- and theory-based approach for developing and measuring leadership for implementing evidence-based practices in health care. Template analysis offers a convenient approach for determining the compatibility of independently developed evaluation tools to test theoretical models. PMID:29355212

  1. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  2. Modelling CRM implementation services with SysML

    OpenAIRE

    Bibiano, Luis H.; Pastor Collado, Juan Antonio; Mayol Sarroca, Enric

    2009-01-01

    CRM information systems are valuable tools for enterprises. But CRM implementation projects are risky and present a high failure rate. In this paper we regard CRM implementation projects as services that could be greatly improved by addressing them in a methodological way that can be designed with the help of tools such as SysML. Here we introduce and comment on our first experience on the use of SysML language, not very well known, for modelling the elements involved in the CRM implementatio...

  3. Theoretic models for recommendation and implementation of assistive technology

    Directory of Open Access Journals (Sweden)

    Ana Cristina de Jesus Alves

    2016-07-01

    Full Text Available Introduction: The latest international researches seek to understand the factors affecting the successful use of assistive technology devices through studies regarding the assessments systematizing; abandonment of devices; or theoric models that consider the aspects of those devices implementation. In Brazil the researches are focused on developing new technologies and there are still not sufficient studies related to the successful use of devices and ways of assistive technology implementation. Objective: To identify conceptual models used for indication and implementation of assistive technology devices. Method: Literature review. The survey was conducted in six databases: CINAHAL, Eric, GALE, LILACS, MEDLINE e PsycInfo. A critical analysis described by Grant and Booth was used. Results: There are no records of a Brazilian survey and among 29 selected articles, 17 conceptual models used in the area of AT were found; of these, 14 were specific to AT. The results showed that the new conceptual models of TA are under development and the conceptual model “Matching Person and Technology – MPT” was the most mentioned. Conclusion: We can observe that the practices related to TA area in international context shows a correlation with conceptual models, thus, we hope this study might have the capacity to contribute for the propagation of this precepts at national level

  4. Implementing Problem Resolution Models in Remedy

    CERN Document Server

    Marquina, M A; Ramos, R

    2000-01-01

    This paper defines the concept of Problem Resolution Model (PRM) and describes the current implementation made by the User Support unit at CERN. One of the main challenges of User Support services in any High Energy Physics institute/organization is to address solving of the computing-relatedproblems faced by their researchers. The User Support group at CERN is the IT unit in charge of modeling the operations of the Help Desk and acts as asecond level support to some of the support lines whose problems are receptioned at the Help Desk. The motivation behind the use of a PRM is to provide well defined procedures and methods to react in an efficient way to a request for solving a problem,providing advice, information etc. A PRM is materialized on a workflow which has a set of defined states in which a problem can be. Problems move from onestate to another according to actions as decided by the person who is handling them. A PRM can be implemented by a computer application, generallyreferred to as Problem Report...

  5. Extended Kalman Filter Modifications Based on an Optimization View Point

    OpenAIRE

    Skoglund, Martin; Hendeby, Gustaf; Axehill, Daniel

    2015-01-01

    The extended Kalman filter (EKF) has been animportant tool for state estimation of nonlinear systems sinceits introduction. However, the EKF does not possess the same optimality properties as the Kalman filter, and may perform poorly. By viewing the EKF as an optimization problem it is possible to, in many cases, improve its performance and robustness. The paper derives three variations of the EKF by applying different optimisation algorithms to the EKF costfunction and relate these to the it...

  6. Parent Management Training-Oregon Model (PMTO™) in Mexico City: Integrating Cultural Adaptation Activities in an Implementation Model.

    Science.gov (United States)

    Baumann, Ana A; Domenech Rodríguez, Melanie M; Amador, Nancy G; Forgatch, Marion S; Parra-Cardona, J Rubén

    2014-03-01

    This article describes the process of cultural adaptation at the start of the implementation of the Parent Management Training intervention-Oregon model (PMTO) in Mexico City. The implementation process was guided by the model, and the cultural adaptation of PMTO was theoretically guided by the cultural adaptation process (CAP) model. During the process of the adaptation, we uncovered the potential for the CAP to be embedded in the implementation process, taking into account broader training and economic challenges and opportunities. We discuss how cultural adaptation and implementation processes are inextricably linked and iterative and how maintaining a collaborative relationship with the treatment developer has guided our work and has helped expand our research efforts, and how building human capital to implement PMTO in Mexico supported the implementation efforts of PMTO in other places in the United States.

  7. Implementation of the model project: Ghanaian experience

    International Nuclear Information System (INIS)

    Schandorf, C.; Darko, E.O.; Yeboah, J.; Asiamah, S.D.

    2003-01-01

    Upgrading of the legal infrastructure has been the most time consuming and frustrating part of the implementation of the Model project due to the unstable system of governance and rule of law coupled with the low priority given to legislation on technical areas such as safe applications of Nuclear Science and Technology in medicine, industry, research and teaching. Dwindling Governmental financial support militated against physical and human resource infrastructure development and operational effectiveness. The trend over the last five years has been to strengthen the revenue generation base of the Radiation Protection Institute through good management practices to ensure a cost effective use of the limited available resources for a self-reliant and sustainable radiation and waste safety programme. The Ghanaian experience regarding the positive and negative aspects of the implementation of the Model Project is highlighted. (author)

  8. Modelling and Implementation of Catalogue Cards Using FreeMarker

    Science.gov (United States)

    Radjenovic, Jelen; Milosavljevic, Branko; Surla, Dusan

    2009-01-01

    Purpose: The purpose of this paper is to report on a study involving the specification (using Unified Modelling Language (UML) 2.0) of information requirements and implementation of the software components for generating catalogue cards. The implementation in a Java environment is developed using the FreeMarker software.…

  9. A Framework Proposal For Choosing A New Business Implementation Model In Henkel

    OpenAIRE

    Li, Tsz Wan

    2015-01-01

    Henkel's New Business team is a corporate venturing unit that explores corporate entrepreneurial activities on behalf of Henkel Adhesives Technologies. The new business ideas are implemented through one of these models: incubator, venturing or innovation ecosystem. In current practice, there is no systematic framework in place to choose the implementation model. The goal of the thesis is to propose a framework for choosing the most appropriate model for implementation of a new business idea i...

  10. A quantum extended Kalman filter

    International Nuclear Information System (INIS)

    Emzir, Muhammad F; Woolley, Matthew J; Petersen, Ian R

    2017-01-01

    In quantum physics, a stochastic master equation (SME) estimates the state (density operator) of a quantum system in the Schrödinger picture based on a record of measurements made on the system. In the Heisenberg picture, the SME is a quantum filter. For a linear quantum system subject to linear measurements and Gaussian noise, the dynamics may be described by quantum stochastic differential equations (QSDEs), also known as quantum Langevin equations, and the quantum filter reduces to a so-called quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to systems of nonlinear QSDEs. We will show that there are conditions under which a filter similar to a classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problem with ‘state-dependent’ covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems that involve multiple modes, nonlinear Hamiltonians, and simultaneous jump-diffusive measurements. (paper)

  11. A quantum extended Kalman filter

    Science.gov (United States)

    Emzir, Muhammad F.; Woolley, Matthew J.; Petersen, Ian R.

    2017-06-01

    In quantum physics, a stochastic master equation (SME) estimates the state (density operator) of a quantum system in the Schrödinger picture based on a record of measurements made on the system. In the Heisenberg picture, the SME is a quantum filter. For a linear quantum system subject to linear measurements and Gaussian noise, the dynamics may be described by quantum stochastic differential equations (QSDEs), also known as quantum Langevin equations, and the quantum filter reduces to a so-called quantum Kalman filter. In this article, we introduce a quantum extended Kalman filter (quantum EKF), which applies a commutative approximation and a time-varying linearization to systems of nonlinear QSDEs. We will show that there are conditions under which a filter similar to a classical EKF can be implemented for quantum systems. The boundedness of estimation errors and the filtering problem with ‘state-dependent’ covariances for process and measurement noises are also discussed. We demonstrate the effectiveness of the quantum EKF by applying it to systems that involve multiple modes, nonlinear Hamiltonians, and simultaneous jump-diffusive measurements.

  12. An alternative sensor fusion method for object orientation using low-cost MEMS inertial sensors

    Science.gov (United States)

    Bouffard, Joshua L.

    This thesis develops an alternative sensor fusion approach for object orientation using low-cost MEMS inertial sensors. The alternative approach focuses on the unique challenges of small UAVs. Such challenges include the vibrational induced noise onto the accelerometer and bias offset errors of the rate gyroscope. To overcome these challenges, a sensor fusion algorithm combines the measured data from the accelerometer and rate gyroscope to achieve a single output free from vibrational noise and bias offset errors. One of the most prevalent sensor fusion algorithms used for orientation estimation is the Extended Kalman filter (EKF). The EKF filter performs the fusion process by first creating the process model using the nonlinear equations of motion and then establishing a measurement model. With the process and measurement models established, the filter operates by propagating the mean and covariance of the states through time. The success of EKF relies on the ability to establish a representative process and measurement model of the system. In most applications, the EKF measurement model utilizes the accelerometer and GPS-derived accelerations to determine an estimate of the orientation. However, if the GPS-derived accelerations are not available then the measurement model becomes less reliable when subjected to harsh vibrational environments. This situation led to the alternative approach, which focuses on the correlation between the rate gyroscope and accelerometer-derived angle. The correlation between the two sensors then determines how much the algorithm will use one sensor over the other. The result is a measurement that does not suffer from the vibrational noise or from bias offset errors.

  13. State Estimation of Induction Motor Drives Using the Unscented Kalman Filter

    DEFF Research Database (Denmark)

    Lascu, Cristian; Jafarzadeh, Saeed; Fadali, M.Sami

    2012-01-01

    This paper investigates the application, design, and implementation of unscented Kalman filters (KFs) (UKFs) for induction motor (IM) sensorless drives. UKFs use nonlinear unscented transforms (UTs) in the prediction step in order to preserve the stochastic characteristics of a nonlinear system....... The advantage of using UTs is their ability to capture the nonlinear behavior of the system, unlike extended KFs (EKFs) that use linearized models. Four original variants of the UKF for IM state estimation, based on different UTs, are described, analyzed, and compared. The four transforms are basic, general...

  14. Design of a multi-model observer-based estimator for Fault Detection and Isolation (FDI strategy: application to a chemical reactor

    Directory of Open Access Journals (Sweden)

    Y. Chetouani

    2008-12-01

    Full Text Available This study presents a FDI strategy for nonlinear dynamic systems. It shows a methodology of tackling the fault detection and isolation issue by combining a technique based on the residuals signal and a technique using the multiple Kalman filters. The usefulness of this combination is the on-line implementation of the set of models, which represents the normal mode and all dynamics of faults, if the statistical decision threshold on the residuals exceeds a fixed value. In other cases, one Extended Kalman Filter (EKF is enough to estimate the process state. After describing the system architecture and the proposed FDI methodology, we present a realistic application in order to show the technique's potential. An algorithm is described and applied to a chemical process like a perfectly stirred chemical reactor functioning in a semi-batch mode. The chemical reaction used is an oxido reduction one, the oxidation of sodium thiosulfate by hydrogen peroxide.

  15. Practical Implementation of Various Public Key Infrastructure Models

    Directory of Open Access Journals (Sweden)

    Dmitriy Anatolievich Melnikov

    2016-03-01

    Full Text Available The paper proposes a short comparative analysis of the contemporary models of public key infrastructure (PKI and the issues of the PKI models real implementation. The Russian model of PKI is presented. Differences between the North American and West Europe models of PKI and Russian model of PKI are described. The problems of creation and main directions of further development and improvement of the Russian PKI and its integration into the global trust environment are defined.

  16. Implementation and automated validation of the minimal Z' model in FeynRules

    International Nuclear Information System (INIS)

    Basso, L.; Christensen, N.D.; Duhr, C.; Fuks, B.; Speckner, C.

    2012-01-01

    We describe the implementation of a well-known class of U(1) gauge models, the 'minimal' Z' models, in FeynRules. We also describe a new automated validation tool for FeynRules models which is controlled by a web interface and allows the user to run a complete set of 2 → 2 processes on different matrix element generators, different gauges, and compare between them all. If existing, the comparison with independent implementations is also possible. This tool has been used to validate our implementation of the 'minimal' Z' models. (authors)

  17. Impact of implementation choices on quantitative predictions of cell-based computational models

    Science.gov (United States)

    Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

    2017-09-01

    'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

  18. A model based security testing method for protocol implementation.

    Science.gov (United States)

    Fu, Yu Long; Xin, Xiao Long

    2014-01-01

    The security of protocol implementation is important and hard to be verified. Since the penetration testing is usually based on the experience of the security tester and the specific protocol specifications, a formal and automatic verification method is always required. In this paper, we propose an extended model of IOLTS to describe the legal roles and intruders of security protocol implementations, and then combine them together to generate the suitable test cases to verify the security of protocol implementation.

  19. Exploiting the Expressiveness of Cyclo-Static Dataflow to Model Multimedia Implementations

    Directory of Open Access Journals (Sweden)

    Henk Corporaal

    2007-01-01

    Full Text Available The design of increasingly complex and concurrent multimedia systems requires a description at a higher abstraction level. Using an appropriate model of computation helps to reason about the system and enables design time analysis methods. The nature of multimedia processing matches in many cases well with cyclo-static dataflow (CSDF, making it a suitable model. However, channels in an implementation often use for cost reasons a kind of shared buffer that cannot be directly described in CSDF. This paper shows how such implementation specific aspects can be expressed in CSDF without the need for extensions. Consequently, the CSDF graph remains completely analyzable and allows reasoning about its temporal behavior. The obtained relation between model and implementation enables a buffer capacity analysis on the model while assuring the throughput of the final implementation. The capabilities of the approach are demonstrated by analyzing the temporal behavior of an MPEG-4 video encoder with a CSDF graph.

  20. Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons.

    Science.gov (United States)

    Zhuang, Yuan; Yang, Jun; Li, You; Qi, Longning; El-Sheimy, Naser

    2016-04-26

    Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target's location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of EKF algorithm and 15.77% more accurate than EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of EKF algorithm and 21.41% better than EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.

  1. The layered learning practice model: Lessons learned from implementation.

    Science.gov (United States)

    Pinelli, Nicole R; Eckel, Stephen F; Vu, Maihan B; Weinberger, Morris; Roth, Mary T

    2016-12-15

    Pharmacists' views about the implementation, benefits, and attributes of a layered learning practice model (LLPM) were examined. Eligible and willing attending pharmacists at the same institution that had implemented an LLPM completed an individual, 90-minute, face-to-face interview using a structured interview guide developed by the interdisciplinary study team. Interviews were digitally recorded and transcribed verbatim without personal identifiers. Three researchers independently reviewed preliminary findings to reach consensus on emerging themes. In cases where thematic coding diverged, the researchers discussed their analyses until consensus was reached. Of 25 eligible attending pharmacists, 24 (96%) agreed to participate. The sample was drawn from both acute and ambulatory care practice settings and all clinical specialty areas. Attending pharmacists described several experiences implementing the LLPM and perceived benefits of the model. Attending pharmacists identified seven key attributes for hospital and health-system pharmacy departments that are needed to design and implement effective LLPMs: shared leadership, a systematic approach, good communication, flexibility for attending pharmacists, adequate resources, commitment, and evaluation. Participants also highlighted several potential challenges and obstacles for organizations to consider before implementing an LLPM. According to attending pharmacists involved in an LLPM, successful implementation of an LLPM required shared leadership, a systematic approach, communication, flexibility, resources, commitment, and a process for evaluation. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

  2. Implementation of the Rauch-Tung-Striebel smoother for sensor compatibility correction of a fixed-wing unmanned air vehicle.

    Science.gov (United States)

    Chan, Woei-Leong; Hsiao, Fei-Bin

    2011-01-01

    This paper presents a complete procedure for sensor compatibility correction of a fixed-wing Unmanned Air Vehicle (UAV). The sensors consist of a differential air pressure transducer for airspeed measurement, two airdata vanes installed on an airdata probe for angle of attack (AoA) and angle of sideslip (AoS) measurement, and an Attitude and Heading Reference System (AHRS) that provides attitude angles, angular rates, and acceleration. The procedure is mainly based on a two pass algorithm called the Rauch-Tung-Striebel (RTS) smoother, which consists of a forward pass Extended Kalman Filter (EKF) and a backward recursion smoother. On top of that, this paper proposes the implementation of the Wiener Type Filter prior to the RTS in order to avoid the complicated process noise covariance matrix estimation. Furthermore, an easy to implement airdata measurement noise variance estimation method is introduced. The method estimates the airdata and subsequently the noise variances using the ground speed and ascent rate provided by the Global Positioning System (GPS). It incorporates the idea of data regionality by assuming that some sort of statistical relation exists between nearby data points. Root mean square deviation (RMSD) is being employed to justify the sensor compatibility. The result shows that the presented procedure is easy to implement and it improves the UAV sensor data compatibility significantly.

  3. Implementing Model-Check for Employee and Management Satisfaction

    Science.gov (United States)

    Jones, Corey; LaPha, Steven

    2013-01-01

    This presentation will discuss methods to which ModelCheck can be implemented to not only improve model quality, but also satisfy both employees and management through different sets of quality checks. This approach allows a standard set of modeling practices to be upheld throughout a company, with minimal interaction required by the end user. The presenter will demonstrate how to create multiple ModelCheck standards, preventing users from evading the system, and how it can improve the quality of drawings and models.

  4. FPGA implementation of predictive degradation model for engine oil lifetime

    Science.gov (United States)

    Idros, M. F. M.; Razak, A. H. A.; Junid, S. A. M. Al; Suliman, S. I.; Halim, A. K.

    2018-03-01

    This paper presents the implementation of linear regression model for degradation prediction on Register Transfer Logic (RTL) using QuartusII. A stationary model had been identified in the degradation trend for the engine oil in a vehicle in time series method. As for RTL implementation, the degradation model is written in Verilog HDL and the data input are taken at a certain time. Clock divider had been designed to support the timing sequence of input data. At every five data, a regression analysis is adapted for slope variation determination and prediction calculation. Here, only the negative value are taken as the consideration for the prediction purposes for less number of logic gate. Least Square Method is adapted to get the best linear model based on the mean values of time series data. The coded algorithm has been implemented on FPGA for validation purposes. The result shows the prediction time to change the engine oil.

  5. On the implementation of the spherical collapse model for dark energy models

    Energy Technology Data Exchange (ETDEWEB)

    Pace, Francesco [Jodrell Bank Centre for Astrophysics, School of Physics and Astronomy, The University of Manchester, Manchester, M13 9PL (United Kingdom); Meyer, Sven; Bartelmann, Matthias, E-mail: francesco.pace@manchester.ac.uk, E-mail: sven.meyer@uni-heidelberg.de, E-mail: bartelmann@uni-heidelberg.de [Zentrum für Astronomie der Universität Heidelberg, Institut für theoretische Astrophysik, Philosophenweg 12, D-69120, Heidelberg (Germany)

    2017-10-01

    In this work we review the theory of the spherical collapse model and critically analyse the aspects of the numerical implementation of its fundamental equations. By extending a recent work by [1], we show how different aspects, such as the initial integration time, the definition of constant infinity and the criterion for the extrapolation method (how close the inverse of the overdensity has to be to zero at the collapse time) can lead to an erroneous estimation (a few per mill error which translates to a few percent in the mass function) of the key quantity in the spherical collapse model: the linear critical overdensity δ{sub c}, which plays a crucial role for the mass function of halos. We provide a better recipe to adopt in designing a code suitable to a generic smooth dark energy model and we compare our numerical results with analytic predictions for the EdS and the ΛCDM models. We further discuss the evolution of δ{sub c} for selected classes of dark energy models as a general test of the robustness of our implementation. We finally outline which modifications need to be taken into account to extend the code to more general classes of models, such as clustering dark energy models and non-minimally coupled models.

  6. On the implementation of the spherical collapse model for dark energy models

    Science.gov (United States)

    Pace, Francesco; Meyer, Sven; Bartelmann, Matthias

    2017-10-01

    In this work we review the theory of the spherical collapse model and critically analyse the aspects of the numerical implementation of its fundamental equations. By extending a recent work by [1], we show how different aspects, such as the initial integration time, the definition of constant infinity and the criterion for the extrapolation method (how close the inverse of the overdensity has to be to zero at the collapse time) can lead to an erroneous estimation (a few per mill error which translates to a few percent in the mass function) of the key quantity in the spherical collapse model: the linear critical overdensity δc, which plays a crucial role for the mass function of halos. We provide a better recipe to adopt in designing a code suitable to a generic smooth dark energy model and we compare our numerical results with analytic predictions for the EdS and the ΛCDM models. We further discuss the evolution of δc for selected classes of dark energy models as a general test of the robustness of our implementation. We finally outline which modifications need to be taken into account to extend the code to more general classes of models, such as clustering dark energy models and non-minimally coupled models.

  7. Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons

    Directory of Open Access Journals (Sweden)

    Yuan Zhuang

    2016-04-01

    Full Text Available Indoor wireless localization using Bluetooth Low Energy (BLE beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM, channel-separate fingerprinting (FP, outlier detection and extended Kalman filtering (EKF for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target’s location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy. The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m, which performs 35.82% better than <3.99 m from the Propagation Model (PM + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m, the proposed algorithm achieves the accuracies of <3.88 m at

  8. Implementation of a PETN failure model using ARIA's general chemistry framework

    Energy Technology Data Exchange (ETDEWEB)

    Hobbs, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-01-01

    We previously developed a PETN thermal decomposition model that accurately predicts thermal ignition and detonator failure [1]. This model was originally developed for CALORE [2] and required several complex user subroutines. Recently, a simplified version of the PETN decomposition model was implemented into ARIA [3] using a general chemistry framework without need for user subroutines. Detonator failure was also predicted with this new model using ENCORE. The model was simplified by 1) basing the model on moles rather than mass, 2) simplifying the thermal conductivity model, and 3) implementing ARIA’s new phase change model. This memo briefly describes the model, implementation, and validation.

  9. A New State of Charge Estimation Method for LiFePO4 Battery Packs Used in Robots

    Directory of Open Access Journals (Sweden)

    Han-Pang Huang

    2013-04-01

    Full Text Available The accurate state of charge (SOC estimation of the LiFePO4 battery packs used in robot applications is required for better battery life cycle, performance, reliability, and economic issues. In this paper, a new SOC estimation method, “Modified ECE + EKF”, is proposed. The method is the combination of the modified Equivalent Coulombic Efficiency (ECE method and the Extended Kalman Filter (EKF method. It is based on the zero-state hysteresis battery model, and adopts the EKF method to correct the initial value used in the Ah counting method. Experimental results show that the proposed technique is superior to the traditional techniques, such as ECE + EKF and ECE + Unscented Kalman Filter (UKF, and the accuracy of estimation is within 1%.

  10. Comparative analysis of coupled creep-damage model implementations and application

    International Nuclear Information System (INIS)

    Bhandari, S.; Feral, X.; Bergheau, J.M.; Mottet, G.; Dupas, P.; Nicolas, L.

    1998-01-01

    Creep rupture of a reactor pressure vessel in a severe accident occurs after complex load and temperature histories leading to interactions between creep deformations, stress relaxation, material damaging and plastic instability. The concepts of continuous damage introduced by Kachanov and Robotnov allow to formulate models coupling elasto-visco-plasticity and damage. However, the integration of such models in a finite element code creates some difficulties related to the strong non-linearity of the constitutive equations. It was feared that different methods of implementation of such a model might lead to different results which, consequently, might limit the application and usefulness of such a model. The Commissariat a l'Energie Atomique (CEA), Electricite de France (EDF) and Framasoft (FRA) have worked out numerical solutions to implement such a model in respectively CASTEM 2000, ASTER and SYSTUS codes. A ''benchmark'' was set up, chosen on the basis of a cylinder studied in the programme ''RUPTHER''. The aim of this paper is not to enter into the numerical details of the implementation of the model, but to present the results of the comparative study made using the three codes mentioned above, on a case of engineering interest. The results of the coupled model will also be compared to an uncoupled model to evaluate differences one can obtain between a simple uncoupled model and a more sophisticated coupled model. The main conclusion drawn from this study is that the different numerical implementations used for the coupled damage-visco-plasticity model give quite consistent results. The numerical difficulty inherent to the integration of the strongly non-linear constitutive equations have been resolved using Runge-Kutta or mid-point rule. The usefulness of the coupled model comes from the fact the uncoupled model leads to too conservative results, at least in the example treated and in particular for the uncoupled analysis under the hypothesis of the small

  11. Implementing a new model for on-the-job training: critical success factors.

    NARCIS (Netherlands)

    van Zolingen, S.J.; Streumer, Jan; van der Klink, Marcel; de Jong, Rolinda

    2000-01-01

    Post Offices Inc. in The Netherlands has developed and implemented a new instruction model for the training of desk employees. The quality of the new instruction model was assessed by means of the evaluation model of Jacobs and Jones for on-the-job training. It is concluded that the implementation

  12. An Analogue VLSI Implementation of the Meddis Inner Hair Cell Model

    Science.gov (United States)

    McEwan, Alistair; van Schaik, André

    2003-12-01

    The Meddis inner hair cell model is a widely accepted, but computationally intensive computer model of mammalian inner hair cell function. We have produced an analogue VLSI implementation of this model that operates in real time in the current domain by using translinear and log-domain circuits. The circuit has been fabricated on a chip and tested against the Meddis model for (a) rate level functions for onset and steady-state response, (b) recovery after masking, (c) additivity, (d) two-component adaptation, (e) phase locking, (f) recovery of spontaneous activity, and (g) computational efficiency. The advantage of this circuit, over other electronic inner hair cell models, is its nearly exact implementation of the Meddis model which can be tuned to behave similarly to the biological inner hair cell. This has important implications on our ability to simulate the auditory system in real time. Furthermore, the technique of mapping a mathematical model of first-order differential equations to a circuit of log-domain filters allows us to implement real-time neuromorphic signal processors for a host of models using the same approach.

  13. Implementation of a documentation model comprising nursing terminologies--theoretical and methodological issues.

    Science.gov (United States)

    von Krogh, Gunn; Nåden, Dagfinn

    2008-04-01

    To describe and discuss theoretical and methodological issues of implementation of a nursing services documentation model comprising NANDA nursing diagnoses, Nursing Intervention Classification and Nursing Outcome Classification terminologies. The model is developed for electronic patient record and was implemented in a psychiatric hospital on an organizational level and on five test wards in 2001-2005. The theory of Rogers guided the process of innovation, whereas the implementation procedure of McCloskey and Bulecheck combined with adult learning principals guided the test site implementation. The test wards managed in different degrees to adopt the model. Two wards succeeded fully, including a ward with high percentage of staff with interdisciplinary background. Better planning regarding the impact of the organization's innovative aptitude, the innovation strategies and the use of differentiated methods regarding the clinician's individual premises for learning nursing terminologies might have enhanced the adoption to the model. To better understand the nature of barriers and the importance of careful planning regarding the implementation of electronic patient record elements in nursing care services, focusing on nursing terminologies. Further to indicate how a theory and specific procedure can be used to guide the process of implementation throughout the different levels of management.

  14. Estimation of the Dynamic States of Synchronous Machines Using an Extended Particle Filter

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Ning; Meng, Da; Lu, Shuai

    2013-11-11

    In this paper, an extended particle filter (PF) is proposed to estimate the dynamic states of a synchronous machine using phasor measurement unit (PMU) data. A PF propagates the mean and covariance of states via Monte Carlo simulation, is easy to implement, and can be directly applied to a non-linear system with non-Gaussian noise. The extended PF modifies a basic PF to improve robustness. Using Monte Carlo simulations with practical noise and model uncertainty considerations, the extended PF’s performance is evaluated and compared with the basic PF and an extended Kalman filter (EKF). The extended PF results showed high accuracy and robustness against measurement and model noise.

  15. Evidence of "Implemented Anticipation" in Mathematising by Beginning Modellers

    Science.gov (United States)

    Stillman, Gloria; Brown, Jill P.

    2014-01-01

    Data from open modelling sessions for year 10 and 11 students at an extracurricular modelling event and from a year 9 class participating in a programme of structured modelling of real situations were analysed for evidence of Niss's theoretical construct, "implemented anticipation," during mathematisation. Evidence was found for all…

  16. Assessment and development of implementation models of health ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Assessment and development of implementation models of health-related ... The Contribution of Civil Society Organizations in Achieving Health for All ... Health Information for Maternal and Child Health Planning in Urban Bangladesh.

  17. Implementation and validation of the condensation model for containment hydrogen distribution studies

    International Nuclear Information System (INIS)

    Ravva, Srinivasa Rao; Iyer, Kannan N.; Gupta, S.K.; Gaikwad, Avinash J.

    2014-01-01

    Highlights: • A condensation model based on diffusion was implemented in FLUENT. • Validation of a condensation model for the H 2 distribution studies was performed. • Multi-component diffusion is used in the present work. • Appropriate grid and turbulence model were identified. - Abstract: This paper aims at the implementation details of a condensation model in the CFD code FLUENT and its validation so that it can be used in performing the containment hydrogen distribution studies. In such studies, computational fluid dynamics simulations are necessary for obtaining accurate predictions. While steam condensation plays an important role, commercial CFD codes such as FLUENT do not have an in-built condensation model. Therefore, a condensation model was developed and implemented in the FLUENT code through user defined functions (UDFs) for the sink terms in the mass, momentum, energy and species balance equations together with associated turbulence quantities viz., kinetic energy and dissipation rate. The implemented model was validated against the ISP-47 test of TOSQAN facility using the standard wall functions and enhanced wall treatment approaches. The best suitable grid size and the turbulence model for the low density gas (He) distribution studies are brought out in this paper

  18. Development of Vision Control Scheme of Extended Kalman filtering for Robot's Position Control

    International Nuclear Information System (INIS)

    Jang, W. S.; Kim, K. S.; Park, S. I.; Kim, K. Y.

    2003-01-01

    It is very important to reduce the computational time in estimating the parameters of vision control algorithm for robot's position control in real time. Unfortunately, the batch estimation commonly used requires too murk computational time because it is iteration method. So, the batch estimation has difficulty for robot's position control in real time. On the other hand, the Extended Kalman Filtering(EKF) has many advantages to calculate the parameters of vision system in that it is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm for the robot's vision control in real time. The vision system model used in this study involves six parameters to account for the inner(orientation, focal length etc) and outer (the relative location between robot and camera) parameters of camera. Then, EKF has been first applied to estimate these parameters, and then with these estimated parameters, also to estimate the robot's joint angles used for robot's operation. finally, the practicality of vision control scheme based on the EKF has been experimentally verified by performing the robot's position control

  19. Robust Model Predictive Control of a Wind Turbine

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

  20. Digital hardware implementation of a stochastic two-dimensional neuron model.

    Science.gov (United States)

    Grassia, F; Kohno, T; Levi, T

    2016-11-01

    This study explores the feasibility of stochastic neuron simulation in digital systems (FPGA), which realizes an implementation of a two-dimensional neuron model. The stochasticity is added by a source of current noise in the silicon neuron using an Ornstein-Uhlenbeck process. This approach uses digital computation to emulate individual neuron behavior using fixed point arithmetic operation. The neuron model's computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. The experimental results confirmed the validity of the developed stochastic FPGA implementation, which makes the implementation of the silicon neuron more biologically plausible for future hybrid experiments. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Modeling, Design, and Implementation of a Cloud Workflow Engine Based on Aneka

    OpenAIRE

    Zhou, Jiantao; Sun, Chaoxin; Fu, Weina; Liu, Jing; Jia, Lei; Tan, Hongyan

    2014-01-01

    This paper presents a Petri net-based model for cloud workflow which plays a key role in industry. Three kinds of parallelisms in cloud workflow are characterized and modeled. Based on the analysis of the modeling, a cloud workflow engine is designed and implemented in Aneka cloud environment. The experimental results validate the effectiveness of our approach of modeling, design, and implementation of cloud workflow.

  2. Cognon Neural Model Software Verification and Hardware Implementation Design

    Science.gov (United States)

    Haro Negre, Pau

    Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ˜104 synapses of neurons in an adjacent layer. The information necessary for cognition is contained in theses synapses, which strengthen during the learning phase in response to newly presented spike patterns. Continuing on the model proposed in "Models for Neural Spike Computation and Cognition" by David H. Staelin and Carl H. Staelin, this study seeks to understand cognition from an information theoretic perspective and develop potential models for artificial implementation of cognition based on neuronal models. To do so we focus on the mathematical properties and limitations of spike-based cognition consistent with existing neurological observations. We validate the cognon model through software simulation and develop concepts for an optical hardware implementation of a network of artificial neural cognons.

  3. Implementation and verification of interface constitutive model in FLAC3D

    Directory of Open Access Journals (Sweden)

    Hai-min Wu

    2011-09-01

    Full Text Available Due to the complexity of soil-structure interaction, simple constitutive models typically used for interface elements in general computer programs cannot satisfy the requirements of discontinuous deformation analysis of structures that contain different interfaces. In order to simulate the strain-softening characteristics of interfaces, a nonlinear strain-softening interface constitutive model was incorporated into fast Lagrange analysis of continua in three dimensions (FLAC3D through a user-defined program in the FISH environment. A numerical simulation of a direct shear test for geosynthetic interfaces was conducted to verify that the interface model was implemented correctly. Results of the numerical tests show good agreement with the results obtained from theoretical calculations, indicating that the model incorporated into FLAC3D can simulate the nonlinear strain-softening behavior of interfaces involving geosynthetic materials. The results confirmed the validity and reliability of the improved interface model. The procedure and method of implementing an interface constitutive model into a commercial computer program also provide a reference for implementation of a new interface constitutive model in FLAC3D.

  4. A Novel Attitude Determination System Aided by Polarization Sensor

    Directory of Open Access Journals (Sweden)

    Wei Zhi

    2018-01-01

    Full Text Available This paper aims to develop a novel attitude determination system aided by polarization sensor. An improved heading angle function is derived using the perpendicular relationship between directions of E-vector of linearly polarized light and solar vector in the atmospheric polarization distribution model. The Extended Kalman filter (EKF with quaternion differential equation as a dynamic model is applied to fuse the data from sensors. The covariance functions of filter process and measurement noises are deduced in detail. The indoor and outdoor tests are conducted to verify the validity and feasibility of proposed attitude determination system. The test results showed that polarization sensor is not affected by magnetic field, thus the proposed system can work properly in environments containing the magnetic interference. The results also showed that proposed system has higher measurement accuracy than common attitude determination system and can provide precise parameters for Unmanned Aerial Vehicle (UAV flight control. The main contribution of this paper is implementation of the EKF for incorporating the self-developed polarization sensor into the conventional attitude determination system. The real-world experiment with the quad-rotor proved that proposed system can work in a magnetic interference environment and provide sufficient accuracy in attitude determination for autonomous navigation of vehicle.

  5. A Novel Attitude Determination System Aided by Polarization Sensor.

    Science.gov (United States)

    Zhi, Wei; Chu, Jinkui; Li, Jinshan; Wang, Yinlong

    2018-01-09

    This paper aims to develop a novel attitude determination system aided by polarization sensor. An improved heading angle function is derived using the perpendicular relationship between directions of E-vector of linearly polarized light and solar vector in the atmospheric polarization distribution model. The Extended Kalman filter (EKF) with quaternion differential equation as a dynamic model is applied to fuse the data from sensors. The covariance functions of filter process and measurement noises are deduced in detail. The indoor and outdoor tests are conducted to verify the validity and feasibility of proposed attitude determination system. The test results showed that polarization sensor is not affected by magnetic field, thus the proposed system can work properly in environments containing the magnetic interference. The results also showed that proposed system has higher measurement accuracy than common attitude determination system and can provide precise parameters for Unmanned Aerial Vehicle (UAV) flight control. The main contribution of this paper is implementation of the EKF for incorporating the self-developed polarization sensor into the conventional attitude determination system. The real-world experiment with the quad-rotor proved that proposed system can work in a magnetic interference environment and provide sufficient accuracy in attitude determination for autonomous navigation of vehicle.

  6. Ottawa Model of Implementation Leadership and Implementation Leadership Scale: mapping concepts for developing and evaluating theory-based leadership interventions

    Directory of Open Access Journals (Sweden)

    Gifford W

    2017-03-01

    Full Text Available Wendy Gifford,1 Ian D Graham,2,3 Mark G Ehrhart,4 Barbara L Davies,5,6 Gregory A Aarons7 1School of Nursing, Faculty of Health Sciences, University of Ottawa, ON, Canada; 2Centre for Practice-Changing Research, Ottawa Hospital Research Institute, 3School of Epidemiology, Public Health and Preventive Medicine, Facility of Medicine, University of Ottawa, Ottawa, ON, Canada; 4Department of Psychology, San Diego State University, San Diego, CA, USA; 5Nursing Best Practice Research Center, University of Ottawa, Ottawa, ON, Canada; 6Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; 7Child and Adolescent Services Research Center, University of California, San Diego, CA, USA Purpose: Leadership in health care is instrumental to creating a supportive organizational environment and positive staff attitudes for implementing evidence-based practices to improve patient care and outcomes. The purpose of this study is to demonstrate the alignment of the Ottawa Model of Implementation Leadership (O-MILe, a theoretical model for developing implementation leadership, with the Implementation Leadership Scale (ILS, an empirically validated tool for measuring implementation leadership. A secondary objective is to describe the methodological process for aligning concepts of a theoretical model with an independently established measurement tool for evaluating theory-based interventions.Methods: Modified template analysis was conducted to deductively map items of the ILS onto concepts of the O-MILe. An iterative process was used in which the model and scale developers (n=5 appraised the relevance, conceptual clarity, and fit of each ILS items with the O-MILe concepts through individual feedback and group discussions until consensus was reached.Results: All 12 items of the ILS correspond to at least one O-MILe concept, demonstrating compatibility of the ILS as a measurement tool for the O-MILe theoretical constructs.Conclusion: The O

  7. Discrimination of Li-ion batteries based on Hamming network using discharging-charging voltage pattern recognition for improved state-of-charge estimation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jonghoon; Lee, Seongjun; Cho, B.H. [Power Electronics System Laboratory, School of Electrical Engineering and Computer Science, Seoul National University, Seoul 151-744 (Korea, Republic of)

    2011-02-15

    Differences in electrochemical characteristics among Li-ion batteries and factors such as temperature and ageing result in erroneous state-of-charge (SoC) estimation when using the existing extended Kalman filter (EKF) algorithm. This study presents an application of the Hamming neural network to the identification of suitable battery model parameters for improved SoC estimation. The discharging-charging voltage (DCV) patterns of ten fresh Li-ion batteries are measured, together with the battery parameters, as representative patterns. Through statistical analysis, the Hamming network is applied for identification of the representative DCV pattern that matches most closely of the pattern of the arbitrary battery to be measured. Model parameters of the representative battery are then applied to estimate the SoC of the arbitrary battery using the EKF. This avoids the need for repeated parameter measurement. Using model parameters selected by the proposed method, all SoC estimates (off-line and on-line) based on the EKF are within {+-}5% of the values estimated by ampere-hour counting. (author)

  8. Extended Kalman filter-based methods for pose estimation using visual, inertial and magnetic sensors: comparative analysis and performance evaluation.

    Science.gov (United States)

    Ligorio, Gabriele; Sabatini, Angelo Maria

    2013-02-04

    In this paper measurements from a monocular vision system are fused with inertial/magnetic measurements from an Inertial Measurement Unit (IMU) rigidly connected to the camera. Two Extended Kalman filters (EKFs) were developed to estimate the pose of the IMU/camera sensor moving relative to a rigid scene (ego-motion), based on a set of fiducials. The two filters were identical as for the state equation and the measurement equations of the inertial/magnetic sensors. The DLT-based EKF exploited visual estimates of the ego-motion using a variant of the Direct Linear Transformation (DLT) method; the error-driven EKF exploited pseudo-measurements based on the projection errors from measured two-dimensional point features to the corresponding three-dimensional fiducials. The two filters were off-line analyzed in different experimental conditions and compared to a purely IMU-based EKF used for estimating the orientation of the IMU/camera sensor. The DLT-based EKF was more accurate than the error-driven EKF, less robust against loss of visual features, and equivalent in terms of computational complexity. Orientation root mean square errors (RMSEs) of 1° (1.5°), and position RMSEs of 3.5 mm (10 mm) were achieved in our experiments by the DLT-based EKF (error-driven EKF); by contrast, orientation RMSEs of 1.6° were achieved by the purely IMU-based EKF.

  9. Implementation of IEC standard models for power system stability studies

    Energy Technology Data Exchange (ETDEWEB)

    Margaris, Ioannis D.; Hansen, Anca D.; Soerensen, Poul [Technical Univ. of Denmark, Roskilde (Denmark). Dept. of Wind Energy; Bech, John; Andresen, Bjoern [Siemens Wind Power A/S, Brande (Denmark)

    2012-07-01

    This paper presents the implementation of the generic wind turbine generator (WTG) electrical simulation models proposed in the IEC 61400-27 standard which is currently in preparation. A general overview of the different WTG types is given while the main focus is on Type 4B WTG standard model, namely a model for a variable speed wind turbine with full scale power converter WTG including a 2-mass mechanical model. The generic models for fixed and variable speed WTGs models are suitable for fundamental frequency positive sequence response simulations during short events in the power system such as voltage dips. The general configuration of the models is presented and discussed; model implementation in the simulation software platform DIgSILENT PowerFactory is presented in order to illustrate the range of applicability of the generic models under discussion. A typical voltage dip is simulated and results from the basic electrical variables of the WTG are presented and discussed. (orig.)

  10. Implementation ambiguity: The fifth element long lost in uncertainty budgets for land biogeochemical modeling

    Science.gov (United States)

    Tang, J.; Riley, W. J.

    2015-12-01

    Previous studies have identified four major sources of predictive uncertainty in modeling land biogeochemical (BGC) processes: (1) imperfect initial conditions (e.g., assumption of preindustrial equilibrium); (2) imperfect boundary conditions (e.g., climate forcing data); (3) parameterization (type I equifinality); and (4) model structure (type II equifinality). As if that were not enough to cause substantial sleep loss in modelers, we propose here a fifth element of uncertainty that results from implementation ambiguity that occurs when the model's mathematical description is translated into computational code. We demonstrate the implementation ambiguity using the example of nitrogen down regulation, a necessary process in modeling carbon-climate feedbacks. We show that, depending on common land BGC model interpretations of the governing equations for mineral nitrogen, there are three different implementations of nitrogen down regulation. We coded these three implementations in the ACME land model (ALM), and explored how they lead to different preindustrial and contemporary land biogeochemical states and fluxes. We also show how this implementation ambiguity can lead to different carbon-climate feedback estimates across the RCP scenarios. We conclude by suggesting how to avoid such implementation ambiguity in ESM BGC models.

  11. Implementing network constraints in the EMPS model

    Energy Technology Data Exchange (ETDEWEB)

    Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.

    2010-02-15

    This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)

  12. An Analogue VLSI Implementation of the Meddis Inner Hair Cell Model

    Directory of Open Access Journals (Sweden)

    Alistair McEwan

    2003-06-01

    Full Text Available The Meddis inner hair cell model is a widely accepted, but computationally intensive computer model of mammalian inner hair cell function. We have produced an analogue VLSI implementation of this model that operates in real time in the current domain by using translinear and log-domain circuits. The circuit has been fabricated on a chip and tested against the Meddis model for (a rate level functions for onset and steady-state response, (b recovery after masking, (c additivity, (d two-component adaptation, (e phase locking, (f recovery of spontaneous activity, and (g computational efficiency. The advantage of this circuit, over other electronic inner hair cell models, is its nearly exact implementation of the Meddis model which can be tuned to behave similarly to the biological inner hair cell. This has important implications on our ability to simulate the auditory system in real time. Furthermore, the technique of mapping a mathematical model of first-order differential equations to a circuit of log-domain filters allows us to implement real-time neuromorphic signal processors for a host of models using the same approach.

  13. Lean business model and implementation of a geriatric fracture center.

    Science.gov (United States)

    Kates, Stephen L

    2014-05-01

    Geriatric hip fracture is a common event associated with high costs of care and often with suboptimal outcomes for the patients. Ideally, a new care model to manage geriatric hip fractures would address both quality and safety of patient care as well as the need for reduced costs of care. The geriatric fracture center model of care is one such model reported to improve both outcomes and quality of care. It is a lean business model applied to medicine. This article describes basic lean business concepts applied to geriatric fracture care and information needed to successfully implement a geriatric fracture center. It is written to assist physicians and surgeons in their efforts to implement an improved care model for their patients. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Recursive Estimation of π-Line Parameters for Electric Power Distribution Grids

    DEFF Research Database (Denmark)

    Prostejovsky, Alexander; Gehrke, Oliver; Kosek, Anna Magdalena

    2016-01-01

    an Extended Kalman Filter (EKF) whose measurement noise covariance matrix is modified in order to account for all noisy variables in the overdetermined system. Simulations confirm the advantages of the EKF over the previously used Least-Squares (LSQ) estimator. In the low random noise cases considered...... in this paper, the EKF yields a four-fold improvement over the LSQ for the parallel susceptance across all quantization ranges. For the highest levels of random and quantization noise, the EKF performs about 1.5 to 3 times better than the LSQ for all line parameters. Furthermore, the EKF shows more consistent...

  15. Dynamic imaging in electrical impedance tomography of the human chest with online transition matrix identification.

    Science.gov (United States)

    Moura, Fernando Silva; Aya, Julio Cesar Ceballos; Fleury, Agenor Toledo; Amato, Marcelo Britto Passos; Lima, Raul Gonzalez

    2010-02-01

    One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

  16. A Two-stage Kalman Filter for Sensorless Direct Torque Controlled PM Synchronous Motor Drive

    Directory of Open Access Journals (Sweden)

    Boyu Yi

    2013-01-01

    Full Text Available This paper presents an optimal two-stage extended Kalman filter (OTSEKF for closed-loop flux, torque, and speed estimation of a permanent magnet synchronous motor (PMSM to achieve sensorless DTC-SVPWM operation of drive system. The novel observer is obtained by using the same transformation as in a linear Kalman observer, which is proposed by C.-S. Hsieh and F.-C. Chen in 1999. The OTSEKF is an effective implementation of the extended Kalman filter (EKF and provides a recursive optimum state estimation for PMSMs using terminal signals that may be polluted by noise. Compared to a conventional EKF, the OTSEKF reduces the number of arithmetic operations. Simulation and experimental results verify the effectiveness of the proposed OTSEKF observer for DTC of PMSMs.

  17. Comparative analysis of elements and models of implementation in local-level spatial plans in Serbia

    Directory of Open Access Journals (Sweden)

    Stefanović Nebojša

    2017-01-01

    Full Text Available Implementation of local-level spatial plans is of paramount importance to the development of the local community. This paper aims to demonstrate the importance of and offer further directions for research into the implementation of spatial plans by presenting the results of a study on models of implementation. The paper describes the basic theoretical postulates of a model for implementing spatial plans. A comparative analysis of the application of elements and models of implementation of plans in practice was conducted based on the spatial plans for the local municipalities of Arilje, Lazarevac and Sremska Mitrovica. The analysis includes four models of implementation: the strategy and policy of spatial development; spatial protection; the implementation of planning solutions of a technical nature; and the implementation of rules of use, arrangement and construction of spaces. The main results of the analysis are presented and used to give recommendations for improving the elements and models of implementation. Final deliberations show that models of implementation are generally used in practice and combined in spatial plans. Based on the analysis of how models of implementation are applied in practice, a general conclusion concerning the complex character of the local level of planning is presented and elaborated. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36035: Spatial, Environmental, Energy and Social Aspects of Developing Settlements and Climate Change - Mutual Impacts and Grant no. III 47014: The Role and Implementation of the National Spatial Plan and Regional Development Documents in Renewal of Strategic Research, Thinking and Governance in Serbia

  18. Merging Digital Surface Models Implementing Bayesian Approaches

    Science.gov (United States)

    Sadeq, H.; Drummond, J.; Li, Z.

    2016-06-01

    In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades). It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.

  19. MERGING DIGITAL SURFACE MODELS IMPLEMENTING BAYESIAN APPROACHES

    Directory of Open Access Journals (Sweden)

    H. Sadeq

    2016-06-01

    Full Text Available In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades. It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.

  20. Localization of a Vehicle: A Dynamic Interval Constraint Satisfaction Problem-Based Approach

    Directory of Open Access Journals (Sweden)

    Kangni Kueviakoe

    2018-01-01

    Full Text Available This paper introduces a new interval constraint propagation (ICP approach dealing with the real-time vehicle localization problem. Bayesian methods like extended Kalman filter (EKF are classically used to achieve vehicle localization. ICP is an alternative which provides guaranteed localization results rather than probabilities. Our approach assumes that all models and measurement errors are bounded within known limits without any other hypotheses on the probability distribution. The proposed algorithm uses a low-level consistency algorithm and has been validated with an outdoor vehicle equipped with a GPS receiver, a gyro, and odometers. Results have been compared to EKF and other ICP methods such as hull consistency (HC4 and 3-bound (3B algorithms. Both consistencies of EKF and our algorithm have been experimentally studied.

  1. A model-guided symbolic execution approach for network protocol implementations and vulnerability detection.

    Science.gov (United States)

    Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

    2017-01-01

    Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM) model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.

  2. Automatic generation of computable implementation guides from clinical information models.

    Science.gov (United States)

    Boscá, Diego; Maldonado, José Alberto; Moner, David; Robles, Montserrat

    2015-06-01

    Clinical information models are increasingly used to describe the contents of Electronic Health Records. Implementation guides are a common specification mechanism used to define such models. They contain, among other reference materials, all the constraints and rules that clinical information must obey. However, these implementation guides typically are oriented to human-readability, and thus cannot be processed by computers. As a consequence, they must be reinterpreted and transformed manually into an executable language such as Schematron or Object Constraint Language (OCL). This task can be difficult and error prone due to the big gap between both representations. The challenge is to develop a methodology for the specification of implementation guides in such a way that humans can read and understand easily and at the same time can be processed by computers. In this paper, we propose and describe a novel methodology that uses archetypes as basis for generation of implementation guides. We use archetypes to generate formal rules expressed in Natural Rule Language (NRL) and other reference materials usually included in implementation guides such as sample XML instances. We also generate Schematron rules from NRL rules to be used for the validation of data instances. We have implemented these methods in LinkEHR, an archetype editing platform, and exemplify our approach by generating NRL rules and implementation guides from EN ISO 13606, openEHR, and HL7 CDA archetypes. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Measuring the Acoustic Release of a Chemotherapeutic Agent from Folate-Targeted Polymeric Micelles.

    Science.gov (United States)

    Abusara, Ayah; Abdel-Hafez, Mamoun; Husseini, Ghaleb

    2018-08-01

    In this paper, we compare the use of Bayesian filters for the estimation of release and re-encapsulation rates of a chemotherapeutic agent (namely Doxorubicin) from nanocarriers in an acoustically activated drug release system. The study is implemented using an advanced kinetic model that takes into account cavitation events causing the antineoplastic agent's release from polymeric micelles upon exposure to ultrasound. This model is an improvement over the previous representations of acoustic release that used simple zero-, first- and second-order release and re-encapsulation kinetics to study acoustically triggered drug release from polymeric micelles. The new model incorporates drug release and micellar reassembly events caused by cavitation allowing for the controlled release of chemotherapeutics specially and temporally. Different Bayesian estimators are tested for this purpose including Kalman filters (KF), Extended Kalman filters (EKF), Particle filters (PF), and multi-model KF and EKF. Simulated and experimental results are used to verify the performance of the above-mentioned estimators. The proposed methods demonstrate the utility and high-accuracy of using estimation methods in modeling this drug delivery technique. The results show that, in both cases (linear and non-linear dynamics), the modeling errors are expensive but can be minimized using a multi-model approach. In addition, particle filters are more flexible filters that perform reasonably well compared to the other two filters. The study improved the accuracy of the kinetic models used to capture acoustically activated drug release from polymeric micelles, which may in turn help in designing hardware and software capable of precisely controlling the delivered amount of chemotherapeutics to cancerous tissue.

  4. A model-guided symbolic execution approach for network protocol implementations and vulnerability detection.

    Directory of Open Access Journals (Sweden)

    Shameng Wen

    Full Text Available Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.

  5. A new multidimensional model with text dimensions: definition and implementation

    Directory of Open Access Journals (Sweden)

    MariaJ. Martin-Bautista

    2013-02-01

    Full Text Available We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual data in the same way as the non-textual one in an automatic way, without user's intervention, so all the classical operations in the multidimensional model can been defined for this textual dimension. While most of the models dealing with texts that can be found in the literature are not implemented, in this proposal, the multidimensional model and the OLAP system have been implemented in a software tool, so it can be tested on real data. A case study with medical data is included in this work.

  6. Implementation of building information modeling in Malaysian construction industry

    Science.gov (United States)

    Memon, Aftab Hameed; Rahman, Ismail Abdul; Harman, Nur Melly Edora

    2014-10-01

    This study has assessed the implementation level of Building Information Modeling (BIM) in the construction industry of Malaysia. It also investigated several computer software packages facilitating BIM and challenges affecting its implementation. Data collection for this study was carried out using questionnaire survey among the construction practitioners. 95 completed forms of questionnaire received against 150 distributed questionnaire sets from consultant, contractor and client organizations were analyzed statistically. Analysis findings indicated that the level of implementation of BIM in the construction industry of Malaysia is very low. Average index method employed to assess the effectiveness of various software packages of BIM highlighted that Bentley construction, AutoCAD and ArchiCAD are three most popular and effective software packages. Major challenges to BIM implementation are it requires enhanced collaboration, add work to a designer, interoperability and needs enhanced collaboration. For improving the level of implementing BIM in Malaysian industry, it is recommended that a flexible training program of BIM for all practitioners must be created.

  7. MISCO: A Conceptual Model for MIS Implementation in SMEs

    Directory of Open Access Journals (Sweden)

    R.Bali

    1999-01-01

    Full Text Available Information Technology ('IT' has made a prolific impact, both in sociological and commercial terms. In the business world, the pursuit of new technology and working practices has often been at the expense of equal regard for the correct methods to manage the new technology. Contemporary IT techniques and methods include Management Information Systems ('MIS' which are normally implemented on a company-wide basis. However, MIS implementation has major cultural and organisational implications which will form the main focus of this paper. A conceptual model is proposed for successful MIS implementation which combines established research findings with ethnographically-informed data from a small, UK-based, business.

  8. Target Tracking in 3-D Using Estimation Based Nonlinear Control Laws for UAVs

    Directory of Open Access Journals (Sweden)

    Mousumi Ahmed

    2016-02-01

    Full Text Available This paper presents an estimation based backstepping like control law design for an Unmanned Aerial Vehicle (UAV to track a moving target in 3-D space. A ground-based sensor or an onboard seeker antenna provides range, azimuth angle, and elevation angle measurements to a chaser UAV that implements an extended Kalman filter (EKF to estimate the full state of the target. A nonlinear controller then utilizes this estimated target state and the chaser’s state to provide speed, flight path, and course/heading angle commands to the chaser UAV. Tracking performance with respect to measurement uncertainty is evaluated for three cases: (1 stationary white noise; (2 stationary colored noise and (3 non-stationary (range correlated white noise. Furthermore, in an effort to improve tracking performance, the measurement model is made more realistic by taking into consideration range-dependent uncertainties in the measurements, i.e., as the chaser closes in on the target, measurement uncertainties are reduced in the EKF, thus providing the UAV with more accurate control commands. Simulation results for these cases are shown to illustrate target state estimation and trajectory tracking performance.

  9. The Implementation of C-ID, R2D2 Model on Learning Reading Comprehension

    Science.gov (United States)

    Rayanto, Yudi Hari; Rusmawan, Putu Ngurah

    2016-01-01

    The purposes of this research are to find out, (1) whether C-ID, R2D2 model is effective to be implemented on learning Reading comprehension, (2) college students' activity during the implementation of C-ID, R2D2 model on learning Reading comprehension, and 3) college students' learning achievement during the implementation of C-ID, R2D2 model on…

  10. Can agent based models effectively reduce fisheries management implementation uncertainty?

    Science.gov (United States)

    Drexler, M.

    2016-02-01

    Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

  11. Data of evolutionary structure change: 1JMEB-3EKFA [Confc[Archive

    Lifescience Database Archive (English)

    Full Text Available 1JMEB-3EKFA 1JME 3EKF B A --KEMPQPKTFGELKNLPLLNTDKPVQALMKIADELGEI...e>PHE CA 283 GLN CA 245 3EKF ...A 3EKFA MNKLQRANQFQ HHGGG ...ax>11.26553726196289 1 3EKF... A 3EKFA NQFQE--KVMND

  12. A new extended H∞ filter for discrete nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    张永安; 周荻; 段广仁

    2004-01-01

    Nonlinear estimation problem is investigated in this paper. By extension of a linear H∞ estimation with corrector-predictor form to nonlinear cases, a new extended H∞ filter is proposed for time-varying discretetime nonlinear systems. The new filter has a simple observer structure based on a local linearization model, and can be viewed as a general case of the extended Kalman filter (EKF). An example demonstrates that the new filter with a suitable-chosen prescribed H∞ bound performs better than the EKF.

  13. Concurrent hyperthermia estimation schemes based on extended Kalman filtering and reduced-order modelling.

    Science.gov (United States)

    Potocki, J K; Tharp, H S

    1993-01-01

    The success of treating cancerous tissue with heat depends on the temperature elevation, the amount of tissue elevated to that temperature, and the length of time that the tissue temperature is elevated. In clinical situations the temperature of most of the treated tissue volume is unknown, because only a small number of temperature sensors can be inserted into the tissue. A state space model based on a finite difference approximation of the bioheat transfer equation (BHTE) is developed for identification purposes. A full-order extended Kalman filter (EKF) is designed to estimate both the unknown blood perfusion parameters and the temperature at unmeasured locations. Two reduced-order estimators are designed as computationally less intensive alternatives to the full-order EKF. Simulation results show that the success of the estimation scheme depends strongly on the number and location of the temperature sensors. Superior results occur when a temperature sensor exists in each unknown blood perfusion zone, and the number of sensors is at least as large as the number of unknown perfusion zones. Unacceptable results occur when there are more unknown perfusion parameters than temperature sensors, or when the sensors are placed in locations that do not sample the unknown perfusion information.

  14. Model-implementation fidelity in cyber physical system design

    CERN Document Server

    Fabre, Christian

    2017-01-01

    This book puts in focus various techniques for checking modeling fidelity of Cyber Physical Systems (CPS), with respect to the physical world they represent. The authors' present modeling and analysis techniques representing different communities, from very different angles, discuss their possible interactions, and discuss the commonalities and differences between their practices. Coverage includes model driven development, resource-driven development, statistical analysis, proofs of simulator implementation, compiler construction, power/temperature modeling of digital devices, high-level performance analysis, and code/device certification. Several industrial contexts are covered, including modeling of computing and communication, proof architectures models and statistical based validation techniques. Addresses CPS design problems such as cross-application interference, parsimonious modeling, and trustful code production Describes solutions, such as simulation for extra-functional properties, extension of cod...

  15. Weak Memory Models: Balancing Definitional Simplicity and Implementation Flexibility

    OpenAIRE

    Zhang, Sizhuo; Vijayaraghavan, Muralidaran; Arvind

    2017-01-01

    The memory model for RISC-V, a newly developed open source ISA, has not been finalized yet and thus, offers an opportunity to evaluate existing memory models. We believe RISC-V should not adopt the memory models of POWER or ARM, because their axiomatic and operational definitions are too complicated. We propose two new weak memory models: WMM and WMM-S, which balance definitional simplicity and implementation flexibility differently. Both allow all instruction reorderings except overtaking of...

  16. Determination of Paris' law constants and crack length evolution via Extended and Unscented Kalman filter: An application to aircraft fuselage panels

    Science.gov (United States)

    Wang, Yiwei; Binaud, Nicolas; Gogu, Christian; Bes, Christian; Fu, Jian

    2016-12-01

    Prediction of fatigue crack length in aircraft fuselage panels is one of the key issues for aircraft structural safety since it helps prevent catastrophic failures. Accurate estimation of crack length propagation is also meaningful for helping develop aircraft maintenance strategies. Paris' law is often used to capture the dynamics of fatigue crack propagation in metallic material. However, uncertainties are often present in the crack growth model, measured crack size and pressure differential in each flight and need to be accounted for accurate prediction. The aim of this paper is to estimate the two unknown Paris' law constants m and C as well as the crack length evolution by taking into account these uncertainties. Due to the nonlinear nature of the Paris' law, we propose here an on-line estimation algorithm based on two widespread nonlinear filtering techniques, Extended Kalman filter (EKF) and Unscented Kalman filter (UKF). The numerical experiments indicate that both EKF and UKF estimated the crack length well and accurately identified the unknown parameters. Although UKF is theoretical superior to EKF, in this Paris' law application EKF is comparable in accuracy to UKF and requires less computational expense.

  17. Implementations and interpretations of the talbot-ogden infiltration model

    KAUST Repository

    Seo, Mookwon

    2014-11-01

    The interaction between surface and subsurface hydrology flow systems is important for water supplies. Accurate, efficient numerical models are needed to estimate the movement of water through unsaturated soil. We investigate a water infiltration model and develop very fast serial and parallel implementations that are suitable for a computer with a graphical processing unit (GPU).

  18. Implementation and assessment of the renormalization group (Rng) k - ε model in gothic

    International Nuclear Information System (INIS)

    Analytis, G.Th.

    2001-01-01

    In GOTHIC, the standard k - ε model is used to model turbulence. In an attempt to enhance the turbulence modelling capabilities of the code for simulation of mixing driven by highly buoyant discharges, we implemented the Renormalization Group (RNG) k - ε model. This model which for the time being, is only implemented in the ''gas'' phase, was tested with different simple test-problems and its predictions were compared to the corresponding ones obtained when the standard k - ε model was used. (author)

  19. Model checking a cache coherence protocol for a Java DSM implementation

    NARCIS (Netherlands)

    J. Pang; W.J. Fokkink (Wan); R. Hofman (Rutger); R. Veldema

    2007-01-01

    textabstractJackal is a fine-grained distributed shared memory implementation of the Java programming language. It aims to implement Java's memory model and allows multithreaded Java programs to run unmodified on a distributed memory system. It employs a multiple-writer cache coherence

  20. Rhythmic Extended Kalman Filter for Gait Rehabilitation Motion Estimation and Segmentation.

    Science.gov (United States)

    Joukov, Vladimir; Bonnet, Vincent; Karg, Michelle; Venture, Gentiane; Kulic, Dana

    2018-02-01

    This paper proposes a method to enable the use of non-intrusive, small, wearable, and wireless sensors to estimate the pose of the lower body during gait and other periodic motions and to extract objective performance measures useful for physiotherapy. The Rhythmic Extended Kalman Filter (Rhythmic-EKF) algorithm is developed to estimate the pose, learn an individualized model of periodic movement over time, and use the learned model to improve pose estimation. The proposed approach learns a canonical dynamical system model of the movement during online observation, which is used to accurately model the acceleration during pose estimation. The canonical dynamical system models the motion as a periodic signal. The estimated phase and frequency of the motion also allow the proposed approach to segment the motion into repetitions and extract useful features, such as gait symmetry, step length, and mean joint movement and variance. The algorithm is shown to outperform the extended Kalman filter in simulation, on healthy participant data, and stroke patient data. For the healthy participant marching dataset, the Rhythmic-EKF improves joint acceleration and velocity estimates over regular EKF by 40% and 37%, respectively, estimates joint angles with 2.4° root mean squared error, and segments the motion into repetitions with 96% accuracy.

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

    Science.gov (United States)

    Trajanoski, Z; Wach, P

    1996-08-01

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

  2. Implementation of Dryden Continuous Turbulence Model into Simulink for LSA-02 Flight Test Simulation

    Science.gov (United States)

    Ichwanul Hakim, Teuku Mohd; Arifianto, Ony

    2018-04-01

    Turbulence is a movement of air on small scale in the atmosphere that caused by instabilities of pressure and temperature distribution. Turbulence model is integrated into flight mechanical model as an atmospheric disturbance. Common turbulence model used in flight mechanical model are Dryden and Von Karman model. In this minor research, only Dryden continuous turbulence model were made. Dryden continuous turbulence model has been implemented, it refers to the military specification MIL-HDBK-1797. The model was implemented into Matlab Simulink. The model will be integrated with flight mechanical model to observe response of the aircraft when it is flight through turbulence field. The turbulence model is characterized by multiplying the filter which are generated from power spectral density with band-limited Gaussian white noise input. In order to ensure that the model provide a good result, model verification has been done by comparing the implemented model with the similar model that is provided in aerospace blockset. The result shows that there are some difference for 2 linear velocities (vg and wg), and 3 angular rate (pg, qg and rg). The difference is instantly caused by different determination of turbulence scale length which is used in aerospace blockset. With the adjustment of turbulence length in the implemented model, both model result the similar output.

  3. Systematic model for lean product development implementation in an automotive related company

    Directory of Open Access Journals (Sweden)

    Daniel Osezua Aikhuele

    2017-07-01

    Full Text Available Lean product development is a major innovative business strategy that employs sets of practices to achieve an efficient, innovative and a sustainable product development. Despite the many benefits and high hopes in the lean strategy, many companies are still struggling, and unable to either achieve or sustain substantial positive results with their lean implementation efforts. However, as the first step towards addressing this issue, this paper seeks to propose a systematic model that considers the administrative and implementation limitations of lean thinking practices in the product development process. The model which is based on the integration of fuzzy Shannon’s entropy and Modified Technique for Order Preference by Similarity to the Ideal Solution (M-TOPSIS model for the lean product development practices implementation with respective to different criteria including management and leadership, financial capabilities, skills and expertise and organization culture, provides a guide or roadmap for product development managers on the lean implementation route.

  4. A model for implementing soundscape maps in smart cities

    Directory of Open Access Journals (Sweden)

    Kang Jian

    2018-04-01

    Full Text Available Smart cities are required to engage with local communities by promoting a user-centred approach to deal with urban life issues and ultimately enhance people’s quality of life. Soundscape promotes a similar approach, based on individuals’ perception of acoustic environments. This paper aims to establish a model to implement soundscape maps for the monitoring and management of the acoustic environment and to demonstrate its feasibility. The final objective of the model is to generate visual maps related to perceptual attributes (e.g. ‘calm’, ‘pleasant’, starting from audio recordings of everyday acoustic environments. The proposed model relies on three main stages: (1 sound sources recognition and profiling, (2 prediction of the soundscape’s perceptual attributes and (3 implementation of soundscape maps. This research particularly explores the two latter phases, for which a set of sub-processes and methods is proposed and discussed. An accuracy analysiswas performed with satisfactory results: the prediction models of the second stage explained up to the 57.5% of the attributes’ variance; the cross-validation errors of the model were close to zero. These findings show that the proposed model is likely to produce representative maps of an individual’s sonic perception in a given environment.

  5. Model checking a cache coherence protocol of a Java DSM implementation

    NARCIS (Netherlands)

    Pang, J.; Fokkink, W.J.; Hofman, R.; Veldema, R.S.

    2007-01-01

    Jackal is a fine-grained distributed shared memory implementation of the Java programming language. It aims to implement Java's memory model and allows multithreaded Java programs to run unmodified on a distributed memory system. It employs a multiple-writer cache coherence protocol. In this paper,

  6. eTOXlab, an open source modeling framework for implementing predictive models in production environments.

    Science.gov (United States)

    Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

    2015-01-01

    Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by e

  7. An extended Kalman filter with inequality constraints for real-time detection of intradialytic hypotension.

    Science.gov (United States)

    Ansari, Sardar; Molaei, Somayeh; Oldham, Kenn; Heung, Michael; Ward, Kevin R; Najarian, Kayvan

    2017-07-01

    Intradialytic hypotension (IDH) is the most common complication of hemodialysis, affecting 15-50% of all dialysis sessions. Previously, we had presented a non-invasive Polyvinylidene Fluoride (PVDF) based sensor in the form of a ring to measure vascular tone and we showed that the morphology of the signal can be utilized to predict IDH. This paper presents an approach for analyzing the PVDF signal using extended Kalman filter (EKF) and a synthetic model that has previously been used to model the ECG signal with Gaussian functions. Moreover, a novel approach for incorporating state inequality constraints into the EKF process using a gradient projection method is introduced. The taut string algorithm was first used to estimate the outline of the signal and remove it to highlight the reflection waves. Then, the EKF was used to characterize the morphology of the signal using Gaussian functions. The amplitudes of the Gaussian functions were used as features to train a classifier. The results indicated that the PPV and NPV for the prediction were 83.33% and 100%, respectively.

  8. Complete modeling and software implementation of a virtual solar hydrogen hybrid system

    International Nuclear Information System (INIS)

    Pedrazzi, S.; Zini, G.; Tartarini, P.

    2010-01-01

    A complete mathematical model and software implementation of a solar hydrogen hybrid system has been developed and applied to real data. The mathematical model has been derived from sub-models taken from literature with appropriate modifications and improvements. The model has been implemented as a stand-alone virtual energy system in a model-based, multi-domain software environment. A test run has then been performed on typical residential user data-sets over a year-long period. Results show that the virtual hybrid system can bring about complete grid independence; in particular, hydrogen production balance is positive (+1.25 kg) after a year's operation with a system efficiency of 7%.

  9. Design and Implementation of Linux Access Control Model

    Institute of Scientific and Technical Information of China (English)

    Wei Xiaomeng; Wu Yongbin; Zhuo Jingchuan; Wang Jianyun; Haliqian Mayibula

    2017-01-01

    In this paper,the design and implementation of an access control model for Linux system are discussed in detail. The design is based on the RBAC model and combines with the inherent characteristics of the Linux system,and the support for the process and role transition is added.The core idea of the model is that the file is divided into different categories,and access authority of every category is distributed to several roles.Then,roles are assigned to users of the system,and the role of the user can be transited from one to another by running the executable file.

  10. GASB's New Financial Reporting Model: Implementation Project for School Districts.

    Science.gov (United States)

    Bean, David; Glick, Paul

    1999-01-01

    In June 1999, the Governmental Accounting Standards Board (GASB) issued its statement on the structure of the basic financial reporting model for state and local governments. Explains the new financial reporting model and reviews the implementation issues that school districts will need to address. (MLF)

  11. A Model of Microteaching Lesson Study Implementation in the Prospective History Teacher Education

    Science.gov (United States)

    Utami, Indah Wahyu Puji; Mashuri; Nafi'ah, Ulfatun

    2016-01-01

    Microteaching lesson study is a model to improve prospective teacher quality by incorporating several element of microteaching and lesson study. This study concern on the implementation of microteaching lesson study in prospective history teacher education. Microteaching lesson study model implemented in this study consist of three stages: plan,…

  12. Numerical implementation of a transverse-isotropic inelastic, work-hardening constitutive model

    International Nuclear Information System (INIS)

    Baladi, G.Y.

    1977-01-01

    This paper documents the numerical implementation of a model, specifically a transverse-isotropic, inelastic, work-hardening constitutive model. A brief overview of the mathematical formulation of the model is presented to facilitate the understanding of its numerical implementation. The model is based on incremental flow theories for materials which have time- and temperature-independent properties and which are capable of undergoing small plastic as well as small elastic strain at each loading increment. In addition, the model is written in terms of 'pseudo' stress invariants so that the incremental anisotropic stress-strain relationship can be readily incorporated into existing finite-difference or finite-element computer codes. The isotropic version of the model is retrieved without any changes in the mathematical formulation or in the numerical implementation (algorithm) of the model. Various methods exist for incorporating inelastic constitutive models into computer programs. The method presented in this paper is appropriate for both finite-difference and finite-element codes, and is applicable for solving static as wall as dynamic problems. This method expresses the material constitutive properties as a matrix of coefficients, C (generalized tangent moduli), which relates incremental stresses to incremental strains. It possesses desirable convergence properties. In either finite-difference or finite-element applications the input quantities are the initial stress components, obtained at the end of the previous strain increment, and the new strain increments. The output quantities are the new values of the stress components

  13. On a model of three-dimensional bursting and its parallel implementation

    Science.gov (United States)

    Tabik, S.; Romero, L. F.; Garzón, E. M.; Ramos, J. I.

    2008-04-01

    A mathematical model for the simulation of three-dimensional bursting phenomena and its parallel implementation are presented. The model consists of four nonlinearly coupled partial differential equations that include fast and slow variables, and exhibits bursting in the absence of diffusion. The differential equations have been discretized by means of a second-order accurate in both space and time, linearly-implicit finite difference method in equally-spaced grids. The resulting system of linear algebraic equations at each time level has been solved by means of the Preconditioned Conjugate Gradient (PCG) method. Three different parallel implementations of the proposed mathematical model have been developed; two of these implementations, i.e., the MPI and the PETSc codes, are based on a message passing paradigm, while the third one, i.e., the OpenMP code, is based on a shared space address paradigm. These three implementations are evaluated on two current high performance parallel architectures, i.e., a dual-processor cluster and a Shared Distributed Memory (SDM) system. A novel representation of the results that emphasizes the most relevant factors that affect the performance of the paralled implementations, is proposed. The comparative analysis of the computational results shows that the MPI and the OpenMP implementations are about twice more efficient than the PETSc code on the SDM system. It is also shown that, for the conditions reported here, the nonlinear dynamics of the three-dimensional bursting phenomena exhibits three stages characterized by asynchronous, synchronous and then asynchronous oscillations, before a quiescent state is reached. It is also shown that the fast system reaches steady state in much less time than the slow variables.

  14. Implementing parallel spreadsheet models for health policy decisions: The impact of unintentional errors on model projections.

    Science.gov (United States)

    Bailey, Stephanie L; Bono, Rose S; Nash, Denis; Kimmel, April D

    2018-01-01

    Spreadsheet software is increasingly used to implement systems science models informing health policy decisions, both in academia and in practice where technical capacity may be limited. However, spreadsheet models are prone to unintentional errors that may not always be identified using standard error-checking techniques. Our objective was to illustrate, through a methodologic case study analysis, the impact of unintentional errors on model projections by implementing parallel model versions. We leveraged a real-world need to revise an existing spreadsheet model designed to inform HIV policy. We developed three parallel versions of a previously validated spreadsheet-based model; versions differed by the spreadsheet cell-referencing approach (named single cells; column/row references; named matrices). For each version, we implemented three model revisions (re-entry into care; guideline-concordant treatment initiation; immediate treatment initiation). After standard error-checking, we identified unintentional errors by comparing model output across the three versions. Concordant model output across all versions was considered error-free. We calculated the impact of unintentional errors as the percentage difference in model projections between model versions with and without unintentional errors, using +/-5% difference to define a material error. We identified 58 original and 4,331 propagated unintentional errors across all model versions and revisions. Over 40% (24/58) of original unintentional errors occurred in the column/row reference model version; most (23/24) were due to incorrect cell references. Overall, >20% of model spreadsheet cells had material unintentional errors. When examining error impact along the HIV care continuum, the percentage difference between versions with and without unintentional errors ranged from +3% to +16% (named single cells), +26% to +76% (column/row reference), and 0% (named matrices). Standard error-checking techniques may not

  15. Kalman filter implementation for small satellites using constraint GPS data

    Science.gov (United States)

    Wesam, Elmahy M.; Zhang, Xiang; Lu, Zhengliang; Liao, Wenhe

    2017-06-01

    Due to the increased need for autonomy, an Extended Kalman Filter (EKF) has been designed to autonomously estimate the orbit using GPS data. A propagation step models the satellite dynamics as a two body with J2 (second zonal effect) perturbations being suitable for orbits in altitudes higher than 600 km. An onboard GPS receiver provides continuous measurement inputs. The continuity of measurements decreases the errors of the orbit determination algorithm. Power restrictions are imposed on small satellites in general and nanosatellites in particular. In cubesats, the GPS is forced to be shut down most of the mission’s life time. GPS is turned on when experiments like atmospheric ones are carried out and meter level accuracy for positioning is required. This accuracy can’t be obtained by other autonomous sensors like magnetometer and sun sensor as they provide kilometer level accuracy. Through simulation using Matlab and satellite tool kit (STK) the position accuracy is analyzed after imposing constrained conditions suitable for small satellites and a very tight one suitable for nanosatellite missions.

  16. Implementation of an anisotropic mechanical model for shale in Geodyn

    Energy Technology Data Exchange (ETDEWEB)

    Attia, A; Vorobiev, O; Walsh, S

    2015-05-15

    The purpose of this report is to present the implementation of a shale model in the Geodyn code, based on published rock material models and properties that can help a petroleum engineer in his design of various strategies for oil/gas recovery from shale rock formation.

  17. FPGA-Based Real Time, Multichannel Emulated-Digital Retina Model Implementation

    Directory of Open Access Journals (Sweden)

    Zsolt Vörösházi

    2009-01-01

    Full Text Available The function of the low-level image processing that takes place in the biological retina is to compress only the relevant visual information to a manageable size. The behavior of the layers and different channels of the neuromorphic retina has been successfully modeled by cellular neural/nonlinear networks (CNNs. In this paper, we present an extended, application-specific emulated-digital CNN-universal machine (UM architecture to compute the complex dynamic of this mammalian retina in video real time. The proposed emulated-digital implementation of multichannel retina model is compared to the previously developed models from three key aspects, which are processing speed, number of physical cells, and accuracy. Our primary aim was to build up a simple, real-time test environment with camera input and display output in order to mimic the behavior of retina model implementation on emulated digital CNN by using low-cost, moderate-sized field-programmable gate array (FPGA architectures.

  18. Implementation of a model of emergency care in an Australian hospital.

    Science.gov (United States)

    Millichamp, Tracey; Bakon, Shannon; Christensen, Martin; Stock, Kate; Howarth, Sarah

    2017-11-10

    Emergency departments are characterised by a fast-paced, quick turnover and high acuity workload, therefore appropriate staffing is vital to ensure positive patient outcomes. Models of care are frameworks in which safe and effective patient-to-nurse ratios can be ensured. The aim of this study was to implement a supportive and transparent model of emergency nursing care that provides structure - regardless of nursing staff profile, business or other demands; improvement to nursing workloads; and promotes individual responsibility and accountability for patient care. A convergent parallel mixed-method approach was used. Quantitative data were analysed using descriptive statistics and the qualitative data used a thematic analysis to identify recurrent themes. Data post-implementation of the model of emergency nursing care indicate improved staff satisfaction in relation to workload, patient care and support structures. The development and implementation of a model of care in an emergency department improved staff workload and staff's perception of their ability to provide care. ©2017 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.

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

    Science.gov (United States)

    Liu, Xin; Niranjan, Mahesan

    2012-06-01

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

  20. Implementing inquiry-based kits within a professional development school model

    Science.gov (United States)

    Jones, Mark Thomas

    2005-07-01

    Implementation of guided inquiry teaching for the first time carries inherent problems for science teachers. Reform efforts on inquiry-based science teaching are often unsustainable and are not sensitive to teachers' needs and abilities as professionals. Professional development schools are meant to provide a research-based partnership between a public school and a university. These collaborations can provide support for the professional development of teachers. This dissertation reports a study focused on the implementation of inquiry-based science kits within the support of one of these collaborations. The researcher describes the difficulties and successful adaptations experienced by science teachers and how a coteaching model provided support. These types of data are needed in order to develop a bottom-up, sustainable process that will allow teachers to implement inquiry-based science. A qualitative methodology with "researcher as participant" was used in this study of two science teachers during 2002--2003. These two teachers were supported by a coteaching model, which included preservice teachers for each teacher as well as a supervising professor. Data were collected from the researcher's direct observations of coteachers' practice. Data were also collected from interviews and reflective pieces from the coteachers. Triangulation of the data on each teacher's case supported the validity of the findings. Case reports were prepared from these data for each classroom teacher. These case reports were used and cross-case analysis was conducted to search for major themes and findings in the study. Major findings described the hurdles teachers encounter, examples of adaptations observed in the teachers' cases and the supportive interactions with their coteachers while implementing the inquiry-based kits. In addition, the data were used to make recommendations for future training and use of the kits and the coteaching model. Results from this study showed that the

  1. Improved electromagnetic tracking for catheter path reconstruction with application in high-dose-rate brachytherapy.

    Science.gov (United States)

    Lugez, Elodie; Sadjadi, Hossein; Joshi, Chandra P; Akl, Selim G; Fichtinger, Gabor

    2017-04-01

    Electromagnetic (EM) catheter tracking has recently been introduced in order to enable prompt and uncomplicated reconstruction of catheter paths in various clinical interventions. However, EM tracking is prone to measurement errors which can compromise the outcome of the procedure. Minimizing catheter tracking errors is therefore paramount to improve the path reconstruction accuracy. An extended Kalman filter (EKF) was employed to combine the nonlinear kinematic model of an EM sensor inside the catheter, with both its position and orientation measurements. The formulation of the kinematic model was based on the nonholonomic motion constraints of the EM sensor inside the catheter. Experimental verification was carried out in a clinical HDR suite. Ten catheters were inserted with mean curvatures varying from 0 to [Formula: see text] in a phantom. A miniaturized Ascension (Burlington, Vermont, USA) trakSTAR EM sensor (model 55) was threaded within each catheter at various speeds ranging from 7.4 to [Formula: see text]. The nonholonomic EKF was applied on the tracking data in order to statistically improve the EM tracking accuracy. A sample reconstruction error was defined at each point as the Euclidean distance between the estimated EM measurement and its corresponding ground truth. A path reconstruction accuracy was defined as the root mean square of the sample reconstruction errors, while the path reconstruction precision was defined as the standard deviation of these sample reconstruction errors. The impacts of sensor velocity and path curvature on the nonholonomic EKF method were determined. Finally, the nonholonomic EKF catheter path reconstructions were compared with the reconstructions provided by the manufacturer's filters under default settings, namely the AC wide notch and the DC adaptive filter. With a path reconstruction accuracy of 1.9 mm, the nonholonomic EKF surpassed the performance of the manufacturer's filters (2.4 mm) by 21% and the raw EM

  2. IT Security Management Implementation Model in Iranian Bank Industry

    Directory of Open Access Journals (Sweden)

    Mona Vanaki

    2017-06-01

    Full Text Available According to the complexity and differences between Iranian banks and other developed countries the appropriate actions to implement effective security management of information technology have not been taken. The aim of this study was to create a powerful model by selecting the appropriate security controls to protect information assets in the bank. In this model, at first the principle set fort in ISO standard 27001, was extracted and then by further studies derived from best practices carried out in the world on the related subject from 2008 to 2016 using a qualitative descriptive method, points comply with information security management in the banking industry were added to it. With the study of Iranian banks in dealing with IT security management system and with help of action research tools, provisions which prevent the actual implementation of this standard was removed and finally a conceptual model with operating instructions and considering all the principles of information security management standard, as well as banking institutions focusing on the characteristics of Iran was proposed.

  3. VISIONS2 Learning for Life Initiative. Workplace Literacy Implementation Model.

    Science.gov (United States)

    Walsh, Chris L.; Ferguson, Susan E.; Taylor, Mary Lou

    This document presents a model for implementing workplace literacy education that focuses on giving front-line workers or first-line workers basic skills instruction and an appreciation for lifelong learning. The introduction presents background information on the model, which was developed during a partnership between a technical college and an…

  4. Changing practice to support self-management and recovery in mental illness: application of an implementation model.

    Science.gov (United States)

    Harris, Melanie; Jones, Phil; Heartfield, Marie; Allstrom, Mary; Hancock, Janette; Lawn, Sharon; Battersby, Malcolm

    2015-01-01

    Health services introducing practice changes need effective implementation methods. Within the setting of a community mental health service offering recovery-oriented psychosocial support for people with mental illness, we aimed to: (i) identify a well-founded implementation model; and (ii) assess its practical usefulness in introducing a new programme for recovery-oriented self-management support. We reviewed the literature to identify implementation models applicable to community mental health organisations, and that also had corresponding measurement tools. We used one of these models to inform organisational change strategies. The literature review showed few models with corresponding tools. The Promoting Action on Research Implementation in Health Services (PARIHS) model and the related Organisational Readiness to Change Assessment (ORCA) tool were used. The PARIHS proposes prerequisites for health service change and the ORCA measures the extent to which these prerequisites are present. Application of the ORCA at two time points during implementation of the new programme showed strategy-related gains for some prerequisites but not for others, reflecting observed implementation progress. Additional strategies to address target prerequisites could be drawn from the PARIHS model. The PARIHS model and ORCA tool have potential in designing and monitoring practice change strategies in community mental health organisations. Further practical use and testing of implementation models appears justified in overcoming barriers to change.

  5. Model-based dispersive wave processing: A recursive Bayesian solution

    International Nuclear Information System (INIS)

    Candy, J.V.; Chambers, D.H.

    1999-01-01

    Wave propagation through dispersive media represents a significant problem in many acoustic applications, especially in ocean acoustics, seismology, and nondestructive evaluation. In this paper we propose a propagation model that can easily represent many classes of dispersive waves and proceed to develop the model-based solution to the wave processing problem. It is shown that the underlying wave system is nonlinear and time-variable requiring a recursive processor. Thus the general solution to the model-based dispersive wave enhancement problem is developed using a Bayesian maximum a posteriori (MAP) approach and shown to lead to the recursive, nonlinear extended Kalman filter (EKF) processor. The problem of internal wave estimation is cast within this framework. The specific processor is developed and applied to data synthesized by a sophisticated simulator demonstrating the feasibility of this approach. copyright 1999 Acoustical Society of America.

  6. Interpersonal success factors for strategy implementation: a case study using group model building

    OpenAIRE

    Rodney J Scott; Robert Y Cavana; Donald Cameron

    2015-01-01

    Strategy implementation has been identified as an area of system dynamics literature requiring greater attention. Most strategies fail to be implemented successfully, and processes for effectively implementing strategy are yet to be fully explained and explored. The reported interpersonal success factors for strategy implementation are reported outcomes for group model building, suggesting potential applicability. A case study using validated survey methods yielded promising results, and sugg...

  7. Implementation of angular response function modeling in SPECT simulations with GATE

    International Nuclear Information System (INIS)

    Descourt, P; Visvikis, D; Carlier, T; Bardies, M; Du, Y; Song, X; Frey, E C; Tsui, B M W; Buvat, I

    2010-01-01

    Among Monte Carlo simulation codes in medical imaging, the GATE simulation platform is widely used today given its flexibility and accuracy, despite long run times, which in SPECT simulations are mostly spent in tracking photons through the collimators. In this work, a tabulated model of the collimator/detector response was implemented within the GATE framework to significantly reduce the simulation times in SPECT. This implementation uses the angular response function (ARF) model. The performance of the implemented ARF approach has been compared to standard SPECT GATE simulations in terms of the ARF tables' accuracy, overall SPECT system performance and run times. Considering the simulation of the Siemens Symbia T SPECT system using high-energy collimators, differences of less than 1% were measured between the ARF-based and the standard GATE-based simulations, while considering the same noise level in the projections, acceleration factors of up to 180 were obtained when simulating a planar 364 keV source seen with the same SPECT system. The ARF-based and the standard GATE simulation results also agreed very well when considering a four-head SPECT simulation of a realistic Jaszczak phantom filled with iodine-131, with a resulting acceleration factor of 100. In conclusion, the implementation of an ARF-based model of collimator/detector response for SPECT simulations within GATE significantly reduces the simulation run times without compromising accuracy. (note)

  8. Implementation of angular response function modeling in SPECT simulations with GATE

    Energy Technology Data Exchange (ETDEWEB)

    Descourt, P; Visvikis, D [INSERM, U650, LaTIM, IFR SclnBioS, Universite de Brest, CHU Brest, Brest, F-29200 (France); Carlier, T; Bardies, M [CRCNA INSERM U892, Nantes (France); Du, Y; Song, X; Frey, E C; Tsui, B M W [Department of Radiology, J Hopkins University, Baltimore, MD (United States); Buvat, I, E-mail: dimitris@univ-brest.f [IMNC-UMR 8165 CNRS Universites Paris 7 et Paris 11, Orsay (France)

    2010-05-07

    Among Monte Carlo simulation codes in medical imaging, the GATE simulation platform is widely used today given its flexibility and accuracy, despite long run times, which in SPECT simulations are mostly spent in tracking photons through the collimators. In this work, a tabulated model of the collimator/detector response was implemented within the GATE framework to significantly reduce the simulation times in SPECT. This implementation uses the angular response function (ARF) model. The performance of the implemented ARF approach has been compared to standard SPECT GATE simulations in terms of the ARF tables' accuracy, overall SPECT system performance and run times. Considering the simulation of the Siemens Symbia T SPECT system using high-energy collimators, differences of less than 1% were measured between the ARF-based and the standard GATE-based simulations, while considering the same noise level in the projections, acceleration factors of up to 180 were obtained when simulating a planar 364 keV source seen with the same SPECT system. The ARF-based and the standard GATE simulation results also agreed very well when considering a four-head SPECT simulation of a realistic Jaszczak phantom filled with iodine-131, with a resulting acceleration factor of 100. In conclusion, the implementation of an ARF-based model of collimator/detector response for SPECT simulations within GATE significantly reduces the simulation run times without compromising accuracy. (note)

  9. State estimation of chemical engineering systems tending to multiple solutions

    Directory of Open Access Journals (Sweden)

    N. P. G. Salau

    2014-09-01

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

  10. A FPGA Implementation of the CAR-FAC Cochlear Model

    Directory of Open Access Journals (Sweden)

    Ying Xu

    2018-04-01

    Full Text Available This paper presents a digital implementation of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC cochlear model. The CAR part simulates the basilar membrane's (BM response to sound. The FAC part models the outer hair cell (OHC, the inner hair cell (IHC, and the medial olivocochlear efferent system functions. The FAC feeds back to the CAR by moving the poles and zeros of the CAR resonators automatically. We have implemented a 70-section, 44.1 kHz sampling rate CAR-FAC system on an Altera Cyclone V Field Programmable Gate Array (FPGA with 18% ALM utilization by using time-multiplexing and pipeline parallelizing techniques and present measurement results here. The fully digital reconfigurable CAR-FAC system is stable, scalable, easy to use, and provides an excellent input stage to more complex machine hearing tasks such as sound localization, sound segregation, speech recognition, and so on.

  11. A FPGA Implementation of the CAR-FAC Cochlear Model.

    Science.gov (United States)

    Xu, Ying; Thakur, Chetan S; Singh, Ram K; Hamilton, Tara Julia; Wang, Runchun M; van Schaik, André

    2018-01-01

    This paper presents a digital implementation of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. The CAR part simulates the basilar membrane's (BM) response to sound. The FAC part models the outer hair cell (OHC), the inner hair cell (IHC), and the medial olivocochlear efferent system functions. The FAC feeds back to the CAR by moving the poles and zeros of the CAR resonators automatically. We have implemented a 70-section, 44.1 kHz sampling rate CAR-FAC system on an Altera Cyclone V Field Programmable Gate Array (FPGA) with 18% ALM utilization by using time-multiplexing and pipeline parallelizing techniques and present measurement results here. The fully digital reconfigurable CAR-FAC system is stable, scalable, easy to use, and provides an excellent input stage to more complex machine hearing tasks such as sound localization, sound segregation, speech recognition, and so on.

  12. Implementing the correlated fermi gas nuclear model for quasielastic neutrino-nucleus scattering

    Science.gov (United States)

    Tockstein, Jameson

    2017-09-01

    When studying neutrino oscillations an understanding of charged current quasielastic (CCQE) neutrino-nucleus scattering is imperative. This interaction depends on a nuclear model as well as knowledge of form factors. Neutrino experiments, such as MiniBooNE, often use the Relativistic Fermi Gas (RFG) nuclear model. Recently, the Correlated Fermi Gas (CFG) nuclear model was suggested in, based on inclusive and exclusive scattering experiments at JLab. We implement the CFG model for CCQE scattering. In particular, we provide analytic expressions for this implementation that can be used to analyze current and future neutrino CCQE data. This project was supported through the Wayne State University REU program under NSF Grant PHY-1460853 and by the DOE Grant DE-SC0007983.

  13. Numerical implementation of a transverse-isotropic inelastic, work-hardening constitutive model

    International Nuclear Information System (INIS)

    Baladi, G.Y.

    1977-01-01

    During the past few decades the dramatic growth of computer technology has been paralleled by an increasing degree of complexity in material constitutive modeling. This paper documents the numerical implementation of one of these models, specifically a transverse-isotropic, inelastic, work-hardening constitutive model which is developed elsewhere by the author. (Auth.)

  14. An Approach for the Implementation of Software Quality Models Adpoting CERTICS and CMMI-DEV

    Directory of Open Access Journals (Sweden)

    GARCIA, F.W.

    2015-12-01

    Full Text Available This paper proposes a mapping between two product quality and software processes models used in the industry, the CERTICS national model and the CMMI-DEV international model. The stages of mapping are presented step by step, as well as the mapping review, which had the cooperation of one specialist in CERTICS and CMMI-DEV models. It aims to correlate the structures of the two models in order to facilitate and reduce the implementation time and costs, and to stimulate the execution of multi-model implementations in software developers companies.

  15. A Model Of The Underlying Philosophy And Criteria For Effective Implementation Of Performance Management

    Directory of Open Access Journals (Sweden)

    C. M. Whitford

    2006-11-01

    Full Text Available The objective of this study was to develop a model that assists organisations in implementing performance management effectively. A model describing the philosophical paradigm underpinning best practice in performance management and the criteria for effective implementation of performance management was developed. The sample used in this study was a convenience sample of 615 employees. Exploratory factor analysis revealed three reliable philosophical dimensions. Moderate correlations were found between the three dimensions and some of the implementation criteria.

  16. Implementation of an Online Chemistry Model to a Large Eddy Simulation Model (PALM-4U0

    Science.gov (United States)

    Mauder, M.; Khan, B.; Forkel, R.; Banzhaf, S.; Russo, E. E.; Sühring, M.; Kanani-Sühring, F.; Raasch, S.; Ketelsen, K.

    2017-12-01

    Large Eddy Simulation (LES) models permit to resolve relevant scales of turbulent motion, so that these models can capture the inherent unsteadiness of atmospheric turbulence. However, LES models are so far hardly applied for urban air quality studies, in particular chemical transformation of pollutants. In this context, BMBF (Bundesministerium für Bildung und Forschung) funded a joint project, MOSAIK (Modellbasierte Stadtplanung und Anwendung im Klimawandel / Model-based city planning and application in climate change) with the main goal to develop a new highly efficient urban climate model (UCM) that also includes atmospheric chemical processes. The state-of-the-art LES model PALM; Maronga et al, 2015, Geosci. Model Dev., 8, doi:10.5194/gmd-8-2515-2015), has been used as a core model for the new UCM named as PALM-4U. For the gas phase chemistry, a fully coupled 'online' chemistry model has been implemented into PALM. The latest version of the Kinetic PreProcessor (KPP) Version 2.3, has been utilized for the numerical integration of chemical species. Due to the high computational demands of the LES model, compromises in the description of chemical processes are required. Therefore, a reduced chemistry mechanism, which includes only major pollutants namely O3, NO, NO2, CO, a highly simplified VOC chemistry and a small number of products have been implemented. This work shows preliminary results of the advection, and chemical transformation of atmospheric pollutants. Non-cyclic boundaries have been used for inflow and outflow in east-west directions while periodic boundary conditions have been implemented to the south-north lateral boundaries. For practical applications, our approach is to go beyond the simulation of single street canyons to chemical transformation, advection and deposition of air pollutants in the larger urban canopy. Tests of chemistry schemes and initial studies of chemistry-turbulence, transport and transformations are presented.

  17. Modeling and implementing a database on drugs into a hospital intranet.

    Science.gov (United States)

    François, M; Joubert, M; Fieschi, D; Fieschi, M

    1998-09-01

    Our objective was to develop a drug information service, implementing a database on drugs in our university hospitals information system. Thériaque is a database, maintained by a group of pharmacists and physicians, on all the drugs available in France. Before its implementation we modeled its content (chemical classes, active components, excipients, indications, contra-indications, side effects, and so on) according to an object-oriented method. Then we designed HTML pages whose appearance translates the structure of classes of objects of the model. Fields in pages are dynamically fulfilled by the results of queries to a relational database in which information on drugs is stored. This allowed a fast implementation and did not imply to port a client application on the thousands of workstations over the network. The interface provides end-users with an easy-to-use and natural way to access information related to drugs in an internet environment.

  18. TESLA cavity modeling and digital implementation in FPGA technology for control system development

    International Nuclear Information System (INIS)

    Czarski, T.; Pozniak, K.T.; Romaniuk, R.S.; Simrock, S.

    2006-01-01

    The electromechanical model of the TESLA cavity has been implemented in FPGA technology for real-time testing of the control system. The model includes Lorentz force detuning and beam loading effects. Step operation and vector stimulus operation modes are applied for the evaluation of a FPGA cavity simulator operated by a digital controller. The performance of the cavity hardware model is verified by comparing with a software model of the cavity implemented in the MATLAB system. The numerical aspects are considered for an optimal DSP calculation. Some experimental results are presented for different cavity operational conditions. (orig.)

  19. Real-time prediction of respiratory motion using a cascade structure of an extended Kalman filter and support vector regression

    International Nuclear Information System (INIS)

    Hong, S-M; Bukhari, W

    2014-01-01

    The motion of thoracic and abdominal tumours induced by respiratory motion often exceeds 20 mm, and can significantly compromise dose conformality. Motion-adaptive radiotherapy aims to deliver a conformal dose distribution to the tumour with minimal normal tissue exposure by compensating for the tumour motion. This adaptive radiotherapy, however, requires the prediction of the tumour movement that can occur over the system latency period. In general, motion prediction approaches can be classified into two groups: model-based and model-free. Model-based approaches utilize a motion model in predicting respiratory motion. These approaches are computationally efficient and responsive to irregular changes in respiratory motion. Model-free approaches do not assume an explicit model of motion dynamics, and predict future positions by learning from previous observations. Artificial neural networks (ANNs) and support vector regression (SVR) are examples of model-free approaches. In this article, we present a prediction algorithm that combines a model-based and a model-free approach in a cascade structure. The algorithm, which we call EKF–SVR, first employs a model-based algorithm (named LCM–EKF) to predict the respiratory motion, and then uses a model-free SVR algorithm to estimate and correct the error of the LCM–EKF prediction. Extensive numerical experiments based on a large database of 304 respiratory motion traces are performed. The experimental results demonstrate that the EKF–SVR algorithm successfully reduces the prediction error of the LCM–EKF, and outperforms the model-free ANN and SVR algorithms in terms of prediction accuracy across lookahead lengths of 192, 384, and 576 ms. (paper)

  20. Gaussian particle filter based pose and motion estimation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

  1. Group Coaching on Pre-School Teachers' Implementation of Pyramid Model Strategies: A Program Description

    Science.gov (United States)

    Fettig, Angel; Artman-Meeker, Kathleen

    2016-01-01

    The purpose of this article was to describe a group coaching model and present preliminary evidence of its impact on teachers' implementation of Pyramid Model practices. In particular, we described coaching strategies used to support teachers in reflecting and problem solving on the implementation of the evidence-based strategies. Preliminary…

  2. Exploring the Process of Implementing Healthy Workplace Initiatives: Mapping to Kotter's Leading Change Model.

    Science.gov (United States)

    Chappell, Stacie; Pescud, Melanie; Waterworth, Pippa; Shilton, Trevor; Roche, Dee; Ledger, Melissa; Slevin, Terry; Rosenberg, Michael

    2016-10-01

    The aim of this study was to use Kotter's leading change model to explore the implementation of workplace health and wellbeing initiatives. Qualitative interviews were conducted with 31 workplace representatives with a healthy workplace initiative. None of the workplaces used a formal change management model when implementing their healthy workplace initiatives. Not all of the steps in Kotter model were considered necessary and the order of the steps was challenged. For example, interviewees perceived that communicating the vision, developing the vision, and creating a guiding coalition were integral parts of the process, although there was less emphasis on the importance of creating a sense of urgency and consolidating change. Although none of the workplaces reported using a formal organizational change model when implementing their healthy workplace initiatives, there did appear to be perceived merit in using the steps in Kotter's model.

  3. A comparative study of sensor fault diagnosis methods based on observer for ECAS system

    Science.gov (United States)

    Xu, Xing; Wang, Wei; Zou, Nannan; Chen, Long; Cui, Xiaoli

    2017-03-01

    The performance and practicality of electronically controlled air suspension (ECAS) system are highly dependent on the state information supplied by kinds of sensors, but faults of sensors occur frequently. Based on a non-linearized 3-DOF 1/4 vehicle model, different methods of fault detection and isolation (FDI) are used to diagnose the sensor faults for ECAS system. The considered approaches include an extended Kalman filter (EKF) with concise algorithm, a strong tracking filter (STF) with robust tracking ability, and the cubature Kalman filter (CKF) with numerical precision. We propose three filters of EKF, STF, and CKF to design a state observer of ECAS system under typical sensor faults and noise. Results show that three approaches can successfully detect and isolate faults respectively despite of the existence of environmental noise, FDI time delay and fault sensitivity of different algorithms are different, meanwhile, compared with EKF and STF, CKF method has best performing FDI of sensor faults for ECAS system.

  4. Teachers' Knowledge Base for Implementing Response-to-Intervention Models in Reading

    Science.gov (United States)

    Spear-Swerling, Louise; Cheesman, Elaine

    2012-01-01

    This study examined the knowledge base of 142 elementary-level educators for implementing response-to-intervention (RTI) models in reading. A questionnaire assessed participants' professional background for teaching reading, as well as their familiarity with specific assessments, research-based instructional models, and interventions potentially…

  5. A system dynamics evaluation model: implementation of health information exchange for public health reporting.

    Science.gov (United States)

    Merrill, Jacqueline A; Deegan, Michael; Wilson, Rosalind V; Kaushal, Rainu; Fredericks, Kimberly

    2013-06-01

    To evaluate the complex dynamics involved in implementing electronic health information exchange (HIE) for public health reporting at a state health department, and to identify policy implications to inform similar implementations. Qualitative data were collected over 8 months from seven experts at New York State Department of Health who implemented web services and protocols for querying, receipt, and validation of electronic data supplied by regional health information organizations. Extensive project documentation was also collected. During group meetings experts described the implementation process and created reference modes and causal diagrams that the evaluation team used to build a preliminary model. System dynamics modeling techniques were applied iteratively to build causal loop diagrams representing the implementation. The diagrams were validated iteratively by individual experts followed by group review online, and through confirmatory review of documents and artifacts. Three casual loop diagrams captured well-recognized system dynamics: Sliding Goals, Project Rework, and Maturity of Resources. The findings were associated with specific policies that address funding, leadership, ensuring expertise, planning for rework, communication, and timeline management. This evaluation illustrates the value of a qualitative approach to system dynamics modeling. As a tool for strategic thinking on complicated and intense processes, qualitative models can be produced with fewer resources than a full simulation, yet still provide insights that are timely and relevant. System dynamics techniques clarified endogenous and exogenous factors at play in a highly complex technology implementation, which may inform other states engaged in implementing HIE supported by federal Health Information Technology for Economic and Clinical Health (HITECH) legislation.

  6. Benchmark problems for numerical implementations of phase field models

    International Nuclear Information System (INIS)

    Jokisaari, A. M.; Voorhees, P. W.; Guyer, J. E.; Warren, J.; Heinonen, O. G.

    2016-01-01

    Here, we present the first set of benchmark problems for phase field models that are being developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST). While many scientific research areas use a limited set of well-established software, the growing phase field community continues to develop a wide variety of codes and lacks benchmark problems to consistently evaluate the numerical performance of new implementations. Phase field modeling has become significantly more popular as computational power has increased and is now becoming mainstream, driving the need for benchmark problems to validate and verify new implementations. We follow the example set by the micromagnetics community to develop an evolving set of benchmark problems that test the usability, computational resources, numerical capabilities and physical scope of phase field simulation codes. In this paper, we propose two benchmark problems that cover the physics of solute diffusion and growth and coarsening of a second phase via a simple spinodal decomposition model and a more complex Ostwald ripening model. We demonstrate the utility of benchmark problems by comparing the results of simulations performed with two different adaptive time stepping techniques, and we discuss the needs of future benchmark problems. The development of benchmark problems will enable the results of quantitative phase field models to be confidently incorporated into integrated computational materials science and engineering (ICME), an important goal of the Materials Genome Initiative.

  7. Implementation of a parallel version of a regional climate model

    Energy Technology Data Exchange (ETDEWEB)

    Gerstengarbe, F.W. [ed.; Kuecken, M. [Potsdam-Institut fuer Klimafolgenforschung (PIK), Potsdam (Germany); Schaettler, U. [Deutscher Wetterdienst, Offenbach am Main (Germany). Geschaeftsbereich Forschung und Entwicklung

    1997-10-01

    A regional climate model developed by the Max Planck Institute for Meterology and the German Climate Computing Centre in Hamburg based on the `Europa` and `Deutschland` models of the German Weather Service has been parallelized and implemented on the IBM RS/6000 SP computer system of the Potsdam Institute for Climate Impact Research including parallel input/output processing, the explicit Eulerian time-step, the semi-implicit corrections, the normal-mode initialization and the physical parameterizations of the German Weather Service. The implementation utilizes Fortran 90 and the Message Passing Interface. The parallelization strategy used is a 2D domain decomposition. This report describes the parallelization strategy, the parallel I/O organization, the influence of different domain decomposition approaches for static and dynamic load imbalances and first numerical results. (orig.)

  8. A state-space-based prognostics model for lithium-ion battery degradation

    International Nuclear Information System (INIS)

    Xu, Xin; Chen, Nan

    2017-01-01

    This paper proposes to analyze the degradation of lithium-ion batteries with the sequentially observed discharging profiles. A general state-space model is developed in which the observation model is used to approximate the discharging profile of each cycle, the corresponding parameter vector is treated as the hidden state, and the state-transition model is used to track the evolution of the parameter vector as the battery ages. The EM and EKF algorithms are adopted to estimate and update the model parameters and states jointly. Based on this model, we construct prediction on the end of discharge times for unobserved cycles and the remaining useful cycles before the battery failure. The effectiveness of the proposed model is demonstrated using a real lithium-ion battery degradation data set. - Highlights: • Unifying model for Li-Ion battery SOC and SOH estimation. • Extended Kalman filter based efficient inference algorithm. • Using voltage curves in discharging to have wide validity.

  9. Implementation of draft IEC Generic Model of Type 1 Wind Turbine Generator in PowerFactory and Simulink

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Sørensen, Poul Ejnar

    2013-01-01

    This paper presents the implementation work of IEC generic model of Type 1 wind turbine generator (WTG) in two commercial simulation tools: DIgSILENT PowerFactory (PF) and Matlab Simulink. The model topology, details of the composite blocks and implementation procedure in PF and Simulink environm......This paper presents the implementation work of IEC generic model of Type 1 wind turbine generator (WTG) in two commercial simulation tools: DIgSILENT PowerFactory (PF) and Matlab Simulink. The model topology, details of the composite blocks and implementation procedure in PF and Simulink...

  10. The implementation of a mid-loop model for Doel 1/2 training simulator

    International Nuclear Information System (INIS)

    Houte, U. Van; Damme, M. Van

    1999-01-01

    To cope with upgrade requirements of the Full Scope training simulator of Doel 1/2 (Belgium), a 5-equation model has been implemented for mid-loop operation training. This model will permit to simulate the following conditions: (a) Normal operating conditions; Draining of the primary circuit at vacuum conditions; Venting of the primary loop with the help of a vacuum pump; Filling-up of the primely circuit, (2) Incident and Accident conditions; Loss of RHR (Cavitation of RHR pumps); Reactor heat-up and boiling. In order to simulate the pressurizer water hold-up and loss of steam generator reflux cooling, flooding correlations are used predicting steam generator U-tube and pressurizer surgeline flooding. Loss of horizontal stratification in the hot leg has been taken into account. A steam generator piston model for heat transfer has been implemented. This paper describes the mid-loop model specifications, its implementation and testing in the simulator environment. Special attention is given on how the model has been integrated within the existing simulator. (author)

  11. New developments in state estimation for Nonlinear Systems

    DEFF Research Database (Denmark)

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

    2000-01-01

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

  12. Business models for implementing geospatial technologies in transportation decision-making

    Science.gov (United States)

    2007-03-31

    This report describes six State DOTs business models for implementing geospatial technologies. It provides a comparison of the organizational factors influencing how Arizona DOT, Delaware DOT, Georgia DOT, Montana DOT, North Carolina DOT, and Okla...

  13. Development, implementation and quality assurance of biokinetic models within CONRAD

    International Nuclear Information System (INIS)

    Nosske, D.; Birchall, A.; Blanchardon, E.; Breustedt, B.; Giussani, A.; Luciani, A.; Oeh, U.; Lopez, M. A.

    2008-01-01

    The work of the Task Group 5.2 'Research Studies on Biokinetic Models' of the CONRAD project is presented. New biokinetic models have been implemented by several European institutions. Quality assurance procedures included intercomparison of the results as well as quality assurance of model formulation. Additionally, the use of the models was examined leading to proposals of tuning parameters. Stable isotope studies were evaluated with respect to their implications to the new models, and new biokinetic models were proposed on the basis of their results. Furthermore, the development of a biokinetic model describing the effects of decorporation of actinides by diethylenetriaminepentaacetic acid treatment was initiated. (authors)

  14. SLHAplus: A library for implementing extensions of the standard model

    Science.gov (United States)

    Bélanger, G.; Christensen, Neil D.; Pukhov, A.; Semenov, A.

    2011-03-01

    We provide a library to facilitate the implementation of new models in codes such as matrix element and event generators or codes for computing dark matter observables. The library contains an SLHA reader routine as well as diagonalisation routines. This library is available in CalcHEP and micrOMEGAs. The implementation of models based on this library is supported by LanHEP and FeynRules. Program summaryProgram title: SLHAplus_1.3 Catalogue identifier: AEHX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 6283 No. of bytes in distributed program, including test data, etc.: 52 119 Distribution format: tar.gz Programming language: C Computer: IBM PC, MAC Operating system: UNIX (Linux, Darwin, Cygwin) RAM: 2000 MB Classification: 11.1 Nature of problem: Implementation of extensions of the standard model in matrix element and event generators and codes for dark matter observables. Solution method: For generic extensions of the standard model we provide routines for reading files that adopt the standard format of the SUSY Les Houches Accord (SLHA) file. The procedure has been generalized to take into account an arbitrary number of blocks so that the reader can be used in generic models including non-supersymmetric ones. The library also contains routines to diagonalize real and complex mass matrices with either unitary or bi-unitary transformations as well as routines for evaluating the running strong coupling constant, running quark masses and effective quark masses. Running time: 0.001 sec

  15. An anisotropic elastoplasticity model implemented in FLAG

    Energy Technology Data Exchange (ETDEWEB)

    Buechler, Miles Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Canfield, Thomas R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-10-12

    Many metals, including Tantalum and Zirconium, exhibit anisotropic elastoplastic behavior at the single crystal level, and if components are manufactured from these metals through forming processes the polycrystal (component) may also exhibit anisotropic elastoplastic behavior. This is because the forming can induce a preferential orientation of the crystals in the polycrystal. One example is a rolled plate of Uranium where the sti /strong orientation of the crystal (c-axis) tends to align itself perpendicular to the rolling direction. If loads are applied to this plate in di erent orientations the sti ness as well as the ow strength of the material will be greater in the through thickness direction than in other directions. To better accommodate simulations of such materials, an anisotropic elastoplasticity model has been implemented in FLAG. The model includes an anisotropic elastic stress model as well as an anisotropic plasticity model. The model could represent single crystals of any symmetry, though it should not be confused with a high- delity crystal plasticity model with multiple slip planes and evolutions. The model is most appropriate for homogenized polycrystalline materials. Elastic rotation of the material due to deformation is captured, so the anisotropic models are appropriate for arbitrary large rotations, but currently they do not account for signi cant change in material texture beyond the elastic rotation of the entire polycrystal.

  16. 6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features.

    Science.gov (United States)

    Ye, Cang; Hong, Soonhac; Tamjidi, Amirhossein

    2015-10-01

    This paper presents a 6-DOF Pose Estimation (PE) method for a Robotic Navigation Aid (RNA) for the visually impaired. The RNA uses a single 3D camera for PE and object detection. The proposed method processes the camera's intensity and range data to estimates the camera's egomotion that is then used by an Extended Kalman Filter (EKF) as the motion model to track a set of visual features for PE. A RANSAC process is employed in the EKF to identify inliers from the visual feature correspondences between two image frames. Only the inliers are used to update the EKF's state. The EKF integrates the egomotion into the camera's pose in the world coordinate system. To retain the EKF's consistency, the distance between the camera and the floor plane (extracted from the range data) is used by the EKF as the observation of the camera's z coordinate. Experimental results demonstrate that the proposed method results in accurate pose estimates for positioning the RNA in indoor environments. Based on the PE method, a wayfinding system is developed for localization of the RNA in a home environment. The system uses the estimated pose and the floorplan to locate the RNA user in the home environment and announces the points of interest and navigational commands to the user through a speech interface. This work was motivated by the limitations of the existing navigation technology for the visually impaired. Most of the existing methods use a point/line measurement sensor for indoor object detection. Therefore, they lack capability in detecting 3D objects and positioning a blind traveler. Stereovision has been used in recent research. However, it cannot provide reliable depth data for object detection. Also, it tends to produce a lower localization accuracy because its depth measurement error quadratically increases with the true distance. This paper suggests a new approach for navigating a blind traveler. The method uses a single 3D time-of-flight camera for both 6-DOF PE and 3D object

  17. A financing model to solve financial barriers for implementing green building projects.

    Science.gov (United States)

    Lee, Sanghyo; Lee, Baekrae; Kim, Juhyung; Kim, Jaejun

    2013-01-01

    Along with the growing interest in greenhouse gas reduction, the effect of greenhouse gas energy reduction from implementing green buildings is gaining attention. The government of the Republic of Korea has set green growth as its paradigm for national development, and there is a growing interest in energy saving for green buildings. However, green buildings may have financial barriers that have high initial construction costs and uncertainties about future project value. Under the circumstances, governmental support to attract private funding is necessary to implement green building projects. The objective of this study is to suggest a financing model for facilitating green building projects with a governmental guarantee based on Certified Emission Reduction (CER). In this model, the government provides a guarantee for the increased costs of a green building project in return for CER. And this study presents the validation of the model as well as feasibility for implementing green building project. In addition, the suggested model assumed governmental guarantees for the increased cost, but private guarantees seem to be feasible as well because of the promising value of the guarantee from CER. To do this, certification of Clean Development Mechanisms (CDMs) for green buildings must be obtained.

  18. Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise.

    Science.gov (United States)

    Vuković, Najdan; Miljković, Zoran

    2015-03-01

    Feedforward neural networks (FFNN) are among the most used neural networks for modeling of various nonlinear problems in engineering. In sequential and especially real time processing all neural networks models fail when faced with outliers. Outliers are found across a wide range of engineering problems. Recent research results in the field have shown that to avoid overfitting or divergence of the model, new approach is needed especially if FFNN is to run sequentially or in real time. To accommodate limitations of FFNN when training data contains a certain number of outliers, this paper presents new learning algorithm based on improvement of conventional extended Kalman filter (EKF). Extended Kalman filter robust to outliers (EKF-OR) is probabilistic generative model in which measurement noise covariance is not constant; the sequence of noise measurement covariance is modeled as stochastic process over the set of symmetric positive-definite matrices in which prior is modeled as inverse Wishart distribution. In each iteration EKF-OR simultaneously estimates noise estimates and current best estimate of FFNN parameters. Bayesian framework enables one to mathematically derive expressions, while analytical intractability of the Bayes' update step is solved by using structured variational approximation. All mathematical expressions in the paper are derived using the first principles. Extensive experimental study shows that FFNN trained with developed learning algorithm, achieves low prediction error and good generalization quality regardless of outliers' presence in training data. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

    Directory of Open Access Journals (Sweden)

    Fernando A. Auat Cheein

    2013-01-01

    Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

  20. Implementation of IEC Generic Models of Type 1 Wind Turbine Generator in DIgSILENT PowerFactory

    Institute of Scientific and Technical Information of China (English)

    Haoran ZHAO; Qiuwei WU; Ioannis MARGARIS; Poul S(O)RENSEN

    2013-01-01

    The implementation method for the International Electrotechnical Commission (IEC) generic models of Type 1 wind turbine generator (WTG) in DIgSILENT PowerFactory is presented.The following items are described,i.e.model structure,model blocks and how to implement these blocks in the PowerFactory environment.Case studies under both normal and fault conditions are done with the implemented IEC generic models of Type 1 WTG,and dynamic responses are captured and analyzed.The case study results show that the IEC generic models of Type 1 WTG can correctly represent the performances of Type 1 WTG under both normal and fault conditions.

  1. Experimental investigation of extended Kalman Filter combined with carrier phase recovery for 16-QAM system

    Science.gov (United States)

    Shu, Tong; Li, Yan; Yu, Miao; Zhang, Yifan; Zhou, Honghang; Qiu, Jifang; Guo, Hongxiang; Hong, Xiaobin; Wu, Jian

    2018-02-01

    Performance of Extended Kalman Filter combined with the Viterbi-Viterbi phase estimation (VVPE-EKF) for joint phase noise mitigation and amplitude noise equalization is experimental demonstrated. Experimental results show that, for 11.2 Gbaud SP-16-QAM, the proposed VVPE-EKF achieves 0.9 dB required OSNR reduction at bit error ratio (BER) of 3.8e-3 compared to the VVPE. The result of maximum likelihood combined with VVPE (VVPE-ML) is only 0.3 dB. For 28 GBaud SP-16-QAM signal, VVPE-EKF achieves 3 dB required OSNR reduction at BER=3.8e-3 (7% HD-FEC threshold) compared to VVPE. And VVPE-ML can reduce the required OSNR for 1.7 dB compared to the VVPE. VVPE-EKF outperforms DD-EKF 3.7 dB and 0.7 dB for 11.2 GBaud and 28 GBaud system, respectively.

  2. 3-D model-based vehicle tracking.

    Science.gov (United States)

    Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

    2005-10-01

    This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  4. Kalman filter based data fusion for neutral axis tracking in wind turbine towers

    DEFF Research Database (Denmark)

    Soman, Rohan; Malinowski, Pawel; Ostachowicz, Wieslaw

    2015-01-01

    downtime, hence increasing the availability of the system. The present work is based on the use of neutral axis (NA) for SHM of the structure. The NA is tracked by data fusion of measured yaw angle and strain through the use of Extended Kalman Filter (EKF). The EKF allows accurate tracking even...... in the NA position may be used for detecting and locating the damage. The wind turbine tower has been modelled with FE software ABAQUS and validated on data from load measurements carried out on the 34m high tower of the Nordtank, NTK 500/41 wind turbine....

  5. Guidelines for a graph-theoretic implementation of structural equation modeling

    Science.gov (United States)

    Grace, James B.; Schoolmaster, Donald R.; Guntenspergen, Glenn R.; Little, Amanda M.; Mitchell, Brian R.; Miller, Kathryn M.; Schweiger, E. William

    2012-01-01

    Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for

  6. OpenSHMEM-UCX : Evaluation of UCX for implementing OpenSHMEM Programming Model

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Matthew B [ORNL; Gorentla Venkata, Manjunath [ORNL; Aderholdt, William Ferrol [ORNL; Shamis, Pavel [ARM Research

    2016-01-01

    The OpenSHMEM reference implementation was developed towards the goal of developing an open source and high-performing Open- SHMEM implementation. To achieve portability and performance across various networks, the OpenSHMEM reference implementation uses GAS- Net and UCCS for network operations. Recently, new network layers have emerged with the promise of providing high-performance, scalabil- ity, and portability for HPC applications. In this paper, we implement the OpenSHMEM reference implementation to use the UCX framework for network operations. Then, we evaluate its performance and scalabil- ity on Cray XK systems to understand UCX s suitability for developing the OpenSHMEM programming model. Further, we develop a bench- mark called SHOMS for evaluating the OpenSHMEM implementation. Our experimental results show that OpenSHMEM-UCX outperforms the vendor supplied OpenSHMEM implementation in most cases on the Cray XK system by up to 40% with respect to message rate and up to 70% for the execution of application kernels.

  7. Implementation of IEC Generic Model of Type 1 Wind Turbine Generator in DIgSILENT PowerFactory

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Margaris, Ioannis

    2013-01-01

    The implementation method for the International Electrotechnical Commission (IEC) generic models of Type 1 wind turbine generator (WTG) in DIgSILENT PowerFactory is presented. The following items are described, i.e. model structure, model blocks and how to implement these blocks in the PowerFactory...

  8. Design and implementation of a generalized laboratory data model

    Directory of Open Access Journals (Sweden)

    Nhan Mike

    2007-09-01

    Full Text Available Abstract Background Investigators in the biological sciences continue to exploit laboratory automation methods and have dramatically increased the rates at which they can generate data. In many environments, the methods themselves also evolve in a rapid and fluid manner. These observations point to the importance of robust information management systems in the modern laboratory. Designing and implementing such systems is non-trivial and it appears that in many cases a database project ultimately proves unserviceable. Results We describe a general modeling framework for laboratory data and its implementation as an information management system. The model utilizes several abstraction techniques, focusing especially on the concepts of inheritance and meta-data. Traditional approaches commingle event-oriented data with regular entity data in ad hoc ways. Instead, we define distinct regular entity and event schemas, but fully integrate these via a standardized interface. The design allows straightforward definition of a "processing pipeline" as a sequence of events, obviating the need for separate workflow management systems. A layer above the event-oriented schema integrates events into a workflow by defining "processing directives", which act as automated project managers of items in the system. Directives can be added or modified in an almost trivial fashion, i.e., without the need for schema modification or re-certification of applications. Association between regular entities and events is managed via simple "many-to-many" relationships. We describe the programming interface, as well as techniques for handling input/output, process control, and state transitions. Conclusion The implementation described here has served as the Washington University Genome Sequencing Center's primary information system for several years. It handles all transactions underlying a throughput rate of about 9 million sequencing reactions of various kinds per month and

  9. The Implementation of Vendor Managed Inventory In the Supply Chain with Simple Probabilistic Inventory Model

    Directory of Open Access Journals (Sweden)

    Anna Ika Deefi

    2016-01-01

    Full Text Available Numerous studies show that the implementation of Vendor Managed Inventory (VMI benefits all members of the supply chain. This research develops model to prove the benefits obtained from implementing VMI to supplier-buyer partnership analytically. The model considers a two-level supply chain which consists of a single supplier and a single buyer. The analytical model is developed to supply chain inventory with probabilistic demand which follows normal distribution. The model also incorporates lead time as a decision variable and investigates the impacts of inventory management before and after the implementation of the VMI. The result shows that the analytical model has the ability to reduce the supply chain expected cost, improve the service level and increase the inventory replenishment. Numerical examples are given to prove them.

  10. Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

    Directory of Open Access Journals (Sweden)

    Fábio Engel de Camargo

    2012-11-01

    Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

  11. Implementation of Dynamic Smart Decision Model for Vertical Handoff

    Science.gov (United States)

    Sahni, Nidhi

    2010-11-01

    International Mobile Telecommunications-Advanced (IMT Advanced), better known as 4G is the next level of evolution in the field of wireless communications. 4G Wireless networks enable users to access information anywhere, anytime, with a seamless connection to a wide range of information and services, and receiving a large volume of information, data, pictures, video and thus increasing the demand for High Bandwidth and Signal Strength. The mobility among various networks is achieved through Vertical Handoff. Vertical handoffs refer to the automatic failover from one technology to another in order to maintain communication. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the "best" available network at "best" time for handoff. In this paper, we implemented the proposed Dynamic and Smart Decision model to decide the "best" network interface and "best" time moment to handoff. The proposed model implementation not only demonstrates the individual user needs but also improve the whole system performance i.e. Quality of Service by reducing the unnecessary handoffs and maintain mobility.

  12. Decentralized identification of nonlinear structure under strong ground motion using the extended Kalman filter and unscented Kalman filter

    Science.gov (United States)

    Tao, Dongwang; Li, Hui; Ma, Qiang

    2016-04-01

    Complete structure identification of complicate nonlinear system using extend Kalman filter (EKF) or unscented Kalman filter (UKF) may have the problems of divergence, huge computation and low estimation precision due to the large dimension of the extended state space for the system. In this article, a decentralized identification method of hysteretic system based on the joint EKF and UKF is proposed. The complete structure is divided into linear substructures and nonlinear substructures. The substructures are identified from the top to the bottom. For the linear substructure, EKF is used to identify the extended space including the displacements, velocities, stiffness and damping coefficients of the substructures, using the limited absolute accelerations and the identified interface force above the substructure. Similarly, for the nonlinear substructure, UKF is used to identify the extended space including the displacements, velocities, stiffness, damping coefficients and control parameters for the hysteretic Bouc-Wen model and the force at the interface of substructures. Finally a 10-story shear-type structure with multiple inter-story hysteresis is used for numerical simulation and is identified using the decentralized approach, and the identified results are compared with those using only EKF or UKF for the complete structure identification. The results show that the decentralized approach has the advantage of more stability, relative less computation and higher estimation precision.

  13. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    Science.gov (United States)

    Ma, Jian; Lu, Chen; Liu, Hongmei

    2015-01-01

    The aircraft environmental control system (ECS) is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF) and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF) and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger.

  14. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    Directory of Open Access Journals (Sweden)

    Jian Ma

    Full Text Available The aircraft environmental control system (ECS is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger.

  15. Implementing the WebSocket Protocol Based on Formal Modelling and Automated Code Generation

    DEFF Research Database (Denmark)

    Simonsen, Kent Inge; Kristensen, Lars Michael

    2014-01-01

    with pragmatic annotations for automated code generation of protocol software. The contribution of this paper is an application of the approach as implemented in the PetriCode tool to obtain protocol software implementing the IETF WebSocket protocol. This demonstrates the scalability of our approach to real...... protocols. Furthermore, we perform formal verification of the CPN model prior to code generation, and test the implementation for interoperability against the Autobahn WebSocket test-suite resulting in 97% and 99% success rate for the client and server implementation, respectively. The tests show...

  16. [Modeling and implementation method for the automatic biochemistry analyzer control system].

    Science.gov (United States)

    Wang, Dong; Ge, Wan-cheng; Song, Chun-lin; Wang, Yun-guang

    2009-03-01

    In this paper the system structure The automatic biochemistry analyzer is a necessary instrument for clinical diagnostics. First of is analyzed. The system problems description and the fundamental principles for dispatch are brought forward. Then this text puts emphasis on the modeling for the automatic biochemistry analyzer control system. The objects model and the communications model are put forward. Finally, the implementation method is designed. It indicates that the system based on the model has good performance.

  17. A Financing Model to Solve Financial Barriers for Implementing Green Building Projects

    Science.gov (United States)

    Lee, Baekrae; Kim, Juhyung; Kim, Jaejun

    2013-01-01

    Along with the growing interest in greenhouse gas reduction, the effect of greenhouse gas energy reduction from implementing green buildings is gaining attention. The government of the Republic of Korea has set green growth as its paradigm for national development, and there is a growing interest in energy saving for green buildings. However, green buildings may have financial barriers that have high initial construction costs and uncertainties about future project value. Under the circumstances, governmental support to attract private funding is necessary to implement green building projects. The objective of this study is to suggest a financing model for facilitating green building projects with a governmental guarantee based on Certified Emission Reduction (CER). In this model, the government provides a guarantee for the increased costs of a green building project in return for CER. And this study presents the validation of the model as well as feasibility for implementing green building project. In addition, the suggested model assumed governmental guarantees for the increased cost, but private guarantees seem to be feasible as well because of the promising value of the guarantee from CER. To do this, certification of Clean Development Mechanisms (CDMs) for green buildings must be obtained. PMID:24376379

  18. Implementation of a cost-accounting model in a biobank: practical implications.

    Science.gov (United States)

    Gonzalez-Sanchez, Maria Beatriz; Lopez-Valeiras, Ernesto; García-Montero, Andres C

    2014-01-01

    Given the state of global economy, cost measurement and control have become increasingly relevant over the past years. The scarcity of resources and the need to use these resources more efficiently is making cost information essential in management, even in non-profit public institutions. Biobanks are no exception. However, no empirical experiences on the implementation of cost accounting in biobanks have been published to date. The aim of this paper is to present a step-by-step implementation of a cost-accounting tool for the main production and distribution activities of a real/active biobank, including a comprehensive explanation on how to perform the calculations carried out in this model. Two mathematical models for the analysis of (1) production costs and (2) request costs (order management and sample distribution) have stemmed from the analysis of the results of this implementation, and different theoretical scenarios have been prepared. Global analysis and discussion provides valuable information for internal biobank management and even for strategic decisions at the research and development governmental policies level.

  19. Modeling antecedents of electronic medical record system implementation success in low-resource setting hospitals.

    Science.gov (United States)

    Tilahun, Binyam; Fritz, Fleur

    2015-08-01

    With the increasing implementation of Electronic Medical Record Systems (EMR) in developing countries, there is a growing need to identify antecedents of EMR success to measure and predict the level of adoption before costly implementation. However, less evidence is available about EMR success in the context of low-resource setting implementations. Therefore, this study aims to fill this gap by examining the constructs and relationships of the widely used DeLone and MacLean (D&M) information system success model to determine whether it can be applied to measure EMR success in those settings. A quantitative cross sectional study design using self-administered questionnaires was used to collect data from 384 health professionals working in five governmental hospitals in Ethiopia. The hospitals use a comprehensive EMR system since three years. Descriptive and structural equation modeling methods were applied to describe and validate the extent of relationship of constructs and mediating effects. The findings of the structural equation modeling shows that system quality has significant influence on EMR use (β = 0.32, P quality has significant influence on EMR use (β = 0.44, P service quality has strong significant influence on EMR use (β = 0.36, P effect of EMR use on user satisfaction was not significant. Both EMR use and user satisfaction have significant influence on perceived net-benefit (β = 0.31, P mediating factor in the relationship between service quality and EMR use (P effect on perceived net-benefit of health professionals. EMR implementers and managers in developing countries are in urgent need of implementation models to design proper implementation strategies. In this study, the constructs and relationships depicted in the updated D&M model were found to be applicable to assess the success of EMR in low resource settings. Additionally, computer literacy was found to be a mediating factor in EMR use and user satisfaction of

  20. Precision and accuracy of blood glucose measurements using three different instruments.

    Science.gov (United States)

    Nowotny, B; Nowotny, P J; Strassburger, K; Roden, M

    2012-02-01

    Assessment of insulin sensitivity by dynamic metabolic tests such as the hyperinsulinemic euglycemic clamp critically relies on the reproducible and fast measurement of blood glucose concentrations. Although various instruments have been developed over the last decades, little is known as to the accuracy and comparability. We therefore compared the best new instrument with the former gold standard instruments to measure glucose concentrations in metabolic tests. Fasting blood samples of 15 diabetic and 10 healthy subjects were collected into sodium-fluoride tubes, spiked with glucose (0, 2.8, 6.9 and 11.1 mmol/l) and measured either as whole blood (range 3.3-26.3 mmol/l) or following centrifugation as plasma (range 3.9-32.0 mmol/l). Plasma samples were analyzed in the YSI-2300 STAT plus (YSI), EKF Biosen C-Line (EKF) and the reference method, Beckman Glucose analyzer-II (BMG), whole blood samples in EKF instruments with YSI as reference method. The average deviation of the EKF from the reference, BMG, was 3.0 ± 3.5% without any concentration-dependent variability. Glucose measurements by YSI were in good agreement with that by BMG (plasma) and EKF (plasma and whole blood) up to concentrations of 13.13 mmol/l (0.5 ± 3.7%), but deviation increased to -6.2 ± 3.8% at higher concentrations. Precision (n = 6) was ±2.2% (YSI), ±3.9% (EKF) and ±5.2% (BMG). The EKF instrument is comparable regarding accuracy and precision to the reference method BMG and can be used in metabolic tests, while the YSI showed a systematic shift at higher glucose concentrations. Based on these results we decided to replace BMG with EKF instrument in metabolic tests. © 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK.

  1. Correlation between the model accuracy and model-based SOC estimation

    International Nuclear Information System (INIS)

    Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

    2017-01-01

    State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

  2. Implementation of Electrical Simulation Model for IEC Standard Type-3A Generator

    DEFF Research Database (Denmark)

    Subramanian, Chandrasekaran; Casadei, Domenico; Tani, Angelo

    2013-01-01

    This paper describes the implementation of electrical simulation model for IEC 61400-27-1 standard Type-3A generator. A general overview of the different wind electric generators(WEG) types are given and the main focused on Type-3A WEG standard models, namely a model for a variable speed wind tur...

  3. Progress in implementation of the neutronics model of HEXTRAN into APROS

    International Nuclear Information System (INIS)

    Rintala, J.

    2009-01-01

    A new three-dimensional nodal model for neutronics calculation is currently under implementation into APROS - Advanced PROcess Simulation environment - to conform the increasing accuracy requirements. The new model is based on an advanced nodal code HEXTRAN and its static version HEXBU-3D by VTT, Technical Research Centre of Finland. However, several improvements for the model are made and the whole model has been reprogrammed. They don't change the theory basement of the method, but rather makes the implementation more flexible. Currently the computational part of the program is ready and current work concentrates on testing and validation. User interface details and usability issues need also work in the future. In this paper, general information about the improvements of the theory is explained first. Then the latest validation results are given. Currently the dynamical characteristics are tested by calculating the AER's kinetic benchmarks for VVER-440 reactors. In this paper, the results for the first benchmark are shown for two version of the code. The first version is fully HEXTRAN-comparable code to test that the basic structure works as wanted. The second version is the actual improved model for APROS. (author)

  4. Progress in implementation of the neutronics model of HEXTRAN into APROS

    International Nuclear Information System (INIS)

    Jukka Rintala

    2009-01-01

    A new three-dimensional nodal model for neutronics calculation is currently under implementation into APROS - Advanced PROcess Simulation environment - to conform the increasing accuracy requirements. The new model is based on an advanced nodal code HEXTRAN and its static version HEXBU-3D by VTT, Technical Research Centre of Finland. However, several improvements for the model are made and the whole model has been reprogrammed. They don't change the theory basement of the method, but rather makes the implementation more flexible. Currently the computational part of the program is ready and current work concentrates on testing and validation. User interface details and usability issues need also work in the future. In this paper, general information about the improvements of the theory is explained first. Then the latest validation results are given. Currently the dynamical characteristics are tested by calculating the atomic energy research's kinetic benchmarks for WWER-440 reactors. In this paper, the results for the first benchmark are shown for two version of the code. The first version is fully HEXTRAN-comparable code to test that the basic structure works as wanted. The second version is the actual improved model for APROS. (Authors)

  5. Tracking single dynamic MEG dipole sources using the projected Extended Kalman Filter.

    Science.gov (United States)

    Yao, Yuchen; Swindlehurst, A Lee

    2011-01-01

    This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

  6. Multi-dimensional boron transport modeling in subchannel approach: Part I. Model selection, implementation and verification of COBRA-TF boron tracking model

    Energy Technology Data Exchange (ETDEWEB)

    Ozdemir, Ozkan Emre, E-mail: ozdemir@psu.edu [Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA 16802 (United States); Avramova, Maria N., E-mail: mna109@psu.edu [Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA 16802 (United States); Sato, Kenya, E-mail: kenya_sato@mhi.co.jp [Mitsubishi Heavy Industries (MHI), Kobe (Japan)

    2014-10-15

    Highlights: ► Implementation of multidimensional boron transport model in a subchannel approach. ► Studies on cross flow mechanism, heat transfer and lateral pressure drop effects. ► Verification of the implemented model via code-to-code comparison with CFD code. - Abstract: The risk of reflux condensation especially during a Small Break Loss Of Coolant Accident (SB-LOCA) and the complications of tracking the boron concentration experimentally inside the primary coolant system have stimulated and subsequently have been a focus of many computational studies on boron tracking simulations in nuclear reactors. This paper presents the development and implementation of a multidimensional boron transport model with Modified Godunov Scheme within a thermal-hydraulic code based on a subchannel approach. The cross flow mechanism in multiple-subchannel rod bundle geometry as well as the heat transfer and lateral pressure drop effects are considered in the performed studies on simulations of deboration and boration cases. The Pennsylvania State University (PSU) version of the COBRA-TF (CTF) code was chosen for the implementation of three different boron tracking models: First Order Accurate Upwind Difference Scheme, Second Order Accurate Godunov Scheme, and Modified Godunov Scheme. Based on the performed nodalization sensitivity studies, the Modified Godunov Scheme approach with a physical diffusion term was determined to provide the best solution in terms of precision and accuracy. As a part of the verification and validation activities, a code-to-code comparison was carried out with the STAR-CD computational fluid dynamics (CFD) code and presented here. The objective of this study was two-fold: (1) to verify the accuracy of the newly developed CTF boron tracking model against CFD calculations; and (2) to investigate its numerical advantages as compared to other thermal-hydraulics codes.

  7. Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

    Science.gov (United States)

    Breckenridge, Jonathan T.; Johnson, Stephen B.

    2013-01-01

    Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions.

  8. Microseismic Full Waveform Modeling in Anisotropic Media with Moment Tensor Implementation

    Science.gov (United States)

    Shi, Peidong; Angus, Doug; Nowacki, Andy; Yuan, Sanyi; Wang, Yanyan

    2018-03-01

    Seismic anisotropy which is common in shale and fractured rocks will cause travel-time and amplitude discrepancy in different propagation directions. For microseismic monitoring which is often implemented in shale or fractured rocks, seismic anisotropy needs to be carefully accounted for in source location and mechanism determination. We have developed an efficient finite-difference full waveform modeling tool with an arbitrary moment tensor source. The modeling tool is suitable for simulating wave propagation in anisotropic media for microseismic monitoring. As both dislocation and non-double-couple source are often observed in microseismic monitoring, an arbitrary moment tensor source is implemented in our forward modeling tool. The increments of shear stress are equally distributed on the staggered grid to implement an accurate and symmetric moment tensor source. Our modeling tool provides an efficient way to obtain the Green's function in anisotropic media, which is the key of anisotropic moment tensor inversion and source mechanism characterization in microseismic monitoring. In our research, wavefields in anisotropic media have been carefully simulated and analyzed in both surface array and downhole array. The variation characteristics of travel-time and amplitude of direct P- and S-wave in vertical transverse isotropic media and horizontal transverse isotropic media are distinct, thus providing a feasible way to distinguish and identify the anisotropic type of the subsurface. Analyzing the travel-times and amplitudes of the microseismic data is a feasible way to estimate the orientation and density of the induced cracks in hydraulic fracturing. Our anisotropic modeling tool can be used to generate and analyze microseismic full wavefield with full moment tensor source in anisotropic media, which can help promote the anisotropic interpretation and inversion of field data.

  9. Information sharing model in supporting implementation of e-procurement service: Case of Bandung city

    Science.gov (United States)

    Ramantoko, Gadang; Irawan, Herry

    2017-10-01

    This research examines the factors influencing the Information Sharing Model in Supporting Implementation of e-Procurement Services: Case of Bandung City in its early maturity stage. The early maturity of information sharing stage was determined using e-Government Maturity Stage Conceptual Framework from Estevez. Bandung City e-Procurement Information Sharing system was categorized at stage 1 in Estevez' model where the concern was mainly on assessing the benefit and risk of implementing the system. The Authors were using DeLone & McLean (D&M) Information System Success model to study benefit and risk of implementing the system in Bandung city. The model was then empirically tested by employing survey data that was collected from the available 40 listed supplier firms. D&M's model adjusted by Klischewski's description was introducing Information Quality, System Quality, and Service Quality as independent variable; Usability and User Satisfaction as intermediate dependent variable; and Perceived Net Benefit as final dependent variable. The findings suggested that, all of the predictors in D&M's model significantly influenced the net perceived benefit of implementing the e-Procurement system in the early maturity stage. The theoretical contribution of this research suggested that D&M's model might find useful in modeling complex information technology successfulness such as the one used in e-Procurement service. This research could also have implications for policy makers (LPSE) and system providers (LKPP) following the introduction of the service. However, the small number of respondent might be considered limitation of the study. The model needs to be further tested using larger number of respondents by involving the population of the firms in extended boundary/municipality area around Bandung.

  10. Tuberculosis active case finding in Cambodia: a pragmatic, cost-effectiveness comparison of three implementation models.

    Science.gov (United States)

    James, Richard; Khim, Keovathanak; Boudarene, Lydia; Yoong, Joanne; Phalla, Chea; Saint, Saly; Koeut, Pichenda; Mao, Tan Eang; Coker, Richard; Khan, Mishal Sameer

    2017-08-22

    Globally, almost 40% of tuberculosis (TB) patients remain undiagnosed, and those that are diagnosed often experience prolonged delays before initiating correct treatment, leading to ongoing transmission. While there is a push for active case finding (ACF) to improve early detection and treatment of TB, there is extremely limited evidence about the relative cost-effectiveness of different ACF implementation models. Cambodia presents a unique opportunity for addressing this gap in evidence as ACF has been implemented using different models, but no comparisons have been conducted. The objective of our study is to contribute to knowledge and methodology on comparing cost-effectiveness of alternative ACF implementation models from the health service perspective, using programmatic data, in order to inform national policy and practice. We retrospectively compared three distinct ACF implementation models - door to door symptom screening in urban slums, checking contacts of TB patients, and door to door symptom screening focusing on rural populations aged above 55 - in terms of the number of new bacteriologically-positive pulmonary TB cases diagnosed and the cost of implementation assuming activities are conducted by the national TB program of Cambodia. We calculated the cost per additional case detected using the alternative ACF models. Our analysis, which is the first of its kind for TB, revealed that the ACF model based on door to door screening in poor urban areas of Phnom Penh was the most cost-effective (249 USD per case detected, 737 cases diagnosed), followed by the model based on testing contacts of TB patients (308 USD per case detected, 807 cases diagnosed), and symptomatic screening of older rural populations (316 USD per case detected, 397 cases diagnosed). Our study provides new evidence on the relative effectiveness and economics of three implementation models for enhanced TB case finding, in line with calls for data from 'routine conditions' to be included

  11. Air-to-Air Missile Vector Scoring

    Science.gov (United States)

    2012-03-22

    SIR sampling-importance resampling . . . . . . . . . . . . . . 53 EPF extended particle filter . . . . . . . . . . . . . . . . . . . . 54 UPF unscented...particle filter ( EPF ) or a unscented particle fil- ter (UPF) [20]. The basic concept is to apply a bank of N EKF or UKF filters to move particles from...Merwe, Doucet, Freitas and Wan provide a comprehensive discussion on the EPF and UPF, including algorithms for implementation [20]. 2Result based on

  12. The AAM-API: An Open Source Active Appearance Model Implementation

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2003-01-01

    This paper presents a public domain implementation of the Active Appearance Model framework and gives examples using it for segmentation and analysis of medical images. The software is open source, designed with efficiency in mind, and has been thoroughly tested and evaluated in several medical...

  13. Autonomous Navigation with Constrained Consistency for C-Ranger

    Directory of Open Access Journals (Sweden)

    Shujing Zhang

    2014-06-01

    Full Text Available Autonomous underwater vehicles (AUVs have become the most widely used tools for undertaking complex exploration tasks in marine environments. Their synthetic ability to carry out localization autonomously and build an environmental map concurrently, in other words, simultaneous localization and mapping (SLAM, are considered to be pivotal requirements for AUVs to have truly autonomous navigation. However, the consistency problem of the SLAM system has been greatly ignored during the past decades. In this paper, a consistency constrained extended Kalman filter (EKF SLAM algorithm, applying the idea of local consistency, is proposed and applied to the autonomous navigation of the C-Ranger AUV, which is developed as our experimental platform. The concept of local consistency (LC is introduced after an explicit theoretical derivation of the EKF-SLAM system. Then, we present a locally consistency-constrained EKF-SLAM design, LC-EKF, in which the landmark estimates used for linearization are fixed at the beginning of each local time period, rather than evaluated at the latest landmark estimates. Finally, our proposed LC-EKF algorithm is experimentally verified, both in simulations and sea trials. The experimental results show that the LC-EKF performs well with regard to consistency, accuracy and computational efficiency.

  14. Robust driver heartbeat estimation: A q-Hurst exponent based automatic sensor change with interactive multi-model EKF.

    Science.gov (United States)

    Vrazic, Sacha

    2015-08-01

    Preventing car accidents by monitoring the driver's physiological parameters is of high importance. However, existing measurement methods are not robust to driver's body movements. In this paper, a system that estimates the heartbeat from the seat embedded piezoelectric sensors, and that is robust to strong body movements is presented. Multifractal q-Hurst exponents are used within a classifier to predict the most probable best sensor signal to be used in an Interactive Multi-Model Extended Kalman Filter pulsation estimation procedure. The car vibration noise is reduced using an autoregressive exogenous model to predict the noise on sensors. The performance of the proposed system was evaluated on real driving data up to 100 km/h and with slaloms at high speed. It is shown that this method improves by 36.7% the pulsation estimation under strong body movement compared to static sensor pulsation estimation and appears to provide reliable pulsation variability information for top-level analysis of drowsiness or other conditions.

  15. Hybrid Multi-Agent Control in Microgrids: Framework, Models and Implementations Based on IEC 61850

    Directory of Open Access Journals (Sweden)

    Xiaobo Dou

    2014-12-01

    Full Text Available Operation control is a vital and complex issue for microgrids. The objective of this paper is to explore the practical means of applying decentralized control by using a multi agent system in actual microgrids and devices. This paper presents a hierarchical control framework (HCF consisting of local reaction control (LRC level, local decision control (LDC level, horizontal cooperation control (HCC level and vertical cooperation control (VCC level to meet different control requirements of a microgrid. Then, a hybrid multi-agent control model (HAM is proposed to implement HCF, and the properties, functionalities and operating rules of HAM are described. Furthermore, the paper elaborates on the implementation of HAM based on the IEC 61850 Standard, and proposes some new implementation methods, such as extended information models of IEC 61850 with agent communication language and bidirectional interaction mechanism of generic object oriented substation event (GOOSE communication. A hardware design and software system are proposed and the results of simulation and laboratory tests verify the effectiveness of the proposed strategies, models and implementations.

  16. Description and Rationale for the Planning, Monitoring, and Implementation (PMI) Model: Description.

    Science.gov (United States)

    Ford, Valeria A.

    The design of the Planning, Monitoring, and Implementation Model (PMI) and the aspects of the model that make it useful in public schools are the topics of this paper. After the objectives of a program or operation have been identified, the model specifies three additional pieces of information that are needed for an evaluation: inputs, processes,…

  17. Health care managers' views on and approaches to implementing models for improving care processes.

    Science.gov (United States)

    Andreasson, Jörgen; Eriksson, Andrea; Dellve, Lotta

    2016-03-01

    To develop a deeper understanding of health-care managers' views on and approaches to the implementation of models for improving care processes. In health care, there are difficulties in implementing models for improving care processes that have been decided on by upper management. Leadership approaches to this implementation can affect the outcome. In-depth interviews with first- and second-line managers in Swedish hospitals were conducted and analysed using grounded theory. 'Coaching for participation' emerged as a central theme for managers in handling top-down initiated process development. The vertical approach in this coaching addresses how managers attempt to sustain unit integrity through adapting and translating orders from top management. The horizontal approach in the coaching refers to managers' strategies for motivating and engaging their employees in implementation work. Implementation models for improving care processes require a coaching leadership built on close manager-employee interaction, mindfulness regarding the pace of change at the unit level, managers with the competence to share responsibility with their teams and engaged employees with the competence to share responsibility for improving the care processes, and organisational structures that support process-oriented work. Implications for nursing management are the importance of giving nurse managers knowledge of change management. © 2015 John Wiley & Sons Ltd.

  18. Implicit implementation and consistent tangent modulus of a viscoplastic model for polymers

    OpenAIRE

    ACHOUR, Nadia; CHATZIGEORGIOU, George; MERAGHNI, Fodil; CHEMISKY, Yves; FITOUSSI, Joseph

    2015-01-01

    In this work, the phenomenological viscoplastic DSGZ model (Duan et al., 2001 [13]), developed for glassy or semi-crystalline polymers, is numerically implemented in a three-dimensional framework, following an implicit formulation. The computational methodology is based on the radial return mapping algorithm. This implicit formulation leads to the definition of the consistent tangent modulus which permits the implementation in incremental micromechanical scale transition analysis. The extende...

  19. The architecture and prototype implementation of the Model Environment system

    Science.gov (United States)

    Donchyts, G.; Treebushny, D.; Primachenko, A.; Shlyahtun, N.; Zheleznyak, M.

    2007-01-01

    An approach that simplifies software development of the model based decision support systems for environmental management has been introduced. The approach is based on definition and management of metadata and data related to computational model without losing data semantics and proposed methods of integration of the new modules into the information system and their management. An architecture of the integrated modelling system is presented. The proposed architecture has been implemented as a prototype of integrated modelling system using. NET/Gtk{#} and is currently being used to re-design European Decision Support System for Nuclear Emergency Management RODOS (http://www.rodos.fzk.de) using Java/Swing.

  20. Implementation of Software Configuration Management Process by Models: Practical Experiments and Learned Lessons

    Directory of Open Access Journals (Sweden)

    Bartusevics Arturs

    2014-12-01

    Full Text Available Nowadays software configuration management process is not only dilemma which system should be used for version control or how to merge changes from one source code branch to other. There are multiple tasks such as version control, build management, deploy management, status accounting, bug tracking and many others that should be solved to support full configuration management process according to most popular quality standards. The main scope of the mentioned process is to include only valid and tested software items to final version of product and prepare a new version as soon as possible. To implement different tasks of software configuration management process, a set of different tools, scripts and utilities should be used. The current paper provides a new model-based approach to implementation of configuration management. Using different models, a new approach helps to organize existing solutions and develop new ones by a parameterized way, thus increasing reuse of solutions. The study provides a general description of new model-based conception and definitions of all models needed to implement a new approach. The second part of the paper contains an overview of criteria, practical experiments and lessons learned from using new models in software configuration management. Finally, further works are defined based on results of practical experiments and lessons learned.

  1. GNSS Positioning Performance Analysis Using PSO-RBF Estimation Model

    Directory of Open Access Journals (Sweden)

    Jgouta Meriem

    2017-06-01

    Full Text Available Positioning solutions need to be more precise and available. The most frequent method used nowadays includes a GPS receiver, sometimes supported by other sensors. Generally, GPS and GNSS suffer from spreading perturbations that produce biases on pseudo-range measurements. With a view to optimize the use of the satellites received, we offer a positioning algorithm with pseudo range error modelling with the contribution of an appropriate filtering process. Extended Kalman Filter, The Rao- Blackwellized filter are among the most widely used algorithms to predict errors and to filter the high frequency noise. This paper describes a new method of estimating the pseudo-range errors based on the PSO-RBF model which achieves an optimal training criterion. This model is appropriate of its method to predict the GPS corrections for accurate positioning, it reduce the positioning errors at high velocities by more than 50% compared to the RLS or EKF methods.

  2. Models of user involvement in the mental health context: intentions and implementation challenges.

    Science.gov (United States)

    Storm, Marianne; Edwards, Adrian

    2013-09-01

    Patient-centered care, shared decision-making, patient participation and the recovery model are models of care which incorporate user involvement and patients' perspectives on their treatment and care. The aims of this paper are to examine these different care models and their association with user involvement in the mental health context and discuss some of the challenges associated with their implementation. The sources used are health policy documents and published literature and research on patient-centered care, shared decision-making, patient participation and recovery. The policy documents advocate that mental health services should be oriented towards patients' or users' needs, participation and involvement. These policies also emphasize recovery and integration of people with mental disorders in the community. However, these collaborative care models have generally been subject to limited empirical research about effectiveness. There are also challenges to implementation of the models in inpatient care. What evidence there is indicates tensions between patients' and providers' perspectives on treatment and care. There are issues related to risk and the person's capacity for user involvement, and concerns about what role patients themselves wish to play in decision-making. Lack of competence and awareness among providers are further issues. Further work on training, evaluation and implementation is needed to ensure that inpatient mental health services are adapting user oriented care models at all levels of services.

  3. Implementation of the frequency dependent line model in a real-time power system simulator

    Directory of Open Access Journals (Sweden)

    Reynaldo Iracheta-Cortez

    2017-09-01

    Full Text Available In this paper is described the implementation of the frequency-dependent line model (FD-Line in a real-time digital power system simulator. The main goal with such development is to describe a general procedure to incorporate new realistic models of power system components in modern real-time simulators based on the Electromagnetic Transients Program (EMTP. In this procedure are described, firstly, the steps to obtain the time domain solution of the differential equations that models the electromagnetic behavior in multi-phase transmission lines with frequency dependent parameters. After, the algorithmic solution of the FD-Line model is implemented in Simulink environment, through an S-function programmed in C language, for running off-line simulations of electromagnetic transients. This implementation allows the free assembling of the FD Line model with any element of the Power System Blockset library and also, it can be used to build any network topology. The main advantage of having a power network built in Simulink is that can be executed in real-time by means of the commercial eMEGAsim simulator. Finally, several simulation cases are presented to validate the accuracy and the real-time performance of the FD-Line model.

  4. Discrete-Feature Model Implementation of SDM-Site Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

    2010-03-15

    A discrete-feature model (DFM) was implemented for the Forsmark repository site based on the final site descriptive model from surface based investigations. The discrete-feature conceptual model represents deformation zones, individual fractures, and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which, in the present study, is treated as impermeable. This approximation is reasonable for sites in crystalline rock which has very low permeability, apart from that which results from macroscopic fracturing. Models are constructed based on the geological and hydrogeological description of the sites and engineering designs. Hydraulic heads and flows through the network of water-conducting features are calculated by the finite-element method, and are used in turn to simulate migration of non-reacting solute by a particle-tracking method, in order to estimate the properties of pathways by which radionuclides could be released to the biosphere. Stochastic simulation is used to evaluate portions of the model that can only be characterized in statistical terms, since many water-conducting features within the model volume cannot be characterized deterministically. Chapter 2 describes the methodology by which discrete features are derived to represent water-conducting features around the hypothetical repository at Forsmark (including both natural features and features that result from the disturbance of excavation), and then assembled to produce a discrete-feature network model for numerical simulation of flow and transport. Chapter 3 describes how site-specific data and repository design are adapted to produce the discrete-feature model. Chapter 4 presents results of the calculations. These include utilization factors for deposition tunnels based on the emplacement criteria that have been set forth by the implementers, flow distributions to the deposition holes, and calculated properties of discharge paths as well as

  5. Discrete-Feature Model Implementation of SDM-Site Forsmark

    International Nuclear Information System (INIS)

    Geier, Joel

    2010-03-01

    A discrete-feature model (DFM) was implemented for the Forsmark repository site based on the final site descriptive model from surface based investigations. The discrete-feature conceptual model represents deformation zones, individual fractures, and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which, in the present study, is treated as impermeable. This approximation is reasonable for sites in crystalline rock which has very low permeability, apart from that which results from macroscopic fracturing. Models are constructed based on the geological and hydrogeological description of the sites and engineering designs. Hydraulic heads and flows through the network of water-conducting features are calculated by the finite-element method, and are used in turn to simulate migration of non-reacting solute by a particle-tracking method, in order to estimate the properties of pathways by which radionuclides could be released to the biosphere. Stochastic simulation is used to evaluate portions of the model that can only be characterized in statistical terms, since many water-conducting features within the model volume cannot be characterized deterministically. Chapter 2 describes the methodology by which discrete features are derived to represent water-conducting features around the hypothetical repository at Forsmark (including both natural features and features that result from the disturbance of excavation), and then assembled to produce a discrete-feature network model for numerical simulation of flow and transport. Chapter 3 describes how site-specific data and repository design are adapted to produce the discrete-feature model. Chapter 4 presents results of the calculations. These include utilization factors for deposition tunnels based on the emplacement criteria that have been set forth by the implementers, flow distributions to the deposition holes, and calculated properties of discharge paths as well as

  6. A Novel Observer for Lithium-Ion Battery State of Charge Estimation in Electric Vehicles Based on a Second-Order Equivalent Circuit Model

    Directory of Open Access Journals (Sweden)

    Bizhong Xia

    2017-08-01

    Full Text Available Accurate state of charge (SOC estimation can prolong lithium-ion battery life and improve its performance in practice. This paper proposes a new method for SOC estimation. The second-order resistor-capacitor (2RC equivalent circuit model (ECM is applied to describe the dynamic behavior of lithium-ion battery on deriving state space equations. A novel method for SOC estimation is then presented. This method does not require any matrix calculation, so the computation cost can be very low, making it more suitable for hardware implementation. The Federal Urban Driving Schedule (FUDS, The New European Driving Cycle (NEDC, and the West Virginia Suburban Driving Schedule (WVUSUB experiments are carried to evaluate the performance of the proposed method. Experimental results show that the SOC estimation error can converge to 3% error boundary within 30 seconds when the initial SOC estimation error is 20%, and the proposed method can maintain an estimation error less than 3% with 1% voltage noise and 5% current noise. Further, the proposed method has excellent robustness against parameter disturbance. Also, it has higher estimation accuracy than the extended Kalman filter (EKF, but with decreased hardware requirements and faster convergence rate.

  7. A multiscale framework with extended Kalman filter for lithium-ion battery SOC and capacity estimation

    International Nuclear Information System (INIS)

    Hu, Chao; Youn, Byeng D.; Chung, Jaesik

    2012-01-01

    Highlights: ► We develop a mutiscale framework with EKF to estimate SOC and capacity. ► The framework is a hybrid of coulomb counting and adaptive filtering techniques. ► It decouples SOC and capacity estimation in terms of measurement and time-scale. ► Results verify the framework achieves higher accuracy and efficiency than dual EKF. -- Abstract: State-of-charge (SOC) and capacity estimation plays an essential role in many battery-powered applications, such as electric vehicle (EV) and hybrid electric vehicle (HEV). However, commonly used joint/dual extended Kalman filter (EKF) suffers from the lack of accuracy in the capacity estimation since (i) the cell voltage is the only measurable data for the SOC and capacity estimation and updates and (ii) the capacity is very weakly linked to the cell voltage. The lack of accuracy in the capacity estimation may further reduce the accuracy in the SOC estimation due to the strong dependency of the SOC on the capacity. Furthermore, although the capacity is a slowly time-varying quantity that indicates cell state-of-health (SOH), the capacity estimation is generally performed on the same time-scale as the quickly time-varying SOC, resulting in high computational complexity. To resolve these difficulties, this paper proposes a multiscale framework with EKF for SOC and capacity estimation. The proposed framework comprises two ideas: (i) a multiscale framework to estimate SOC and capacity that exhibit time-scale separation and (ii) a state projection scheme for accurate and stable capacity estimation. Simulation results with synthetic data based on a valid cell dynamic model suggest that the proposed framework, as a hybrid of coulomb counting and adaptive filtering techniques, achieves higher accuracy and efficiency than joint/dual EKF. Results of the cycle test on Lithium-ion prismatic cells further verify the effectiveness of our framework.

  8. Regulation of electricity distribution: Issues for implementing a norm model

    International Nuclear Information System (INIS)

    Bjoerndal, Endre; Bjoerndal, Mette; Bjoernenak, Trond; Johnsen, Thore

    2005-01-01

    The Norwegian regulation of transmission and distribution of electricity is currently under revision, and several proposals, including price caps, various norm models and adjustments to the present revenue cap model, have been considered by the Norwegian regulator, NVE. Our starting point is that a successful and sustainable income-regulation-model for electricity distribution should be in accordance with the way of thinking, and the managerial tools of modern businesses. In the regulation it is assumed that decisions regarding operations and investments are made by independent, business oriented entities. The ambition of a dynamically efficient industry therefore requires that the regulatory model and its implementation support best practice business performance. This will influence how the cost base is determined and the way investments are dealt with. We will investigate a possible implementation of a regulatory model based on cost norms. In this we will distinguish between on the one hand, customer driven costs, and on the other hand, costs related to the network itself. The network related costs, which account for approximately 80% of the total cost of electricity distribution, include the costs of operating and maintaining the network, as well as capital costs. These are the ''difficult'' costs, as their levels depend on structural and climatic factors, as well as the number of customers and the load that is served. Additionally, the costs are not separable, since for instance maintenance and investments can be substitutable activities. The work concentrates on verifying the cost model, and evaluating implications for the use of the present efficiency model (DEA) in the regulation. Moreover, we consider how network related costs can be managed in a norm model. Finally, it is highlighted that an important part of a regulatory model based on cost norms is to devise quality measures and how to use them in the economic regulation. (Author)

  9. Hospital information system: reusability, designing, modelling, recommendations for implementing.

    Science.gov (United States)

    Huet, B

    1998-01-01

    The aims of this paper are to precise some essential conditions for building reuse models for hospital information systems (HIS) and to present an application for hospital clinical laboratories. Reusability is a general trend in software, however reuse can involve a more or less part of design, classes, programs; consequently, a project involving reusability must be precisely defined. In the introduction it is seen trends in software, the stakes of reuse models for HIS and the special use case constituted with a HIS. The main three parts of this paper are: 1) Designing a reuse model (which objects are common to several information systems?) 2) A reuse model for hospital clinical laboratories (a genspec object model is presented for all laboratories: biochemistry, bacteriology, parasitology, pharmacology, ...) 3) Recommendations for generating plug-compatible software components (a reuse model can be implemented as a framework, concrete factors that increase reusability are presented). In conclusion reusability is a subtle exercise of which project must be previously and carefully defined.

  10. A Quantum Implementation Model for Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ammar Daskin

    2018-02-01

    Full Text Available The learning process for multilayered neural networks with many nodes makes heavy demands on computational resources. In some neural network models, the learning formulas, such as the Widrow–Hoff formula, do not change the eigenvectors of the weight matrix while flatting the eigenvalues. In infinity, these iterative formulas result in terms formed by the principal components of the weight matrix, namely, the eigenvectors corresponding to the non-zero eigenvalues. In quantum computing, the phase estimation algorithm is known to provide speedups over the conventional algorithms for the eigenvalue-related problems. Combining the quantum amplitude amplification with the phase estimation algorithm, a quantum implementation model for artificial neural networks using the Widrow–Hoff learning rule is presented. The complexity of the model is found to be linear in the size of the weight matrix. This provides a quadratic improvement over the classical algorithms. Quanta 2018; 7: 7–18.

  11. Implementation of an enlarged model of the safety valves and relief in the plant integral model for the code RELAP/SCDAPSIM

    International Nuclear Information System (INIS)

    Amador G, R.; Ortiz V, J.; Castillo D, R.; Hernandez L, E. J.; Galeana R, J. C.; Gutierrez, V. H.

    2013-10-01

    The present work refers to the implementation of a new model on the logic of the safety valves and relief in the integral model of the Nuclear Power Plant of Laguna Verde of the thermal-hydraulic compute code RELAP/SCDAPSIM Mod. 3.4. The new model was developed with the compute package SIMULINK-MATLAB and contemplates all the operation options of the safety valves and relief, besides including the availability options of the valves in all the operation ways and of blockage in the ways of relief and low-low. The implementation means the elimination of the old model of the safety valves and to analyze the group of logical variables, of discharge and available control systems to associate them to the model of package SIMULINK-MATLAB. The implementation has been practically transparent and 27 cases corresponding to a turbine discharge were analyzed with the code RELAP/SCDAPSIM Mod. 3.4. The results were satisfactory. (Author)

  12. Implementation of a user defined mine blast model in LSDYNA

    NARCIS (Netherlands)

    Tyler-Street, M.; Leerdam, P.J.C.

    2012-01-01

    A user defined mine blast model has been developed and implemented into the explicit finite element code LS-DYNA to provide a numerically efficient method for simulating an antivehicular mine blast. The objective is to provide a simple and robust numerical method which is able to represent both the

  13. Modelling and Practical Implementation of 2-Coil Wireless Power Transfer Systems

    Directory of Open Access Journals (Sweden)

    Hong Zhou

    2014-01-01

    Full Text Available Wireless power transfer (WPT based on inductive coupling could be potentially applied in many practical applications. It has attracted a lot of research interests in the last few years. In this paper, the modelling, design, and implementation of a 2-coil WPT system are represented. The prototype system can be implemented using conventional power electronic devices such as MOSFETs with very low costs as it works in relative low frequency range (less than 1 MHz. In order to find out about the optimal working area for the WPT system, the circuit model based on the practical parameters from the prototype is built. The relationships between the exciting frequency, coupling, and output power are analyzed based on the circuit and magnetic principles. Apart from the theoretic study, the detailed implementation of the WPT prototype including the coil design, digital frequency generation, and high frequency power electronics is also introduced in this paper. Experiments are conducted to verify the effectiveness of the circuit analysis. By carefully tuning the circuit parameters, the prototype is able to deliver 20 W power through 2.2 meter distance with 20–30% efficiency.

  14. Online updating and uncertainty quantification using nonstationary output-only measurement

    Science.gov (United States)

    Yuen, Ka-Veng; Kuok, Sin-Chi

    2016-01-01

    Extended Kalman filter (EKF) is widely adopted for state estimation and parametric identification of dynamical systems. In this algorithm, it is required to specify the covariance matrices of the process noise and measurement noise based on prior knowledge. However, improper assignment of these noise covariance matrices leads to unreliable estimation and misleading uncertainty estimation on the system state and model parameters. Furthermore, it may induce diverging estimation. To resolve these problems, we propose a Bayesian probabilistic algorithm for online estimation of the noise parameters which are used to characterize the noise covariance matrices. There are three major appealing features of the proposed approach. First, it resolves the divergence problem in the conventional usage of EKF due to improper choice of the noise covariance matrices. Second, the proposed approach ensures the reliability of the uncertainty quantification. Finally, since the noise parameters are allowed to be time-varying, nonstationary process noise and/or measurement noise are explicitly taken into account. Examples using stationary/nonstationary response of linear/nonlinear time-varying dynamical systems are presented to demonstrate the efficacy of the proposed approach. Furthermore, comparison with the conventional usage of EKF will be provided to reveal the necessity of the proposed approach for reliable model updating and uncertainty quantification.

  15. Factors affecting strategic plan implementation using interpretive structural modeling (ISM).

    Science.gov (United States)

    Bahadori, Mohammadkarim; Teymourzadeh, Ehsan; Tajik, Hamidreza; Ravangard, Ramin; Raadabadi, Mehdi; Hosseini, Seyed Mojtaba

    2018-06-11

    Purpose Strategic planning is the best tool for managers seeking an informed presence and participation in the market without surrendering to changes. Strategic planning enables managers to achieve their organizational goals and objectives. Hospital goals, such as improving service quality and increasing patient satisfaction cannot be achieved if agreed strategies are not implemented. The purpose of this paper is to investigate the factors affecting strategic plan implementation in one teaching hospital using interpretive structural modeling (ISM). Design/methodology/approach The authors used a descriptive study involving experts and senior managers; 16 were selected as the study sample using a purposive sampling method. Data were collected using a questionnaire designed and prepared based on previous studies. Data were analyzed using ISM. Findings Five main factors affected strategic plan implementation. Although all five variables and factors are top level, "senior manager awareness and participation in the strategic planning process" and "creating and maintaining team participation in the strategic planning process" had maximum drive power. "Organizational structure effects on the strategic planning process" and "Organizational culture effects on the strategic planning process" had maximum dependence power. Practical implications Identifying factors affecting strategic plan implementation is a basis for healthcare quality improvement by analyzing the relationship among factors and overcoming the barriers. Originality/value The authors used ISM to analyze the relationship between factors affecting strategic plan implementation.

  16. A Dynamic Object Behavior Model and Implementation Based on Computational Reflection

    Institute of Scientific and Technical Information of China (English)

    HE Cheng-wan; HE Fei; HE Ke-qing

    2005-01-01

    A dynamic object behavior model based on computational reflection is proposed. This model consists of function level and meta level, the meta objects in meta level manage the base objects and behaviors in function level, including dynamic binding and unbinding of base object and behavior.We implement this model with RoleJava Language, which is our self linguistic extension of the Java Language. Meta Objects are generated automatically at compile-time, this makes the reflecton mechanism transparent to programmers. Finally an example applying this model to a banking system is presented.

  17. Development of a Forward Model for the Assimilation of Delay-Doppler Maps (DDMs)

    Science.gov (United States)

    Garrison, J. L.; Huang, F.; Leidner, M.; Annane, B.; Hoffman, R.

    2017-12-01

    Ocean wind measurements from CYGNSS have the potential to improve the observation and analysis of tropical cyclones globally. The standard Level-2 wind product, however, is defined by the 25-km spatial resolution requirement using only 15 out of a total of 187 delay-Doppler bins. The full forward model relating a surface wind field to the delay-Doppler map (DDM) involves a surface integral over the glistening zone (which can be expressed in a variety of more numerically efficient convolutional forms) and incorporates variation of the receiver antenna pattern over the surface. Combined with the well-known ambiguity in the mapping between surface coordinates and delay-Doppler space, this model cannot be inverted to provide wind speed estimates away from the specular point. Two approaches are being studied to improve wind retrievals through use of the full DDM. The first uses sequential DDM measurements which cover a large common area on the sea surface, but provide some variation in geometry due to satellite motion. An Extended Kalman filter (EKF) is used to integrate these sequential observations. Numerical simulations have been performed to show the sensitivity of the filter stability to the initial covariance matrix. Although it was found that the EKF wind field still retains artifacts of the delay-Doppler ambiguity, the wind speed at the specular point can be estimated with lower error than that of the baseline Level 2 products. Another approach is to assimilate DDMs directly into a 2-dimensional, Variational vector wind Analysis Method (VAM). Sample results from this forward model will be generated from idealized and real wind fields, and compared to results from the CYGNSS Science Team End-to-End simulator (E2ES). In both of these approaches, an accurate forward model for the calibrated level 1a DDM data is required. This presentation will emphasize the development of this model and the results of testing the forward model through comparison with early CYGNSS

  18. Description and Rationale for the Planning, Monitoring, and Implementation (PMI) Model: Rationale.

    Science.gov (United States)

    Cort, H. Russell

    The rationale for the Planning, Monitoring, and Implementation Model (PMI) is the subject of this paper. The Superintendent of the District of Columbia Public Schools requested a model for systematic evaluation of educational programs to determine their effectiveness. The school system's emphasis on objective-referenced instruction and testing,…

  19. Effect of different implementations of the same ice history in GIA modeling

    DEFF Research Database (Denmark)

    Barletta, Valentina Roberta; Bordoni, Andrea

    2013-01-01

    -level equation solver often forces to implement the ice model in a representation that differs from the one originally provided. We show that using different representations of the same ice model gives important differences and artificial contributions to the sea level estimates, both at global and at regional...

  20. Implementation and validation of a condensation model in ANSYS

    International Nuclear Information System (INIS)

    Lehmkuhl, J.; Kelm, S.; Allelein, H.J.; Forschungszentrum Juelich

    2012-01-01

    During design-based beyond-design accidents large amounts of steam and hydrogen are released onto the containment. The knowledge on the local distribution of gases and atmospheric conditions is therefore necessary for the design of safety systems or emergency measures. Condensation processes have a significant influence on the thermal hydraulics, the hydrogen combustion and the aerosol behavior in the containment. The presented one-phase condensation model was developed for an effective CFD modeling of condensation processes in ANSYS CFX for accident analyses. Based on the assumption that wall condensation is mainly determined by the mass transport the assumption of thermal equilibrium can be used for one-phase calculations. The modeling concept is applicable for wall and volume condensation and has been implemented.

  1. Pedestrian Path Prediction with Recursive Bayesian Filters: A Comparative Study

    NARCIS (Netherlands)

    Schneider, N.; Gavrila, D.M.

    2013-01-01

    In the context of intelligent vehicles, we perform a comparative study on recursive Bayesian filters for pedestrian path prediction at short time horizons (< 2s). We consider Extended Kalman Filters (EKF) based on single dynamical models and Interacting Multiple Models (IMM) combining several such

  2. Pilot implementation

    DEFF Research Database (Denmark)

    Hertzum, Morten; Bansler, Jørgen P.; Havn, Erling C.

    2012-01-01

    A recurrent problem in information-systems development (ISD) is that many design shortcomings are not detected during development, but first after the system has been delivered and implemented in its intended environment. Pilot implementations appear to promise a way to extend prototyping from...... the laboratory to the field, thereby allowing users to experience a system design under realistic conditions and developers to get feedback from realistic use while the design is still malleable. We characterize pilot implementation, contrast it with prototyping, propose a iveelement model of pilot...... implementation and provide three empirical illustrations of our model. We conclude that pilot implementation has much merit as an ISD technique when system performance is contingent on context. But we also warn developers that, despite their seductive conceptual simplicity, pilot implementations can be difficult...

  3. Economic Optimization of Spray Dryer Operation using Nonlinear Model Predictive Control with State Estimation

    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....

  4. More scalability, less pain: A simple programming model and its implementation for extreme computing

    International Nuclear Information System (INIS)

    Lusk, E.L.; Pieper, S.C.; Butler, R.M.

    2010-01-01

    This is the story of a simple programming model, its implementation for extreme computing, and a breakthrough in nuclear physics. A critical issue for the future of high-performance computing is the programming model to use on next-generation architectures. Described here is a promising approach: program very large machines by combining a simplified programming model with a scalable library implementation. The presentation takes the form of a case study in nuclear physics. The chosen application addresses fundamental issues in the origins of our Universe, while the library developed to enable this application on the largest computers may have applications beyond this one.

  5. Implementing a citizen's DWI reporting program using the Extra Eyes model

    Science.gov (United States)

    2008-09-01

    This manual is a guide for law enforcement agencies and community organizations in creating and implementing a citizens DWI reporting program in their communities modeling the Operation Extra Eyes program. Extra Eyes is a program that engages volu...

  6. Implementation of the Modified Hoek-Brown Model into the Finite Element Method

    DEFF Research Database (Denmark)

    Sørensen, Emil Smed; Clausen, Johan Christian; Merifield, Richard S.

    2015-01-01

    The Hoek-Brown model for near-homogeneous rock masses will, in some cases, overpredict the tensile strength of the material. In some cases this can lead to unsafe design of structures. Therefore, a tension cut-off is introduced and the model is implemented into an elasto-plastic framework for use...

  7. BARRIERS AND CHALLENGES OF BUILDING INFORMATION MODELLING IMPLEMENTATION IN JORDANIAN CONSTRUCTION INDUSTRY

    OpenAIRE

    Mohammed A.KA. AL-Btoush*, Ahmad Tarmizi Haron

    2017-01-01

    Construction companies are faced with the need to innovatively integrate the construction process and address project development challenges. One way of doing that is the integration of building information modelling (BIM) in the building design and development cycles. However, due to the lack of clear understanding and the absence of a holistic implementation guideline, many companies are unable to fully achieve BIM potentials or implement BIM in their project and building lifecycle. BIM imp...

  8. A First Step Towards High-Level Cost Models for the Implementation of SDRs on Multiprocessing Reconfigurable Systems

    DEFF Research Database (Denmark)

    Le Moullec, Yannick

    2011-01-01

    -In-Progress paper we introduce our set of high-level estimation models for Area-Time costs of applications mapped onto FPGA-based multiprocessing reconfigurable architectures. In particular, we suggest models for static and dynamic implementations, taking various internal and external architectural elements...... into account. We believe that such models could be used for rapidly comparing implementation alternatives at a high level of abstraction and for guiding the designer during the (pre)analysis phase of the design flow for the implementation of e.g. SDR platforms....

  9. Development of transformations from business process models to implementations by reuse

    NARCIS (Netherlands)

    Dirgahayu, T.; Quartel, Dick; van Sinderen, Marten J.; Ferreira Pires, Luis; Hammoudi, S.

    2007-01-01

    This paper presents an approach for developing transformations from business process models to implementations that facilitates reuse. A transformation is developed as a composition of three smaller tasks: pattern recognition, pattern realization and activity transformation. The approach allows one

  10. cudaBayesreg: Parallel Implementation of a Bayesian Multilevel Model for fMRI Data Analysis

    Directory of Open Access Journals (Sweden)

    Adelino R. Ferreira da Silva

    2011-10-01

    Full Text Available Graphic processing units (GPUs are rapidly gaining maturity as powerful general parallel computing devices. A key feature in the development of modern GPUs has been the advancement of the programming model and programming tools. Compute Unified Device Architecture (CUDA is a software platform for massively parallel high-performance computing on Nvidia many-core GPUs. In functional magnetic resonance imaging (fMRI, the volume of the data to be processed, and the type of statistical analysis to perform call for high-performance computing strategies. In this work, we present the main features of the R-CUDA package cudaBayesreg which implements in CUDA the core of a Bayesian multilevel model for the analysis of brain fMRI data. The statistical model implements a Gibbs sampler for multilevel/hierarchical linear models with a normal prior. The main contribution for the increased performance comes from the use of separate threads for fitting the linear regression model at each voxel in parallel. The R-CUDA implementation of the Bayesian model proposed here has been able to reduce significantly the run-time processing of Markov chain Monte Carlo (MCMC simulations used in Bayesian fMRI data analyses. Presently, cudaBayesreg is only configured for Linux systems with Nvidia CUDA support.

  11. Virtual Sensors for Biodiesel Production in a Batch Reactor

    Directory of Open Access Journals (Sweden)

    Betty Y. López-Zapata

    2017-03-01

    Full Text Available Fossil fuel combustion produces around 98% of coal emissions. Therefore, liquid and gaseous biofuels have become more attractive due to their environmental benefits. The biodiesel production process requires measurements that help to control and supervise the variables involved in the process. The measurements provide valuable information about the operation conditions and give estimations about the critical variables of the process. The information from measurements is essential for monitoring the state of a process and verifying if it has an optimal performance. The objective of this study was the conception of a virtual sensor based on the Extended Kalman Filter (EKF and the model of a batch biodiesel reactor for estimating concentrations of triglycerides (TG, diglycerides (DG, monoglycerides (MG, methyl ester (E, alcohol (A, and glycerol (GL in real-time through measurement of the temperature and pH. Estimation of the TG, DG, MG, E, A, and Gl through this method eliminates the need for additional sensors and allows the use of different types of control. For the performance analysis of the virtual sensor, the data obtained from the EKF are compared with experimental data reported in the literature, with the mean square error of the estimate then being calculated. In addition, the results of this approach can be implemented in a real system, since it only uses measurements available in a reactor such as temperature and pH.

  12. Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, J Lynn

    2014-06-24

    Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have

  13. Implementation of JAERI's reflood model into TRAC-PF1/MOD1 code

    International Nuclear Information System (INIS)

    Akimoto, Hajime; Ohnuki, Akira; Murao, Yoshio

    1993-02-01

    Selected physical models of REFLA code, that is a reflood analysis code developed at JAERI, were implemented into the TRAC-PF1/MOD1 code in order to improve the predictive capability of the TRAC-PF1/MOD1 code for the core thermal hydraulic behaviors during the reflood phase in a PWR LOCA. Through comparisons of physical models between both codes, (1) Murao-Iguchi void fraction correlation, (2) the drag coefficient correlation acting to drops, (3) the correlation for wall heat transfer coefficient in the film boiling regime, (4) the quench velocity correlation and (5) heat transfer correlations for the dispersed flow regime were selected from the REFLA code to be implemented into the TRAC-PF1/MOD1 code. A method for the transformation of the void fraction correlation to the equivalent interfacial friction model was developed and the effect of the transformation method on the stability of the solution was discussed. Through assessment calculation using data from CCTF (Cylindrical Core Test Facility) flat power test, it was confirmed that the predictive capability of the TRAC code for the core thermal hydraulic behaviors during the reflood can be improved by the implementation of selected physical models of the REFLA code. Several user guidelines for the modified TRAC code were proposed based on the sensitivity studies on fluid cell number in the hydraulic calculation and on node number and effect of axial heat conduction in the heat conduction calculation of fuel rod. (author)

  14. A Framework for Semi-Automated Implementation of Multidimensional Data Models

    Directory of Open Access Journals (Sweden)

    Ilona Mariana NAGY

    2012-08-01

    Full Text Available Data warehousing solution development represents a challenging task which requires the employment of considerable resources on behalf of enterprises and sustained commitment from the stakeholders. Costs derive mostly from the amount of time invested in the design and physical implementation of these large projects, time that we consider, may be decreased through the automation of several processes. Thus, we present a framework for semi-automated implementation of multidimensional data models and introduce an automation prototype intended to reduce the time of data structures generation in the warehousing environment. Our research is focused on the design of an automation component and the development of a corresponding prototype from technical metadata.

  15. Implementation of a Unified Constitutive Model into the ABAQUS Finite Element Package

    National Research Council Canada - National Science Library

    Wescott, R

    1999-01-01

    Unified constitutive models have previously been developed at AMRL and implemented into the PAFEC and ABAQUS Finite Element packages to predict the stress-strain response of structures that undergo...

  16. Computational implementation of the multi-mechanism deformation coupled fracture model for salt

    International Nuclear Information System (INIS)

    Koteras, J.R.; Munson, D.E.

    1996-01-01

    The Multi-Mechanism Deformation (M-D) model for creep in rock salt has been used in three-dimensional computations for the Waste Isolation Pilot Plant (WIPP), a potential waste, repository. These computational studies are relied upon to make key predictions about long-term behavior of the repository. Recently, the M-D model was extended to include creep-induced damage. The extended model, the Multi-Mechanism Deformation Coupled Fracture (MDCF) model, is considerably more complicated than the M-D model and required a different technology from that of the M-D model for a computational implementation

  17. Implementing The Automated Phases Of The Partially-Automated Digital Triage Process Model

    Directory of Open Access Journals (Sweden)

    Gary D Cantrell

    2012-12-01

    Full Text Available Digital triage is a pre-digital-forensic phase that sometimes takes place as a way of gathering quick intelligence. Although effort has been undertaken to model the digital forensics process, little has been done to date to model digital triage. This work discuses the further development of a model that does attempt to address digital triage the Partially-automated Crime Specific Digital Triage Process model. The model itself will be presented along with a description of how its automated functionality was implemented to facilitate model testing.

  18. Implementing a New Model for Teachers' Professional Learning in Papua New Guinea

    Science.gov (United States)

    Honan, Eileen; Evans, Terry; Muspratt, Sandy; Paraide, Patricia; Reta, Medi; Baroutsis, Aspa

    2012-01-01

    This article reports on a study that investigates the possibilities of developing a professional learning model based on action research that could lead to sustained improvements in teaching and learning in schools in remote areas of Papua New Guinea. The issues related to the implementation of this model are discussed using a critical lens that…

  19. Modelling a Java Ring based implementation of an N-Count payment system

    NARCIS (Netherlands)

    Revill, J.D.; Hartel, Pieter H.

    N-Count is a system for offline value transfer. A prototype of an N-Count payment system has been designed, and it has been implemented in Java. We have used the Java Ring with the Java Card API as a secure device. The system has also been modelled using the Spin model checker. The combined

  20. Business Modeling to Implement an eHealth Portal for Infection Control: A Reflection on Co-Creation With Stakeholders

    Science.gov (United States)

    Wentzel, Jobke; Sanderman, Robbert; van Gemert-Pijnen, Lisette

    2015-01-01

    Background It is acknowledged that the success and uptake of eHealth improve with the involvement of users and stakeholders to make technology reflect their needs. Involving stakeholders in implementation research is thus a crucial element in developing eHealth technology. Business modeling is an approach to guide implementation research for eHealth. Stakeholders are involved in business modeling by identifying relevant stakeholders, conducting value co-creation dialogs, and co-creating a business model. Because implementation activities are often underestimated as a crucial step while developing eHealth, comprehensive and applicable approaches geared toward business modeling in eHealth are scarce. Objective This paper demonstrates the potential of several stakeholder-oriented analysis methods and their practical application was demonstrated using Infectionmanager as an example case. In this paper, we aim to demonstrate how business modeling, with the focus on stakeholder involvement, is used to co-create an eHealth implementation. Methods We divided business modeling in 4 main research steps. As part of stakeholder identification, we performed literature scans, expert recommendations, and snowball sampling (Step 1). For stakeholder analyzes, we performed “basic stakeholder analysis,” stakeholder salience, and ranking/analytic hierarchy process (Step 2). For value co-creation dialogs, we performed a process analysis and stakeholder interviews based on the business model canvas (Step 3). Finally, for business model generation, we combined all findings into the business model canvas (Step 4). Results Based on the applied methods, we synthesized a step-by-step guide for business modeling with stakeholder-oriented analysis methods that we consider suitable for implementing eHealth. Conclusions The step-by-step guide for business modeling with stakeholder involvement enables eHealth researchers to apply a systematic and multidisciplinary, co-creative approach for

  1. Business Modeling to Implement an eHealth Portal for Infection Control: A Reflection on Co-Creation With Stakeholders.

    Science.gov (United States)

    van Limburg, Maarten; Wentzel, Jobke; Sanderman, Robbert; van Gemert-Pijnen, Lisette

    2015-08-13

    It is acknowledged that the success and uptake of eHealth improve with the involvement of users and stakeholders to make technology reflect their needs. Involving stakeholders in implementation research is thus a crucial element in developing eHealth technology. Business modeling is an approach to guide implementation research for eHealth. Stakeholders are involved in business modeling by identifying relevant stakeholders, conducting value co-creation dialogs, and co-creating a business model. Because implementation activities are often underestimated as a crucial step while developing eHealth, comprehensive and applicable approaches geared toward business modeling in eHealth are scarce. This paper demonstrates the potential of several stakeholder-oriented analysis methods and their practical application was demonstrated using Infectionmanager as an example case. In this paper, we aim to demonstrate how business modeling, with the focus on stakeholder involvement, is used to co-create an eHealth implementation. We divided business modeling in 4 main research steps. As part of stakeholder identification, we performed literature scans, expert recommendations, and snowball sampling (Step 1). For stakeholder analyzes, we performed "basic stakeholder analysis," stakeholder salience, and ranking/analytic hierarchy process (Step 2). For value co-creation dialogs, we performed a process analysis and stakeholder interviews based on the business model canvas (Step 3). Finally, for business model generation, we combined all findings into the business model canvas (Step 4). Based on the applied methods, we synthesized a step-by-step guide for business modeling with stakeholder-oriented analysis methods that we consider suitable for implementing eHealth. The step-by-step guide for business modeling with stakeholder involvement enables eHealth researchers to apply a systematic and multidisciplinary, co-creative approach for implementing eHealth. Business modeling becomes an

  2. Measurement of a model of implementation for health care : toward a testable theory

    NARCIS (Netherlands)

    Cook, Joan M.; O'Donnell, Casey; Dinnen, Stephanie; Coyne, James C.; Ruzek, Josef I.; Schnurr, Paula P.

    2012-01-01

    Background: Greenhalgh et al. used a considerable evidence-base to develop a comprehensive model of implementation of innovations in healthcare organizations [1]. However, these authors did not fully operationalize their model, making it difficult to test formally. The present paper represents a

  3. Introducing students to ocean modeling via a web-based implementation for the Regional Ocean Modeling System (ROMS) river plume case study

    Science.gov (United States)

    Harris, C. K.; Overeem, I.; Hutton, E.; Moriarty, J.; Wiberg, P.

    2016-12-01

    Numerical models are increasingly used for both research and applied sciences, and it is important that we train students to run models and analyze model data. This is especially true within oceanographic sciences, many of which use hydrodynamic models to address oceanographic transport problems. These models, however, often require a fair amount of training and computer skills before a student can run the models and analyze the large data sets produced by the models. One example is the Regional Ocean Modeling System (ROMS), an open source, three-dimensional primitive equation hydrodynamic ocean model that uses a structured curvilinear horizontal grid. It currently has thousands of users worldwide, and the full model includes modules for sediment transport and biogeochemistry, and several options for turbulence closures and numerical schemes. Implementing ROMS can be challenging to students, however, in part because the code was designed to provide flexibility for the choice of model parameterizations and processes, and to run on a variety of High Performance Computing (HPC) platforms. To provide a more accessible tool for classroom use, we have modified an existing idealized ROMS implementation to be run on a High Performance Computer (HPC) via the WMT (Web Modeling Toolkit), and developed a series of lesson plans that explore sediment transport within the idealized model domain. This has addressed our goal to provide a relatively easy introduction to the numerical modeling process that can be used within upper level undergraduate and graduate classes to explore sediment transport on continental shelves. The model implementation includes wave forcing, along-shelf currents, a riverine source, and suspended sediment transport. The model calculates suspended transport and deposition of sediment delivered to the continental shelf by a riverine flood. Lesson plans lead the students through running the model on a remote HPC, modifying the standard model. The lesson

  4. Symplectic Attitude Estimation for Small Satellites

    National Research Council Canada - National Science Library

    Valpiani, James M; Palmer, Phillip L

    2006-01-01

    .... Symplectic numerical methods are applied to the Extended Kalman Filter (EKF) algorithm to give the SKF, which outperforms the standard EKF in the presence of nonlinearity and low measurement noise in the 1-D case...

  5. Discussion on the Implementation of the Patient Centred Medical Home model - Experiences from Australia

    Directory of Open Access Journals (Sweden)

    Safa Majidi Rahbar

    2017-07-01

    Full Text Available Introduction: Different practitioners and academics have been working on the application of the Patient Centred Medical Home (PCMH model within the Australian context for many years. In early 2016, the Commonwealth government of Australia announced plans to establish Health Care Homes throughout the country based off the PCMH model, beginning with trial sites focused on the bundling of payments. As a result, the number of Primary Health Networks, policy makers and general practices receptive to establishing Health Care Homes is growing rapidly. The time is ripe to identify how best the elements of the model translate into the Australian context and how to implement its elements with success. As a contribution to the opportunity for a widespread implementation, the North Coast Primary Health Network is engaged in a project to build capacity in general practices to transition into Health Care Homes. The main outcomes of this project include: 1. Preparing “The Australian Handbook for Transitioning to Health Care Homes” A resource which will provide a rationale for transitioning to a HCH, milestones for transitioning along a continuum and tools for practice and practice support for establishing the model in general practice. Thus developing capacity to train ‘change facilitators’ to work to accompany transitioning practices. 2. Establishment of a National Network of Patient Centred HCH Collaborators Made up of PHN representatives, experts and policy makers working in the PCMH development space. Focused on improving advocacy effectiveness, knowledge sharing and keeping stakeholders up to date with unfolding developments. 3. Increasing local preparedness and interest for establishing HCHs Focused on propagation of development of interest locally for transitioning practices into HCHs. A local network of practitioners and collaborators informed of project updates and HCH learning and development opportunities in the region. 4. Local trial and

  6. Prediction of L70 lumen maintenance and chromaticity for LEDs using extended Kalman filter models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, Lynn

    2013-09-30

    Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life

  7. Implementation of an object oriented track reconstruction model into multiple LHC experiments*

    Science.gov (United States)

    Gaines, Irwin; Gonzalez, Saul; Qian, Sijin

    2001-10-01

    An Object Oriented (OO) model (Gaines et al., 1996; 1997; Gaines and Qian, 1998; 1999) for track reconstruction by the Kalman filtering method has been designed for high energy physics experiments at high luminosity hadron colliders. The model has been coded in the C++ programming language and has been successfully implemented into the OO computing environments of both the CMS (1994) and ATLAS (1994) experiments at the future Large Hadron Collider (LHC) at CERN. We shall report: how the OO model was adapted, with largely the same code, to different scenarios and serves the different reconstruction aims in different experiments (i.e. the level-2 trigger software for ATLAS and the offline software for CMS); how the OO model has been incorporated into different OO environments with a similar integration structure (demonstrating the ease of re-use of OO program); what are the OO model's performance, including execution time, memory usage, track finding efficiency and ghost rate, etc.; and additional physics performance based on use of the OO tracking model. We shall also mention the experience and lessons learned from the implementation of the OO model into the general OO software framework of the experiments. In summary, our practice shows that the OO technology really makes the software development and the integration issues straightforward and convenient; this may be particularly beneficial for the general non-computer-professional physicists.

  8. Autonomous determination of orbit for probe around asteroids using unscented Kalman filter

    Institute of Scientific and Technical Information of China (English)

    崔平远; 崔祜涛; 黄翔宇; 栾恩杰

    2003-01-01

    The observed images of the asteroid and the asteroid reference images are used to obtain the probe-to-asteroid direction and the location of the limb features of the asteroid in the inertial coordinate. These informa-tion in combination with the shape model of the asteroid and attitude information of the probe are utilized to ob-tain the position of the probe. The position information is then input to the UKF which determines the real-timeorbit of the probe. Finally, the autonomous orbit determination algorithm is validated using digital simulation.The determination of orbit using UKF is compared with that using extended Kalman filter (EKF), and the resultshows that UKF is superior to EKF.

  9. Theory, Solution Methods, and Implementation of the HERMES Model

    Energy Technology Data Exchange (ETDEWEB)

    Reaugh, John E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); White, Bradley W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Curtis, John P. [Atomic Weapons Establishment (AWE), Reading, Berkshire (United Kingdom); Univ. College London (UCL), Gower Street, London (United Kingdom); Springer, H. Keo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-07-13

    The HERMES (high explosive response to mechanical stimulus) model was developed over the past decade to enable computer simulation of the mechanical and subsequent energetic response of explosives and propellants to mechanical insults such as impacts, perforations, drops, and falls. The model is embedded in computer simulation programs that solve the non-linear, large deformation equations of compressible solid and fluid flow in space and time. It is implemented as a user-defined model, which returns the updated stress tensor and composition that result from the simulation supplied strain tensor change. Although it is multi-phase, in that gas and solid species are present, it is single-velocity, in that the gas does not flow through the porous solid. More than 70 time-dependent variables are made available for additional analyses and plotting. The model encompasses a broad range of possible responses: mechanical damage with no energetic response, and a continuous spectrum of degrees of violence including delayed and prompt detonation. This paper describes the basic workings of the model.

  10. Efficient parallel implementation of active appearance model fitting algorithm on GPU.

    Science.gov (United States)

    Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

    2014-01-01

    The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

  11. Implementing a modeling software for animated protein-complex interactions using a physics simulation library.

    Science.gov (United States)

    Ueno, Yutaka; Ito, Shuntaro; Konagaya, Akihiko

    2014-12-01

    To better understand the behaviors and structural dynamics of proteins within a cell, novel software tools are being developed that can create molecular animations based on the findings of structural biology. This study proposes our method developed based on our prototypes to detect collisions and examine the soft-body dynamics of molecular models. The code was implemented with a software development toolkit for rigid-body dynamics simulation and a three-dimensional graphics library. The essential functions of the target software system included the basic molecular modeling environment, collision detection in the molecular models, and physical simulations of the movement of the model. Taking advantage of recent software technologies such as physics simulation modules and interpreted scripting language, the functions required for accurate and meaningful molecular animation were implemented efficiently.

  12. An Object-Oriented Python Implementation of an Intermediate-Level Atmospheric Model

    Science.gov (United States)

    Lin, J. W.

    2008-12-01

    The Neelin-Zeng Quasi-equilibrium Tropical Circulation Model (QTCM1) is a Fortran-based intermediate-level atmospheric model that includes simplified treatments of several physical processes, including a GCM-like convective scheme and a land-surface scheme with representations of different surface types, evaporation, and soil moisture. This model has been used in studies of the Madden-Julian oscillation, ENSO, and vegetation-atmosphere interaction effects on climate. Through the assumption of convective quasi-equilibrium in the troposphere, the QTCM1 is able to include full nonlinearity, resolve baroclinic disturbances, and generate a reasonable climatology, all at low computational cost. One year of simulation on a PC at 5.625 × 3.75 degree longitude-latitude resolution takes under three minutes of wall-clock time. The Python package qtcm implements the QTCM1 in a mixed-language environment that retains the speed of compiled Fortran while providing the benefits of Python's object-oriented framework and robust suite of utilities and datatypes. We describe key programming constructs used to create this modeling environment: the decomposition of model runs into Python objects, providing methods so visualization tools are attached to model runs, and the use of Python's mutable datatypes (lists and dictionaries) to implement the "run list" entity, which enables total runtime control of subroutine execution order and content. The result is an interactive modeling environment where the traditional sequence of "hypothesis → modeling → visualization and analysis" is opened up and made nonlinear and flexible. In this environment, science tasks such as parameter-space exploration and testing alternative parameterizations can be easily automated, without the need for multiple versions of the model code interacting with a bevy of makefiles and shell scripts. The environment also simplifies interfacing of the atmospheric model to other models (e.g., hydrologic models

  13. Formal Implementation of a Performance Evaluation Model for the Face Recognition System

    Directory of Open Access Journals (Sweden)

    Yong-Nyuo Shin

    2008-01-01

    Full Text Available Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

  14. Pseudolinear Model Based Solution to the SLAM Problem of Nonholonomic Mobile Robots

    Science.gov (United States)

    Pathiranage, Chandima Dedduwa; Watanabe, Keigo; Izumi, Kiyotaka

    This paper describes an improved solution to the simultaneous localization and mapping (SLAM) problem based on pseudolinear models. Accurate estimation of vehicle and landmark states is one of the key issues for successful mobile robot navigation if the configuration of the environment and initial robot location are unknown. A state estimator which can be designed to use the nonlinearity as it is coming from the original model has always been invaluable in which high accuracy is expected. Thus to accomplish the above highlighted point, pseudolinear model based Kalman filter (PLKF) state estimator is introduced. A less error prone vehicle process model is proposed to improve the accuracy and the faster convergence of state estimation. Evolution of vehicle motion is modeled using vehicle frame translation derived from successive dead reckoned poses as a control input. A measurement model with two sensor frames is proposed to improve the data association. The PLKF-based SLAM algorithm is simulated using Matlab for vehicle-landmarks system and results show that the proposed approach performs much accurately compared to the well known extended Kalman filter (EKF).

  15. Total Productive Maintenance And Role Of Interpretive Structural Modeling And Structural Equation Modeling In Analyzing Barriers In Its Implementation A Literature Review

    Directory of Open Access Journals (Sweden)

    Prasanth S. Poduval

    2015-08-01

    Full Text Available Abstract - The aim of the authors is to present a review of literature of Total Productive Maintenance and the barriers in implementation of Total Productive Maintenance TPM. The paper begins with a brief description of TPM and the barriers in implementation of TPM. Interpretive Structural Modeling ISM and its role in analyzing the barriers in TPM implementation is explained in brief. Applications of ISM in analyzing issues in various fields are highlighted with special emphasis on TPM. The paper moves on to introduction to Structural Equation Modeling SEM and its role in validating ISM in analyzing barriers in implementation of TPM. The paper concludes with a gap analysis from the current literature research that can be carried out and expected outcomes from the proposed research.

  16. Implementation and evaluation of a depression care model for homebound elderly.

    Science.gov (United States)

    Madden-Baer, Rose; McConnell, Eleanor; Rosati, Robert J; Rosenfeld, Peri; Edison, Ilaina

    2013-01-01

    Depression affects 14% to 46% of homebound elderly and is costly and disabling. Home health agencies face significant challenges delivering effective depression care. In response, an evidence-based depression care model was developed in a home health agency. Twelve-month program evaluation data demonstrated a 2.99 mean reduction in depression scores (P Depression Scale and confirmed that a clinically effective, operationally feasible, and financially sustainable depression care model can be implemented in home health care.

  17. EVALUATING THE EFFECTS OF THE IMPLEMENTATION OF IRAN NATIONAL QUALITY AWARD NEW MODEL (INQA IN IRANIAN ORGANIZATIONS

    Directory of Open Access Journals (Sweden)

    Mahmoud Zamani

    2014-09-01

    Full Text Available The aim of this study is to examine the effectiveness of the Iran National Quality Award new model (INQA in corporations that have implemented this model in Iran. This research aims to reveal the effects of implementation of Iran National Quality Award (INQA New Model on seven dimensions of the Iranian companies which indeed are seven core factors of this model, i.e. Management & leadership, People, Processes, Resources, Customer & consumer results, Environment & community results, and Performance results. A mail survey was conducted on a simple random sample of 210 organizations that have achieved certification or appreciation during the implementation of INQA model in four rounds. 400 questionnaires were randomly distributed and 392 complete and correct questionnaires were returned. Descriptive and inferential statistics were employed to analyze the data.Results indicated that the highest positive impact of INQA New Model on the improvement of organizational performance of the surveyed organizations was on customers' area. Performance results, leadership and management, processes improvement, environment and society results, and finally better utilization of organizational resources were respectively other areas which are affected mostly. Also, this study found no significant relationship between the implementation of this model and the improvement of employees' conditions in the surveyed organizations.

  18. [Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on Field Programmable Gate Array].

    Science.gov (United States)

    Wang, Jinlong; Lu, Mai; Hu, Yanwen; Chen, Xiaoqiang; Pan, Qiangqiang

    2015-12-01

    Neuron is the basic unit of the biological neural system. The Hodgkin-Huxley (HH) model is one of the most realistic neuron models on the electrophysiological characteristic description of neuron. Hardware implementation of neuron could provide new research ideas to clinical treatment of spinal cord injury, bionics and artificial intelligence. Based on the HH model neuron and the DSP Builder technology, in the present study, a single HH model neuron hardware implementation was completed in Field Programmable Gate Array (FPGA). The neuron implemented in FPGA was stimulated by different types of current, the action potential response characteristics were analyzed, and the correlation coefficient between numerical simulation result and hardware implementation result were calculated. The results showed that neuronal action potential response of FPGA was highly consistent with numerical simulation result. This work lays the foundation for hardware implementation of neural network.

  19. Evaluating the Potential Business Benefits of Ecodesign Implementation: A Logic Model Approach

    Directory of Open Access Journals (Sweden)

    Vinícius P. Rodrigues

    2018-06-01

    Full Text Available The business benefits attained from ecodesign programs in manufacturing companies have been regularly documented by several studies from both the academic and corporate spheres. However, there are still significant challenges for adopting ecodesign, especially regarding the evaluation of these potential business benefits prior to the actual ecodesign implementation. To address such gap, this study proposes an exploratory and theory-driven framework based on logic models to support the development of business cases for ecodesign implementation. The objective is to offer an outlook into how ecodesign implementation can potentially affect key corporate performance outcomes. This paper is based on a three-stage research methodology with six steps. Two full systematic literature reviews were performed, along with two thematic analyses and a grounded theory approach with the aim of developing the business case framework, which was then evaluated by seven industry experts. This research contributes to the literature of ecodesign especially by laying out an ecodesign-instantiated logic model, which is readily available to be adapted and customized for further test and use in practice. Discussions on the usefulness and applicability of the framework and directions for future research are presented.

  20. Enablers and inhibitors of the implementation of the Casalud Model, a Mexican innovative healthcare model for non-communicable disease prevention and control.

    Science.gov (United States)

    Tapia-Conyer, Roberto; Saucedo-Martinez, Rodrigo; Mujica-Rosales, Ricardo; Gallardo-Rincon, Hector; Campos-Rivera, Paola Abril; Lee, Evan; Waugh, Craig; Guajardo, Lucia; Torres-Beltran, Braulio; Quijano-Gonzalez, Ursula; Soni-Gallardo, Lidia

    2016-07-22

    The Mexican healthcare system is under increasing strain due to the rising prevalence of non-communicable diseases (especially type 2 diabetes), mounting costs, and a reactive curative approach focused on treating existing diseases and their complications rather than preventing them. Casalud is a comprehensive primary healthcare model that enables proactive prevention and disease management throughout the continuum of care, using innovative technologies and a patient-centred approach. Data were collected over a 2-year period in eight primary health clinics (PHCs) in two states in central Mexico to identify and assess enablers and inhibitors of the implementation process of Casalud. We used mixed quantitative and qualitative data collection tools: surveys, in-depth interviews, and participant and non-participant observations. Transcripts and field notes were analyzed and coded using Framework Analysis, focusing on defining and describing enablers and inhibitors of the implementation process. We identified seven recurring topics in the analyzed textual data. Four topics were categorized as enablers: political support for the Casalud model, alignment with current healthcare trends, ongoing technical improvements (to ease adoption and support), and capacity building. Three topics were categorized as inhibitors: administrative practices, health clinic human resources, and the lack of a shared vision of the model. Enablers are located at PHCs and across all levels of government, and include political support for, and the technological validity of, the model. The main inhibitor is the persistence of obsolete administrative practices at both state and PHC levels, which puts the administrative feasibility of the model's implementation in jeopardy. Constructing a shared vision around the model could facilitate the implementation of Casalud as well as circumvent administrative inhibitors. In order to overcome PHC-level barriers, it is crucial to have an efficient and

  1. Dynamic average modeling of a bidirectional solid state transformer for feasibility studies and real-time implementation

    OpenAIRE

    Martínez Velasco, Juan Antonio; Alepuz Menéndez, Salvador; Gonzalez Molina, Francisco; Martín Arnedo, Jacinto

    2014-01-01

    Detailed switching models of power electronics devices often lead to long computing times, limiting the size of the system to be simulated. This drawback is especially important when the goal is to implement the model in a real-time simulation platform. An alternative is to use dynamic average models (DAM) for analyzing the dynamic behavior of power electronic devices. This paper presents the development of a DAM for a bidirectional solid-state transformer and its implementation in a real-tim...

  2. UKF-based attitude determination method for gyroless satellite

    Institute of Scientific and Technical Information of China (English)

    张红梅; 邓正隆

    2004-01-01

    UKF (unscented Kalman filtering) is a new filtering method suitable to nonlinear systems. The method need not linearize nonlinear systems at the prediction stage of filtering, which is indispensable in EKF (extended Kalman filtering). As a result, the linearization error is avoided, and the filtering accuracy is greatly improved. UKF is applied to the attitude determination for gyroless satellite. Simulations are made to compare the new filter with the traditional EKF.The results indicate that under same conditions, compared with EKF, UKF has faster convergence speed, higher filtering accuracy and more stable estimation performance.

  3. Design and Implementation of Radar Cross-Section Models on a Virtex-6 FPGA

    Directory of Open Access Journals (Sweden)

    B. U. V. Prashanth

    2014-01-01

    Full Text Available The simulation of radar cross-section (RCS models in FPGA is illustrated. The models adopted are the Swerling ones. Radar cross-section (RCS which is also termed as echo area gives the amount of scattered power from a target towards the radar. This paper elucidates the simulation of RCS to represent the specified targets under different conditions, namely, aspect angle and frequency. This model is used for the performance evaluation of radar. RCS models have been developed for various targets like simple objects to complex objects like aircrafts, missiles, tanks, and so forth. First, the model was developed in MATLAB real time simulation environment and after successful verification, the same was implemented in FPGA. Xilinx ISE software was used for VHDL coding. This simulation model was used for the testing of a radar system. The results were compared with MATLAB simulations and FPGA based timing diagrams and RTL synthesis. The paper illustrates the simulation of various target radar cross-section (RCS models. These models are simulated in MATLAB and in FPGA, with the aim of implementing them efficiently on a radar system. This method can be generalized to apply to objects of arbitrary geometry for the two configurations of transmitter and receiver in the same as well as different locations.

  4. Model-based design of RNA hybridization networks implemented in living cells.

    Science.gov (United States)

    Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter; Daròs, José-Antonio; Jaramillo, Alfonso

    2017-09-19

    Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. The Green House Model of Nursing Home Care in Design and Implementation.

    Science.gov (United States)

    Cohen, Lauren W; Zimmerman, Sheryl; Reed, David; Brown, Patrick; Bowers, Barbara J; Nolet, Kimberly; Hudak, Sandra; Horn, Susan

    2016-02-01

    To describe the Green House (GH) model of nursing home (NH) care, and examine how GH homes vary from the model, one another, and their founding (or legacy) NH. Data include primary quantitative and qualitative data and secondary quantitative data, derived from 12 GH/legacy NH organizations February 2012-September 2014. This mixed methods, cross-sectional study used structured interviews to obtain information about presence of, and variation in, GH-relevant structures and processes of care. Qualitative questions explored reasons for variation in model implementation. Interview data were analyzed using related-sample tests, and qualitative data were iteratively analyzed using a directed content approach. GH homes showed substantial variation in practices to support resident choice and decision making; neither GH nor legacy homes provided complete choice, and all GH homes excluded residents from some key decisions. GH homes were most consistent with the model and one another in elements to create a real home, such as private rooms and baths and open kitchens, and in staff-related elements, such as self-managed work teams and consistent, universal workers. Although variation in model implementation complicates evaluation, if expansion is to continue, it is essential to examine GH elements and their outcomes. © Health Research and Educational Trust.

  6. Applying a contingency model of strategic decision making to the implementation of smoking bans: a case study.

    Science.gov (United States)

    Willemsen, M C; Meijer, A; Jannink, M

    1999-08-01

    A model of strategic decision making was applied to study the implementation of worksite smoking policy. This model assumes there is no best way of implementing smoking policies, but that 'the best way' depends on how decision making fits specific content and context factors. A case study at Wehkamp, a mail-order company, is presented to illustrate the usefulness of this model to understand how organizations implement smoking policies. Interview data were collected from representatives of Wehkamp, and pre- and post-ban survey data were collected from employees. After having failed to solve the smoking problem in a more democratic way, Wehkamp's top management choose a highly confrontational and decentralized decision-making approach to implement a complete smoking ban. This resulted in an effective smoking ban, but was to some extent at the cost of employees' satisfaction with the policy and with how the policy was implemented. The choice of implementation approach was contingent upon specific content and context factors, such as managers' perception of the problem, leadership style and legislation. More case studies from different types of companies are needed to better understand how organizational factors affect decision making about smoking bans and other health promotion innovations.

  7. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    Science.gov (United States)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2015-10-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

  8. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    International Nuclear Information System (INIS)

    Setiadi, A C; Brunsell, P R; Frassinetti, L

    2015-01-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM. (paper)

  9. Implementation of a structural dependent model for the superalloy IN738LC in ABAQUS-code

    International Nuclear Information System (INIS)

    Wolters, J.; Betten, J.; Penkalla, H.J.

    1994-05-01

    Superalloys, mainly consisting of nickel, are used for applications in aerospace as well as in stationary gas turbines. In the temperature range above 800 C the blades, which are manufactured of these superalloys, are subjected to high centrifugal forces and thermal induced loads. For computer based analysis of the thermo-mechanical behaviour of the blades models for the stress-strain behaviour are necessary. These models have to give a reliable description of the stress-strain behaviour, with emphasis on inelastic affects. The implementation of the model in finite element codes requires a numerical treatment of the constitutive equations with respect to the given interface of the used code. In this paper constitutive equations for the superalloy IN738LC are presented and the implementation in the finite element code ABAQUS with the numerical preparation of the model is described. In order to validate the model calculations were performed for simple uniaxial loading conditions as well as for a complete cross section of a turbine blade under combined thermal and mechanical loading. The achieved results were compared with those of additional calculations by using ABAQUS, including Norton's law, which was already implemented in this code. (orig.) [de

  10. Implementation of Linus Programme Based on the Model of Van Meter and Van Horn

    Science.gov (United States)

    Sani, Nazariyah bt; Idris, Abdul Rahman

    2013-01-01

    The purpose of this study is to identify the understanding of school leaders on the implementation of LINUS programme that based on the features contained in the Implementation Model of Van Meter and Van Horn (1975). The study was carried out in the form of qualitative method and particularly, the multiple case studies that were conducted in four…

  11. Data Decision-Making and Program-Wide Implementation of the Pyramid Model. Roadmap to Effective Intervention Practices #7

    Science.gov (United States)

    Fox, Lise; Veguilla, Myrna; Perez Binder, Denise

    2014-01-01

    The Technical Assistance Center on Social Emotional Intervention for Young Children (TACSEI) Roadmap on "Data Decision-Making and Program-Wide Implementation of the Pyramid Model" provides programs with guidance on how to collect and use data to ensure the implementation of the Pyramid Model with fidelity and decision-making that…

  12. Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France

    Directory of Open Access Journals (Sweden)

    A. L. Barbu

    2014-01-01

    Full Text Available The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM and leaf area index (LAI. This study investigates the impact of joint assimilation of remotely sensed SSM derived from Advanced Scatterometer (ASCAT backscatter data and the Copernicus Global Land GEOV1 satellite-based LAI product into the the vegetation growth version of the Interactions between Soil Biosphere Atmosphere (ISBA-A-gs land surface model within the the externalised surface model (SURFEX modelling platform of Météo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function matching technique. A multivariate multi-scale land data assimilation system (LDAS based on the extended Kalman Filter (EKF is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the domain of France at a spatial resolution of 8 km. Each model grid box is divided into a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average. In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008–2011. The EKF is able to extract useful information from the data signal at the grid scale and distribute the root-zone soil moisture and LAI increments throughout the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study of the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil

  13. Participatory System Dynamics Modeling: Increasing Stakeholder Engagement and Precision to Improve Implementation Planning in Systems.

    Science.gov (United States)

    Zimmerman, Lindsey; Lounsbury, David W; Rosen, Craig S; Kimerling, Rachel; Trafton, Jodie A; Lindley, Steven E

    2016-11-01

    Implementation planning typically incorporates stakeholder input. Quality improvement efforts provide data-based feedback regarding progress. Participatory system dynamics modeling (PSD) triangulates stakeholder expertise, data and simulation of implementation plans prior to attempting change. Frontline staff in one VA outpatient mental health system used PSD to examine policy and procedural "mechanisms" they believe underlie local capacity to implement evidence-based psychotherapies (EBPs) for PTSD and depression. We piloted the PSD process, simulating implementation plans to improve EBP reach. Findings indicate PSD is a feasible, useful strategy for building stakeholder consensus, and may save time and effort as compared to trial-and-error EBP implementation planning.

  14. Implementation of two-party protocols in the noisy-storage model

    International Nuclear Information System (INIS)

    Wehner, Stephanie; Curty, Marcos; Schaffner, Christian; Lo, Hoi-Kwong

    2010-01-01

    The noisy-storage model allows the implementation of secure two-party protocols under the sole assumption that no large-scale reliable quantum storage is available to the cheating party. No quantum storage is thereby required for the honest parties. Examples of such protocols include bit commitment, oblivious transfer, and secure identification. Here, we provide a guideline for the practical implementation of such protocols. In particular, we analyze security in a practical setting where the honest parties themselves are unable to perform perfect operations and need to deal with practical problems such as errors during transmission and detector inefficiencies. We provide explicit security parameters for two different experimental setups using weak coherent, and parametric down-conversion sources. In addition, we analyze a modification of the protocols based on decoy states.

  15. THE IMPLEMENTATION OF FLIPPED CLASSROOM MODEL IN EFL WRITING

    OpenAIRE

    Rida Afrilyasanti

    2016-01-01

    Flipped classroom is an approach to learning to write that allows teachers to have one-on-one assistance to help learners in the “during writing” stage in the classroom. Theories are given to the students in a video lectures to watch before class. Because problems in writing mostly occur in “during writing” stage, teacher assistance is crucial. This paper aims to share theoretical review and research findings pertaining to the implementation of flipped classroom model to EFL writing. Research...

  16. On the characterization and software implementation of general protein lattice models.

    Directory of Open Access Journals (Sweden)

    Alessio Bechini

    Full Text Available models of proteins have been widely used as a practical means to computationally investigate general properties of the system. In lattice models any sterically feasible conformation is represented as a self-avoiding walk on a lattice, and residue types are limited in number. So far, only two- or three-dimensional lattices have been used. The inspection of the neighborhood of alpha carbons in the core of real proteins reveals that also lattices with higher coordination numbers, possibly in higher dimensional spaces, can be adopted. In this paper, a new general parametric lattice model for simplified protein conformations is proposed and investigated. It is shown how the supporting software can be consistently designed to let algorithms that operate on protein structures be implemented in a lattice-agnostic way. The necessary theoretical foundations are developed and organically presented, pinpointing the role of the concept of main directions in lattice-agnostic model handling. Subsequently, the model features across dimensions and lattice types are explored in tests performed on benchmark protein sequences, using a Python implementation. Simulations give insights on the use of square and triangular lattices in a range of dimensions. The trend of potential minimum for sequences of different lengths, varying the lattice dimension, is uncovered. Moreover, an extensive quantitative characterization of the usage of the so-called "move types" is reported for the first time. The proposed general framework for the development of lattice models is simple yet complete, and an object-oriented architecture can be proficiently employed for the supporting software, by designing ad-hoc classes. The proposed framework represents a new general viewpoint that potentially subsumes a number of solutions previously studied. The adoption of the described model pushes to look at protein structure issues from a more general and essential perspective, making

  17. Optimization models and techniques for implementation and pricing of electricity markets

    International Nuclear Information System (INIS)

    Madrigal Martinez, M.

    2001-01-01

    The operation and planning of vertically integrated electric power systems can be optimized using models that simulate solutions to problems. As the electric power industry is going through a period of restructuring, there is a need for new optimization tools. This thesis describes the importance of optimization tools and presents techniques for implementing them. It also presents methods for pricing primary electricity markets. Three modeling groups are studied. The first considers a simplified continuous and discrete model for power pool auctions. The second considers the unit commitment problem, and the third makes use of a new type of linear network-constrained clearing system model for daily markets for power and spinning reserve. The newly proposed model considers bids for supply and demand and bilateral contracts. It is a direct current model for the transmission network

  18. Implementing model-based system engineering for the whole lifecycle of a spacecraft

    Science.gov (United States)

    Fischer, P. M.; Lüdtke, D.; Lange, C.; Roshani, F.-C.; Dannemann, F.; Gerndt, A.

    2017-09-01

    Design information of a spacecraft is collected over all phases in the lifecycle of a project. A lot of this information is exchanged between different engineering tasks and business processes. In some lifecycle phases, model-based system engineering (MBSE) has introduced system models and databases that help to organize such information and to keep it consistent for everyone. Nevertheless, none of the existing databases approached the whole lifecycle yet. Virtual Satellite is the MBSE database developed at DLR. It has been used for quite some time in Phase A studies and is currently extended for implementing it in the whole lifecycle of spacecraft projects. Since it is unforeseeable which future use cases such a database needs to support in all these different projects, the underlying data model has to provide tailoring and extension mechanisms to its conceptual data model (CDM). This paper explains the mechanisms as they are implemented in Virtual Satellite, which enables extending the CDM along the project without corrupting already stored information. As an upcoming major use case, Virtual Satellite will be implemented as MBSE tool in the S2TEP project. This project provides a new satellite bus for internal research and several different payload missions in the future. This paper explains how Virtual Satellite will be used to manage configuration control problems associated with such a multi-mission platform. It discusses how the S2TEP project starts using the software for collecting the first design information from concurrent engineering studies, then making use of the extension mechanisms of the CDM to introduce further information artefacts such as functional electrical architecture, thus linking more and more processes into an integrated MBSE approach.

  19. Evaluation of an Implementation Model : A National Investigation of VA Residential Programs

    NARCIS (Netherlands)

    Cook, Joan M.; Dinnen, Stephanie; Coyne, James C.; Thompson, Richard; Simiola, Vanessa; Ruzek, Josef; Schnurr, Paula P.

    This national investigation utilizes qualitative data to evaluate an implementation model regarding factors influencing provider use of two evidence-based treatments for posttraumatic stress disorder (PTSD). Semi-structured qualitative interviews with 198 mental health providers from 38 Department

  20. Implementing Modifed Burg Algorithms in Multivariate Subset Autoregressive Modeling

    Directory of Open Access Journals (Sweden)

    A. Alexandre Trindade

    2003-02-01

    Full Text Available The large number of parameters in subset vector autoregressive models often leads one to procure fast, simple, and efficient alternatives or precursors to maximum likelihood estimation. We present the solution of the multivariate subset Yule-Walker equations as one such alternative. In recent work, Brockwell, Dahlhaus, and Trindade (2002, show that the Yule-Walker estimators can actually be obtained as a special case of a general recursive Burg-type algorithm. We illustrate the structure of this Algorithm, and discuss its implementation in a high-level programming language. Applications of the Algorithm in univariate and bivariate modeling are showcased in examples. Univariate and bivariate versions of the Algorithm written in Fortran 90 are included in the appendix, and their use illustrated.

  1. Schmidt-Kalman Filter with Polynomial Chaos Expansion for Orbit Determination of Space Objects

    Science.gov (United States)

    Yang, Y.; Cai, H.; Zhang, K.

    2016-09-01

    Parameter errors in orbital models can result in poor orbit determination (OD) using a traditional Kalman filter. One approach to account for these errors is to consider them in the so-called Schmidt-Kalman filter (SKF), by augmenting the state covariance matrix (CM) with additional parameter covariance rather than additively estimating these so-called "consider" parameters. This paper introduces a new SKF algorithm with polynomial chaos expansion (PCE-SKF). The PCE approach has been proved to be more efficient than Monte Carlo method for propagating the input uncertainties onto the system response without experiencing any constraints of linear dynamics, or Gaussian distributions of the uncertainty sources. The state and covariance needed in the orbit prediction step are propagated using PCE. An inclined geosynchronous orbit scenario is set up to test the proposed PCE-SKF based OD algorithm. The satellite orbit is propagated based on numerical integration, with the uncertain coefficient of solar radiation pressure considered. The PCE-SKF solutions are compared with extended Kalman filter (EKF), SKF and PCE-EKF (EKF with PCE) solutions. It is implied that the covariance propagation using PCE leads to more precise OD solutions in comparison with those based on linear propagation of covariance.

  2. Speed sensorless direct torque control of IMs with rotor resistance estimation

    International Nuclear Information System (INIS)

    Barut, Murat; Bogosyan, Seta; Gokasan, Metin

    2005-01-01

    Direct torque control (DTC) of induction motors (IMs) requires an accurate knowledge on the amplitude and angular position of the controlled flux in addition to the information related to angular velocity for velocity control applications. However, unknown load torque and uncertainties related to stator/rotor resistances due to operating conditions constitute major challenges for the performance of such systems. The determination of stator resistance can be performed by measurements, but methods must be developed for estimation and identification of rotor resistance and load torque. In this study, an EKF based solution is sought for determination of the rotor resistance and load torque as well as the above mentioned states required for DTC. The EKF algorithm used in conjunction with the speed sensorless DTC is tested under eleven scenarios comprised of various changes made in the velocity reference beside the load torque and rotor resistance values assigned in the model. With no a priori information in the estimated states and parameters, it has been demonstrated that the EKF estimation and sensorless DTC perform quite well in spite of the uncertainties and variations imposed on the system

  3. A novel spatiotemporal muscle activity imaging approach based on the Extended Kalman Filter.

    Science.gov (United States)

    Wang, Jing; Zhang, Yingchun; Zhu, Xiangjun; Zhou, Ping; Liu, Chenguang; Rymer, William Z

    2012-01-01

    A novel spatiotemporal muscle activity imaging (sMAI) approach has been developed using the Extended Kalman Filter (EKF) to reconstruct internal muscle activities from non-invasive multi-channel surface electromyogram (sEMG) recordings. A distributed bioelectric dipole source model is employed to describe the internal muscle activity space, and a linear relationship between the muscle activity space and the sEMG measurement space is then established. The EKF is employed to recursively solve the ill-posed inverse problem in the sMAI approach, in which the weighted minimum norm (WMN) method is utilized to calculate the initial state and a new nonlinear method is developed based on the propagating features of muscle activities to predict the recursive state. A series of computer simulations was conducted to test the performance of the proposed sMAI approach. Results show that the localization error rapidly decreases over 35% and the overlap ratio rapidly increases over 45% compared to the results achieved using the WMN method only. The present promising results demonstrate the feasibility of utilizing the proposed EKF-based sMAI approach to accurately reconstruct internal muscle activities from non-invasive sEMG recordings.

  4. Tiered Models of Integrated Academic and Behavioral Support: Effect of Implementation Level on Academic Outcomes

    Science.gov (United States)

    Noltemeyer, Amity; Sansosti, Frank J.

    2012-01-01

    This exploratory study examined (a) Integrated Systems Model (ISM) implementation levels, and (b) the effect of implementation of the academic and behavioral components of ISM on student academic outcomes. Participants included 2,660 students attending six suburban elementary schools. Hierarchical linear regression was conducted using a control…

  5. Comparison of various structural damage tracking techniques with unknown excitations based on experimental data

    Science.gov (United States)

    Huang, Hongwei; Yang, Jann N.; Zhou, Li

    2009-03-01

    An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the LSE with unknown inputs (LSE-UI) and the EKF with unknown inputs (EKF-UI). Also, new analysis methods, referred to as the sequential non-linear least-square estimation with unknown inputs and unknown outputs (SNLSE-UI-UO) and the quadratic sum-square error with unknown inputs (QSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of experimental tests using a small-scale 3-story building model with white noise excitation. The capability of the LSE-UI, EKF-UI, SNLSE-UI-UO and QSSE-UI approaches in tracking the structural damages will be demonstrated.

  6. Applicability evaluation on the conservative metal-water reaction(MWR) model implemented into the SPACE code

    International Nuclear Information System (INIS)

    Lee, Suk Ho; You, Sung Chang; Kim, Han Gon

    2011-01-01

    The SBLOCA (Small Break Loss-of-Coolant Accident) evaluation methodology for the APR1400 (Advanced Power Reactor 1400) is under development using the SPACE code. The goal of the development of this methodology is to set up a conservative evaluation methodology in accordance with Appendix K of 10CFR50 by the end of 2012. In order to develop the Appendix K version of the SPACE code, the code modification is considered through implementation of the code on the required evaluation models. For the conservative models required in the SPACE code, the metal-water reaction (MWR) model, the critical flow model, the Critical Heat Flux (CHF) model and the post-CHF model must be implemented in the code. At present, the integration of the model to generate the Appendix K version of SPACE is in its preliminary stage. Among them, the conservative MWR model and its code applicability are introduced in this paper

  7. Deployment and implementation of the Grundfos' sustainability strategy by means of the ecodesign maturity model

    DEFF Research Database (Denmark)

    Pigosso, Daniela Cristina Antelmi; McAloone, Tim C.; Rozenfeld, Henrique

    2014-01-01

    Companies are increasingly realizing the needs and opportunities for implementing sustainability into their business processes and corporate culture. This paper describes the approach followed by Grundfos to deploy its Sustainability Strategy for the development of Sustainable Product Solutions......, by means of the Ecodesign Maturity Model (EcoM2), which included the diagnosis of their current maturity profile, the definition of a strategic roadmap for ecodesign implementation and the implementation of the defined projects....

  8. The Implementation of Character Education Model Based on Empowerment Theatre for Primary School Students

    Science.gov (United States)

    Anggraini, Purwati; Kusniarti, Tuti

    2016-01-01

    This study aimed at constructing character education model implemented in primary school. The research method was qualitative with five samples in total, comprising primary schools in Malang city/regency and one school as a pilot model. The pilot model was instructed by theatre coach teacher, parents, and school society. The result showed that…

  9. A comparison of two coaching approaches to enhance implementation of a recovery-oriented service model.

    Science.gov (United States)

    Deane, Frank P; Andresen, Retta; Crowe, Trevor P; Oades, Lindsay G; Ciarrochi, Joseph; Williams, Virginia

    2014-09-01

    Moving to recovery-oriented service provision in mental health may entail retraining existing staff, as well as training new staff. This represents a substantial burden on organisations, particularly since transfer of training into practice is often poor. Follow-up supervision and/or coaching have been found to improve the implementation and sustainment of new approaches. We compared the effect of two coaching conditions, skills-based and transformational coaching, on the implementation of a recovery-oriented model following training. Training followed by coaching led to significant sustained improvements in the quality of care planning in accordance with the new model over the 12-month study period. No interaction effect was observed between the two conditions. However, post hoc analyses suggest that transformational coaching warrants further exploration. The results support the provision of supervision in the form of coaching in the implementation of a recovery-oriented service model, and suggest the need to better elucidate the mechanisms within different coaching approaches that might contribute to improved care.

  10. Transmural care in the rehabilitation sector: implementation experiences with a transmural care model for people with spinal cord injury

    Directory of Open Access Journals (Sweden)

    J.H.A. Bloemen-Vrencken

    2005-06-01

    Full Text Available Purposes: The purpose of this article is first to describe the development and content of a transmural care model in the rehabilitation sector, which aims to reduce the number and severity of health problems of people with spinal cord injury (SCI and improve the continuity of care. Second, the purpose is to describe the applicability and implementation experiences of a transmural care model in the rehabilitation sector. Methods: The transmural care model was developed in cooperation with the Dutch Association of Spinal Cord Injured Patients, community nurses, general practitioners, rehabilitation nurses, rehabilitation managers, physiatrists and researchers. The core component of the care model consists of a transmural nurse, who ‘liaises’ between people with SCI living in the community, professional primary care professionals and the rehabilitation centre. The transmural care model provides a job description containing activities to support people with SCI and their family/partners and activities to promote continuity of care. The transmural care model was implemented in two Dutch rehabilitation centres. The following three aspects, as experienced by the transmural nurses, were evaluated: the extent to which the care model was implemented; enabling factors and barriers for implementation; strength and weakness of the care model. Results: The transmural care model was not implemented in all its details, with a clear difference between the two rehabilitation centres. Enabling factors and barriers for implementation were found at three levels: 1. the level of the individual professional (e.g. competencies, attitude and motivation, 2. the organisational and financing level (e.g. availability of facilities and finances, and 3. the social context (the opinion of colleagues, managers and other professionals involved with the care. The most important weakness experienced was that there was not enough time to put all the activities into practice

  11. L70 life prediction for solid state lighting using Kalman Filter and Extended Kalman Filter based models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, Lynn

    2013-08-08

    Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life

  12. A new state-space model for three-phase systems for Kalman filtering with application to power quality estimation

    Science.gov (United States)

    Phan, Anh Tuan; Ho, Duc Du; Hermann, Gilles; Wira, Patrice

    2015-12-01

    For power quality issues like reducing harmonic pollution, reactive power and load unbalance, the estimation of the fundamental frequency of a power lines in a fast and precise way is essential. This paper introduces a new state-space model to be used with an extended Kalman filter (EKF) for estimating the frequency of distorted power system signals in real-time. The proposed model takes into account all the characteristics of a general three-phase power system and mainly the unbalance. Therefore, the symmetrical components of the power system, i.e., their amplitude and phase angle values, can also be deduced at each iteration from the proposed state-space model. The effectiveness of the method has been evaluated. Results and comparisons of online frequency estimation and symmetrical components identification show the efficiency of the proposed method for disturbed and time-varying signals.

  13. Implementing Marzano's Model: The Reality of Educational Leadership and School Reform

    Science.gov (United States)

    Keaveny, Stacy M.

    2013-01-01

    Federal and state guidelines for school reform dominate the landscape of public education. Florida and its school districts, as a Race to the Top state, are in the process of fully implementing a value-added model of teacher evaluation. Effective school leaders are calling upon the theoretical framework of transformational, visionary and…

  14. Finite element implementation of the Hoek-Brown material model with general strain softening behavior

    DEFF Research Database (Denmark)

    Sørensen, Emil Smed; Clausen, Johan Christian; Damkilde, Lars

    2015-01-01

    A numerical implementation of the Hoek–Brown criterion is presented, which is capable of modeling different post-failure behaviors observed in jointed rock mass. This is done by making the material parameters a function of the accumulated plastic strain. The implementation is for use in finite...... for perfectly-plastic, brittle and strain softening material behavior and the results are compared with known solutions....

  15. A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments.

    Science.gov (United States)

    Allen, Marcus; Zhong, Qiang; Kirsch, Nicholas; Dani, Ashwin; Clark, William W; Sharma, Nitin

    2017-12-01

    Miniature inertial measurement units (IMUs) are wearable sensors that measure limb segment or joint angles during dynamic movements. However, IMUs are generally prone to drift, external magnetic interference, and measurement noise. This paper presents a new class of nonlinear state estimation technique called state-dependent coefficient (SDC) estimation to accurately predict joint angles from IMU measurements. The SDC estimation method uses limb dynamics, instead of limb kinematics, to estimate the limb state. Importantly, the nonlinear limb dynamic model is formulated into state-dependent matrices that facilitate the estimator design without performing a Jacobian linearization. The estimation method is experimentally demonstrated to predict knee joint angle measurements during functional electrical stimulation of the quadriceps muscle. The nonlinear knee musculoskeletal model was identified through a series of experiments. The SDC estimator was then compared with an extended kalman filter (EKF), which uses a Jacobian linearization and a rotation matrix method, which uses a kinematic model instead of the dynamic model. Each estimator's performance was evaluated against the true value of the joint angle, which was measured through a rotary encoder. The experimental results showed that the SDC estimator, the rotation matrix method, and EKF had root mean square errors of 2.70°, 2.86°, and 4.42°, respectively. Our preliminary experimental results show the new estimator's advantage over the EKF method but a slight advantage over the rotation matrix method. However, the information from the dynamic model allows the SDC method to use only one IMU to measure the knee angle compared with the rotation matrix method that uses two IMUs to estimate the angle.

  16. An optical model for implementing Parrondo’s game and designing stochastic game with long-term memory

    International Nuclear Information System (INIS)

    Si Tieyan

    2012-01-01

    Highlights: ► Using a photon propagating through a designed array of beam splitters to simulate Parrondo’s game paradox. ► Design the optical flowchart for implementing Parrondo history-dependent game paradox. ► Design new game with long-term memory on a designed tree lattice and loop lattice. - Abstract: An optical model for a photon propagating through a designed array of beam splitters is developed to give a physical implementation of Parrondo’s game and Parrondo’s history-dependent game. The winner in this optical model is a photon passed the beam splitter. The loser is a photon being reflected by the beam splitter. The optical beam splitter is the coin-tosser. We designed new games with long-term memory by using this optical diagram method. The optical output of the combined game of two losing games could be a win, or a loss, or an oscillation between win and loss. The modern technology to implement this optical model is well developed. A circularly polarized photon is a possible candidate for this physical implementation in laboratory.

  17. Improving Safe Sleep Modeling in the Hospital through Policy Implementation.

    Science.gov (United States)

    Heitmann, Rachel; Nilles, Ester K; Jeans, Ashley; Moreland, Jackie; Clarke, Chris; McDonald, Morgan F; Warren, Michael D

    2017-11-01

    Introduction Sleep-related infant deaths are major contributors to Tennessee's high infant mortality rate. The purpose of this initiative was to evaluate the impact of policy-based efforts to improve modeling of safe sleep practices by health care providers in hospital settings across Tennessee. Methods Safe sleep policies were developed and implemented at 71 hospitals in Tennessee. Policies, at minimum, were required to address staff training on the American Academy of Pediatrics' safe sleep recommendations, correct modeling of infant safe sleep practices, and parent education. Hospital data on process measures related to training and results of crib audits were compiled for analysis. Results The overall observance of infants who were found with any risk factors for unsafe sleep decreased 45.6% (p ≤ 0.001) from the first crib audit to the last crib audit. Significant decreases were noted for specific risk factors, including infants found asleep not on their back, with a toy or object in the crib, and not sleeping in a crib. Significant improvements were observed at hospitals where printed materials or video were utilized for training staff compared to face-to-face training. Discussion Statewide implementation of the hospital policy intervention resulted in significant reductions in infants found in unsafe sleep situations. The most common risk factors for sleep-related infant deaths can be modeled in hospitals. This effort has the potential to reduce sleep-related infant deaths and ultimately infant mortality.

  18. State-of-charge inconsistency estimation of lithium-ion battery pack using mean-difference model and extended Kalman filter

    Science.gov (United States)

    Zheng, Yuejiu; Gao, Wenkai; Ouyang, Minggao; Lu, Languang; Zhou, Long; Han, Xuebing

    2018-04-01

    State-of-charge (SOC) inconsistency impacts the power, durability and safety of the battery pack. Therefore, it is necessary to measure the SOC inconsistency of the battery pack with good accuracy. We explore a novel method for modeling and estimating the SOC inconsistency of lithium-ion (Li-ion) battery pack with low computation effort. In this method, a second-order RC model is selected as the cell mean model (CMM) to represent the overall performance of the battery pack. A hypothetical Rint model is employed as the cell difference model (CDM) to evaluate the SOC difference. The parameters of mean-difference model (MDM) are identified with particle swarm optimization (PSO). Subsequently, the mean SOC and the cell SOC differences are estimated by using extended Kalman filter (EKF). Finally, we conduct an experiment on a small Li-ion battery pack with twelve cells connected in series. The results show that the evaluated SOC difference is capable of tracking the changing of actual value after a quick convergence.

  19. AUTOMATIC TEXTURE MAPPING WITH AN OMNIDIRECTIONAL CAMERA MOUNTED ON A VEHICLE TOWARDS LARGE SCALE 3D CITY MODELS

    Directory of Open Access Journals (Sweden)

    F. Deng

    2012-07-01

    Full Text Available Today high resolution panoramic images with competitive quality have been widely used for rendering in some commercial systems. However the potential applications such as mapping, augmented reality and modelling which need accurate orientation information are still poorly studied. Urban models can be quickly obtained from aerial images or LIDAR, however with limited quality or efficiency due to low resolution textures and manual texture mapping work flow. We combine an Extended Kalman Filter (EKF with the traditional Structure from Motion (SFM method without any prior information based on a general camera model which can handle various kinds of omnidirectional and other kind of single perspective image sequences even with unconnected or weakly connected frames. The orientation results is then applied to mapping the textures from panoramas to the existing building models obtained from aerial photogrammetry. It turns out to largely improve the quality of the models and the efficiency of the modelling procedure.

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

    Science.gov (United States)

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

    2018-07-01

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

  1. Implementation of wall film condensation model to two-fluid model in component thermal hydraulic analysis code CUPID - 15237

    International Nuclear Information System (INIS)

    Lee, J.H.; Park, G.C.; Cho, H.K.

    2015-01-01

    In the containment of a nuclear reactor, the wall condensation occurs when containment cooling system and structures remove the mass and energy release and this phenomenon is of great importance to ensure containment integrity. If the phenomenon occurs in the presence of non-condensable gases, their accumulation near the condensate film leads to significant reduction in heat transfer during the condensation. This study aims at simulating the wall film condensation in the presence of non-condensable gas using CUPID, a computational multi-fluid dynamics code, which is developed by the Korea Atomic Energy Research Institute (KAERI) for the analysis of transient two-phase flows in nuclear reactor components. In order to simulate the wall film condensation in containment, the code requires a proper wall condensation model and liquid film model applicable to the analysis of the large scale system. In the present study, the liquid film model and wall film condensation model were implemented in the two-fluid model of CUPID. For the condensation simulation, a wall function approach with heat and mass transfer analogy was applied in order to save computational time without considerable refinement for the boundary layer. This paper presents the implemented wall film condensation model and then, introduces the simulation result using CUPID with the model for a conceptual condensation problem in a large system. (authors)

  2. UAV State Estimation Modeling Techniques in AHRS

    Science.gov (United States)

    Razali, Shikin; Zhahir, Amzari

    2017-11-01

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

  3. Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

    Directory of Open Access Journals (Sweden)

    Jinwei Wang

    2014-01-01

    Full Text Available The active appearance model (AAM is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

  4. Implicit implementation and consistent tangent modulus of a viscoplastic model for polymers

    OpenAIRE

    ACHOUR-RENAULT, Nadia; CHATZIGEORGIOU, George; MERAGHNI, Fodil; CHEMISKY, Yves; FITOUSSI, Joseph

    2015-01-01

    In this work, the phenomenological viscoplastic DSGZ model[Duan, Y., Saigal, A., Greif, R., Zimmerman, M. A., 2001. A Uniform Phenomenological Constitutive Model for Glassy and Semicrystalline Polymers. Polymer Engineering and Science 41 (8), 1322-1328], developed for glassy or semi-crystalline polymers, is numerically implemented in a three dimensional framework, following an implicit formulation. The computational methodology is based on the radial return mapping algorithm. This implicit fo...

  5. A Conceptual Model for Production Leveling (Heijunka) Implementation in Batch Production Systems

    OpenAIRE

    De Araujo , Luciano Fonseca; De Queiroz , Abelardo Alves

    2009-01-01

    International audience; This paper explains an implementation model for a new method for Production Leveling designed for batch production system. The main structure of this model is grounded on three constructs: traditional framework for Operations Planning, Lean Manufacturing concepts for Production Leveling and case study guidelines. By combining the first and second construct, a framework for Production Leveling has been developed for batch production systems. Then, case study guidelines ...

  6. Systems Intelligence in Knowledge Management Implementation: A Momentum of the SECI Model

    OpenAIRE

    Sasaki, Yasuo

    2014-01-01

    This paper discusses the role of systems intelligence in knowledge management implementations, in particular, in the SECI model, a widely acknowledged knowledge creation process in an organization identified by Nonaka and Takeuchi (1995). The SECI model deals with interactions and conversions of tacit knowledge and explicit knowledge and mainly consists of four stages. The author illustrates systems intelligence, a certain kind of human intelligence focusing on systems thinking perspective pr...

  7. Efficient Implementation Algorithms for Homogenized Energy Models

    National Research Council Canada - National Science Library

    Braun, Thomas R; Smith, Ralph C

    2005-01-01

    ... for real-time control implementation. In this paper, we develop algorithms employing lookup tables which permit the high speed implementation of formulations which incorporate relaxation mechanisms and electromechanical coupling...

  8. Earth Observations, Models and Geo-Design in Support of SDG Implementation and Monitoring

    Science.gov (United States)

    Plag, H. P.; Jules-Plag, S.

    2016-12-01

    Implementation and Monitoring of the United Nations' Sustainable Development Goals (SDGs) requires support from Earth observation and scientific communities. Applying a goal-based approach to determine the data needs to the Targets and Indicators associated with the SDGs demonstrates that integration of environmental with socio-economic and statistical data is required. Large data gaps exist for the built environment. A Geo-Design platform can provide the infrastructure and conceptual model for the data integration. The development of policies and actions to foster the implementation of SDGs in many cases requires research and the development of tools to answer "what if" questions. Here, agent-based models and model webs combined with a Geo-Design platform are promising avenues. This advanced combined infrastructure can also play a crucial role in the necessary capacity building. We will use the example of SDG 5 (Gender equality) to illustrate these approaches. SDG 11 (Sustainable Cities and Communities) is used to underline the cross-goal linkages and the joint benefits of Earth observations, data integration, and modeling tools for multiple SDGs.

  9. Using structural equation modelling to integrate human resources with internal practices for lean manufacturing implementation

    Directory of Open Access Journals (Sweden)

    Protik Basu

    2018-01-01

    Full Text Available The purpose of this paper is to explore and integrate the role of human resources with the internal practices of the Indian manufacturing industries towards successful implementation of lean manu-facturing (LM. An extensive literature survey is carried out. An attempt is made to build an ex-haustive list of all the input manifests related to human resources and internal practices necessary for LM implementation, coupled with a similar exhaustive list of the benefits accrued from its suc-cessful implementation. A structural model is thus conceptualized, which is empirically validated based on the data from the Indian manufacturing sector. Hardly any survey based empirical study in India has been found to integrate human resources with the internal processes towards success-ful LM implementation. This empirical research is thus carried out in the Indian manufacturing in-dustries. The analysis reveals six key input constructs and three output constructs, indicating that these constructs should act in unison to maximize the benefits of implementing lean. The structural model presented in this paper may be treated as a guide to integrate human resources with internal practices to successfully implement lean, leading to an optimum utilization of resources. This work is one of the very first researches to have a survey-based empirical analysis of the role of human resources and internal practices of the Indian manufacturing sector towards an effective lean im-plementation.

  10. More performance results and implementation of an object oriented track reconstruction model in different OO frameworks

    International Nuclear Information System (INIS)

    Gaines, Irwin; Qian Sijin

    2001-01-01

    This is an update of the report about an Object Oriented (OO) track reconstruction model, which was presented in the previous AIHENP'99 at Crete, Greece. The OO model for the Kalman filtering method has been designed for high energy physics experiments at high luminosity hadron colliders. It has been coded in the C++ programming language and successfully implemented into a few different OO computing environments of the CMS and ATLAS experiments at the future Large Hadron Collider at CERN. We shall report: (1) more performance result: (2) implementing the OO model into the new SW OO framework 'Athena' of ATLAS experiment and some upgrades of the OO model itself

  11. Towards a Maturity Modeling Approach for the Implementation of Industrial Internet

    DEFF Research Database (Denmark)

    Menon, Karan; Kärkkäinen, Hannu; Lasrado, Lester Allan

    2016-01-01

    guidelines for industrial internet maturity model for mass production manufacturing industries which use heavy equipment. The detailed research design presented here uses ADR methodology to enable the construction of the ensemble artefact. The industrial internet maturity model will be tested, developed......This Research-in-Progress paper facilitates the design and provides guidelines for the development of a maturity model to achieve a coordinated, systematic and stepwise adoption of industrial internet, thus enabling the industrial internet to be used to its full potential in manufacturing...... enterprises. Using analogous maturity models from the fields of supply chain management and product lifecycle maturity among others, this paper explains why a maturity model approach would facilitate the step-by-step implementation of industrial internet. The paper goes on to provide systematic design...

  12. Implementing a continuum of care model for older people - results from a Swedish case study

    Directory of Open Access Journals (Sweden)

    Anna Duner

    2011-11-01

    Full Text Available Introduction: There is a need for integrated care and smooth collaboration between care-providing organisations and professions to create a continuum of care for frail older people. However, collaboration between organisations and professions is often problematic. The aim of this study was to examine the process of implementing a new continuum of care model in a complex organisational context, and illuminate some of the challenges involved. The introduced model strived to connect three organisations responsible for delivering health and social care to older people: the regional hospital, primary health care and municipal eldercare.Methods: The actions of the actors involved in the process of implementing the model were understood to be shaped by the actors' understanding, commitment and ability. This article is based on 44 qualitative interviews performed on four occasions with 26 key actors at three organisational levels within these three organisations.Results and conclusions: The results point to the importance of paying regard to the different cultures of the organisations when implementing a new model. The role of upper management emerged as very important. Furthermore, to be accepted, the model has to be experienced as effectively dealing with real problems in the everyday practice of the actors in the organisations, from the bottom to the top.

  13. Implementing a continuum of care model for older people - results from a Swedish case study

    Directory of Open Access Journals (Sweden)

    Anna Duner

    2011-11-01

    Full Text Available Introduction: There is a need for integrated care and smooth collaboration between care-providing organisations and professions to create a continuum of care for frail older people. However, collaboration between organisations and professions is often problematic. The aim of this study was to examine the process of implementing a new continuum of care model in a complex organisational context, and illuminate some of the challenges involved. The introduced model strived to connect three organisations responsible for delivering health and social care to older people: the regional hospital, primary health care and municipal eldercare. Methods: The actions of the actors involved in the process of implementing the model were understood to be shaped by the actors' understanding, commitment and ability. This article is based on 44 qualitative interviews performed on four occasions with 26 key actors at three organisational levels within these three organisations. Results and conclusions: The results point to the importance of paying regard to the different cultures of the organisations when implementing a new model. The role of upper management emerged as very important. Furthermore, to be accepted, the model has to be experienced as effectively dealing with real problems in the everyday practice of the actors in the organisations, from the bottom to the top.

  14. A Sand Cone Model of Lean Implementation

    OpenAIRE

    Yestemessov, Azamat

    2011-01-01

    Over the past 20 years Lean Production system has been a focus of researches by different academicians. A numerous works have been written in the field of Lean implementation in manufacturing companies. However, as shown, most of the academic topics relate to the issues of implementing Lean tools and techniques. Critical Success Factors have been also described widely; however, no efforts in systematization have been made. Only several works have a focus on integration of Lean implementation ...

  15. Design and implementation of segment oriented spatio-temporal model in urban panoramic maps

    Science.gov (United States)

    Li, Haiting; Fei, Lifan; Peng, Qingshan; Li, Yanhong

    2009-10-01

    Object-oriented spatio-temporal model is directed by human cognition that each object has what/where/when attributes. The precise and flexible structure of such models supports multi-semantics of space and time. This paper reviews current research of spatio-temporal models using object-oriented approach and proposed a new spatio-temporal model based on segmentation in order to resolve the updating problem of some special GIS system by taking advantages of object-oriented spatio-temporal model and adopting category theory. Category theory can be used as a unifying framework for specifying complex systems and it provides rules on how objects may be joined. It characterizes the segments of object through mappings between them. The segment-oriented spatio-temporal model designed for urban panoramic maps is described and implemented. We take points and polylines as objects in this model in the management of panoramic map data. For the randomness of routes which transportation vehicle adopts each time, road objects in this model are split into some segments by crossing points. The segments still remains polyline type, but the splitting makes it easier to update the panoramic data when new photos are captured. This model is capable of eliminating redundant data and accelerating data access when panoramas are unchanged. For evaluation purpose, the data types and operations are designed and implemented in PostgreSQL and the results of experiments come out to prove that this model is efficient and expedient in the application of urban panoramic maps.

  16. THE IMPLEMENTATION OF THE 5E MODEL STAGES TO BUILD STUDENTS’ VOCABULARY

    Directory of Open Access Journals (Sweden)

    Muhammad Rochman

    2015-12-01

    Full Text Available There are stages of human to learn something. In early ages, they will learn simplest things to the complicated ones. A learning process of human is started with and introductory and it tries to connect with their prior knowledge to the new one. Children begin to curious about what they want to know and start to make some questions about what they want to know. In the process of finding the answers of their own questions, they will interact with others and try to share the knowledge in this process. The result of this study illustrates that the implementation of the 5E model in teaching vocabulary that can enhance the students’ vocabulary achievement and successfully encourages them to actively and enthusiastically take part in the teaching-learning process of vocabulary through group task. Keywords: implementation, vocabulary, vocabulary course, and 5E model

  17. Application of Consider Covariance to the Extended Kalman Filter

    Science.gov (United States)

    Lundberg, John B.

    1996-01-01

    The extended Kalman filter (EKF) is the basis for many applications of filtering theory to real-time problems where estimates of the state of a dynamical system are to be computed based upon some set of observations. The form of the EKF may vary somewhat from one application to another, but the fundamental principles are typically unchanged among these various applications. As is the case in many filtering applications, models of the dynamical system (differential equations describing the state variables) and models of the relationship between the observations and the state variables are created. These models typically employ a set of constants whose values are established my means of theory or experimental procedure. Since the estimates of the state are formed assuming that the models are perfect, any modeling errors will affect the accuracy of the computed estimates. Note that the modeling errors may be errors of commission (errors in terms included in the model) or omission (errors in terms excluded from the model). Consequently, it becomes imperative when evaluating the performance of real-time filters to evaluate the effect of modeling errors on the estimates of the state.

  18. New model of enterprises resource planning implementation planning process in manufacturing enterprises

    Directory of Open Access Journals (Sweden)

    Mirjana Misita

    2016-05-01

    Full Text Available This article presents new model of enterprises resource planning implementation planning process in manufacturing enterprises based on assessment of risk sources. This assessment was performed by applying analytic hierarchy process. Analytic hierarchy process method allows variation of relative importance of specific risk sources dependent on the section from which the risk source originates (organizational environment, technical issues, people issues, adoption process management, and external support. Survey was conducted on 85 manufacturing enterprises involved with an enterprises resource planning solution. Ranking of risk sources assessments returns most frequent risks of enterprises resource planning implementation success in manufacturing enterprises, and representative factors were isolated through factor analysis by risk source origin. Finally, results indicate that there are hidden causes of failed implementation, for example, risk source “top management training and education,” from risk origin “adoption process management.”

  19. Implementation, availability and regulatory status of an OECD accepted Reconstructed Human Epidermis model in Brazil

    Directory of Open Access Journals (Sweden)

    Rodrigo De Vecchi

    2018-02-01

    Full Text Available Introduction: In 2014, Brazil has joined the growing list of countries to ban cosmetic products from being tested on animal models. The new legislation comes into force in 2019. As a result, the interest for validated alternative testing methods for safety assessment has been increasing in academia, industry and associations. However, the lack of specific legislation on the use of biological material of human origin for toxicological tests makes the access to alternative in vitro models difficult. Furthermore, importation to Brazil is not possible on timely manner. Method: In this article, we report the implementation process of a Reconstructed Human Epidermis (SkinEthic™ RHE, an alternative model internationally accepted by OECD, through a technology transfer from EPISKIN® Lyon to Brazil. Regulatory evolution has been motivating the implementation and wide use of alternative methods to animal testing in several industry segments including cosmetic and pharmaceutical. Results: Protocol has been shown to be robust and highly reproducible. Quality control parameters (histological analysis, barrier function test and tissue viability were performed on 24 batches assembled in Brazil. SkinEthic™ RHE model use allows the full replacement of animal test methods for skin hazards identification. It has regulatory acceptance for several toxicological endpoints, such as the Draize test for skin irritation and corrosion. It allows the reduction and refining of pre-clinical protocols through tiered strategies. Implementation of SkinEthic™ RHE protocol is just a first and important step towards a new approach of toxicological safety testing in Brazil. Conclusion: The implementation was successfully done and reported here. However, in order to follow completely the new legislation up to 2019, the availability of validated models is essential. Quality control tests done on RHE batches produced in Brazil demonstrate that the model met OECD acceptance

  20. Moving source localization with a single hydrophone using multipath time delays in the deep ocean.

    Science.gov (United States)

    Duan, Rui; Yang, Kunde; Ma, Yuanliang; Yang, Qiulong; Li, Hui

    2014-08-01

    Localizing a source of radial movement at moderate range using a single hydrophone can be achieved in the reliable acoustic path by tracking the time delays between the direct and surface-reflected arrivals (D-SR time delays). The problem is defined as a joint estimation of the depth, initial range, and speed of the source, which are the state parameters for the extended Kalman filter (EKF). The D-SR time delays extracted from the autocorrelation functions are the measurements for the EKF. Experimental results using pseudorandom signals show that accurate localization results are achieved by offline iteration of the EKF.

  1. Quebec mental health services networks: models and implementation

    Directory of Open Access Journals (Sweden)

    Marie-Josée Fleury

    2005-06-01

    Full Text Available Purpose: In the transformation of health care systems, the introduction of integrated service networks is considered to be one of the main solutions for enhancing efficiency. In the last few years, a wealth of literature has emerged on the topic of services integration. However, the question of how integrated service networks should be modelled to suit different implementation contexts has barely been touched. To fill that gap, this article presents four models for the organization of mental health integrated networks. Data sources: The proposed models are drawn from three recently published studies on mental health integrated services in the province of Quebec (Canada with the author as principal investigator. Description: Following an explanation of the concept of integrated service network and a description of the Quebec context for mental health networks, the models, applicable in all settings: rural, urban or semi-urban, and metropolitan, and summarized in four figures, are presented. Discussion and conclusion: To apply the models successfully, the necessity of rallying all the actors of a system, from the strategic, tactical and operational levels, according to the type of integration involved: functional/administrative, clinical and physician-system is highlighted. The importance of formalizing activities among organizations and actors in a network and reinforcing the governing mechanisms at the local level is also underlined. Finally, a number of integration strategies and key conditions of success to operationalize integrated service networks are suggested.

  2. Modelling and implementation of the “6D” beam-beam interaction

    CERN Document Server

    Iadarola, Giovanni; Papaphilippou, Yannis

    2018-01-01

    These slides illustrate the numerical modelling of a beam-beam interaction using the “Synchro Beam Mapping” approach. The employed description of the strong beam allows correctly accounting for the hour-glass effect as well as for linear coupling at the interaction point. The implementation of the method within the SixTrack code is reviewed and tested.

  3. A review of BIM (Building Information Modeling) implementation in Indonesia construction industry

    Science.gov (United States)

    Suryadinata Telaga, Abdi

    2018-05-01

    Construction projects in Indonesia have been growing rapidly in the last three years. Therefore, construction management is very important to ensure completion of construction projects are within schedule and budget. Utilization of building information modeling (BIM) can increase the efficiency of a construction project. However, the implementation of BIM in Indonesia is still not known. This paper is intended to review the implementation of BIM in Indonesia through literature analysis. To find BIM articles in Indonesia, Firstly, searching was limited to English articles published in reputed journals or conferences. However the results were limited, then the search was expanded to the article using Indonesian languages that published in journal and conference. Based on the number of articles, the results showed that BIM research in Indonesia is still in a dearth. Furthermore, BIM study cases were conducted in a limited location and within a small population. Nevertheless, the literature shared the conclusion that BIM can increase project efficiency, but the implementation was hindered by high initial investment cost, inadequate human resources, small demand, and technology resistant. The research contributes to providing a current reported level of BIM implementation in Indonesia. In the future research to study of BIM implementation comprehensively in Indonesia is eminent.

  4. Qualitative performance comparison of reactivity estimation between the extended Kalman filter technique and the inverse point kinetic method

    International Nuclear Information System (INIS)

    Shimazu, Y.; Rooijen, W.F.G. van

    2014-01-01

    Highlights: • Estimation of the reactivity of nuclear reactor based on neutron flux measurements. • Comparison of the traditional method, and the new approach based on Extended Kalman Filtering (EKF). • Estimation accuracy depends on filter parameters, the selection of which is described in this paper. • The EKF algorithm is preferred if the signal to noise ratio is low (low flux situation). • The accuracy of the EKF depends on the ratio of the filter coefficients. - Abstract: The Extended Kalman Filtering (EKF) technique has been applied for estimation of subcriticality with a good noise filtering and accuracy. The Inverse Point Kinetic (IPK) method has also been widely used for reactivity estimation. The important parameters for the EKF estimation are the process noise covariance, and the measurement noise covariance. However the optimal selection is quite difficult. On the other hand, there is only one parameter in the IPK method, namely the time constant for the first order delay filter. Thus, the selection of this parameter is quite easy. Thus, it is required to give certain idea for the selection of which method should be selected and how to select the required parameters. From this point of view, a qualitative performance comparison is carried out

  5. Noninvasive estimation of global activation sequence using the extended Kalman filter.

    Science.gov (United States)

    Liu, Chenguang; He, Bin

    2011-03-01

    A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the "predict" procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.

  6. What Determines Lean Manufacturing Implementation? A CB-SEM Model

    Directory of Open Access Journals (Sweden)

    Tan Ching Ng

    2018-02-01

    Full Text Available This research aims to ascertain the determinants of effective Lean Manufacturing (LM. In this research, Covariance-based Structural Equation Modeling (CB-SEM analysis will be used in order to analyze the determinants. Through CB-SEM analysis, the significant key determinants can be determined and the direct relationships among determinants can be analyzed. Thus, the findings of this research can act as guidelines for achievement of LM effectiveness, not only providing necessary steps for successful implementation of lean, but also helping lean companies to achieve higher level of lean cost and time savings.

  7. A Robust Method to Detect Zero Velocity for Improved 3D Personal Navigation Using Inertial Sensors

    Science.gov (United States)

    Xu, Zhengyi; Wei, Jianming; Zhang, Bo; Yang, Weijun

    2015-01-01

    This paper proposes a robust zero velocity (ZV) detector algorithm to accurately calculate stationary periods in a gait cycle. The proposed algorithm adopts an effective gait cycle segmentation method and introduces a Bayesian network (BN) model based on the measurements of inertial sensors and kinesiology knowledge to infer the ZV period. During the detected ZV period, an Extended Kalman Filter (EKF) is used to estimate the error states and calibrate the position error. The experiments reveal that the removal rate of ZV false detections by the proposed method increases 80% compared with traditional method at high walking speed. Furthermore, based on the detected ZV, the Personal Inertial Navigation System (PINS) algorithm aided by EKF performs better, especially in the altitude aspect. PMID:25831086

  8. Bds/gps Integrated Positioning Method Research Based on Nonlinear Kalman Filtering

    Science.gov (United States)

    Ma, Y.; Yuan, W.; Sun, H.

    2017-09-01

    In order to realize fast and accurate BDS/GPS integrated positioning, it is necessary to overcome the adverse effects of signal attenuation, multipath effect and echo interference to ensure the result of continuous and accurate navigation and positioning. In this paper, pseudo-range positioning is used as the mathematical model. In the stage of data preprocessing, using precise and smooth carrier phase measurement value to promote the rough pseudo-range measurement value without ambiguity. At last, the Extended Kalman Filter(EKF), the Unscented Kalman Filter(UKF) and the Particle Filter(PF) algorithm are applied in the integrated positioning method for higher positioning accuracy. The experimental results show that the positioning accuracy of PF is the highest, and UKF is better than EKF.

  9. Implementing Strategy in a Budget: A Model of the Coast Guard Reserve

    OpenAIRE

    Bromund, Carl Douglas

    1990-01-01

    Approved for public release; distribution is unlimited. This thesis discusses the managment strategy of the Coast Guard Reserve; it examines the formulation and implmentation of strateqy. A model to develop and implement strategy is proposed, which defines the role of the budget in this strategic management process. The recent strategy of the Coast Guard Reserve is analyzed using this model.. This analysis seems to indicate that the Coast Guard Reserve had no explicit strate...

  10. Control of a Quadrotor Using a Smart Self-Tuning Fuzzy PID Controller

    Directory of Open Access Journals (Sweden)

    Deepak Gautam

    2013-11-01

    Full Text Available This paper deals with the modelling, simulation-based controller design and path planning of a four rotor helicopter known as a quadrotor. All the drags, aerodynamic, coriolis and gyroscopic effect are neglected. A Newton-Euler formulation is used to derive the mathematical model. A smart self-tuning fuzzy PID controller based on an EKF algorithm is proposed for the attitude and position control of the quadrotor. The PID gains are tuned using a self-tuning fuzzy algorithm. The self-tuning of fuzzy parameters is achieved based on an EKF algorithm. A smart selection technique and exclusive tuning of active fuzzy parameters is proposed to reduce the computational time. Dijkstra's algorithm is used for path planning in a closed and known environment filled with obstacles and/or boundaries. The Dijkstra algorithm helps avoid obstacle and find the shortest route from a given initial position to the final position.

  11. An efficient implementation of maximum likelihood identification of LTI state-space models by local gradient search

    NARCIS (Netherlands)

    Bergboer, N.H.; Verdult, V.; Verhaegen, M.H.G.

    2002-01-01

    We present a numerically efficient implementation of the nonlinear least squares and maximum likelihood identification of multivariable linear time-invariant (LTI) state-space models. This implementation is based on a local parameterization of the system and a gradient search in the resulting

  12. An H(∞) approach for elasticity properties reconstruction.

    Science.gov (United States)

    Liu, Huafeng; Hu, Hongjie; Sinusas, Albert J; Shi, Pengcheng

    2012-01-01

    Quantification of object elasticity properties has significant technical implications as well as important practical applications, such as medical disease diagnosis. In general, given noisy measurements on the kinematic states of the objects from imaging data, the aim is to recover the elasticity parameters for assumed material constitutive models of the objects. The implementation is complicated caused by the large dimensionality of the parameters. Various versions of the least-square (LS) methods have been widely used, which, however, do not perform well under reasonably realistic levels of disturbances. Another popular strategy, based on the extended Kalman filter (EKF), is also far from optimal and subject to divergence if either the initializations are poor or the noises are not Gaussian. In this paper, the authors propose a robust system identification paradigm for the quantitative analysis of object elasticity. It is derived and extended from the H(∞) filtering principles and is particularly powerful for real-world situations where the types and levels of the disturbances are unknown. Using synthetic data, the authors investigate the sensitivity of the strategies toward different types (Gaussian and Poisson) and levels of noises, as well as various initializations. The experimental results show consistently superior performance of the proposed method over the LS and EKF algorithms in reliably identifying object elastic modulus distributions. Results from phase contrast imaging data of canine hearts and human MRI data are also presented, which demonstrate the power of the framework.

  13. Design and Experiment of Nonlinear Observer with Adaptive Gains for Battery State of Charge Estimation

    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.

  14. Comparative assessment of PSI air oxidation model implementation in SCDAPSim3.5, MELCOR 1.8.6 and MELCOR 2.1

    International Nuclear Information System (INIS)

    Fernandez-Moguel, Leticia

    2015-01-01

    Highlights: • The PSI air oxidation model has been successfully implemented in MELCOR. • The model treats oxygen as an active species and nitrogen as a catalyst. • The implementation has been assessed against the previous post-test analyses for QUENCH-16. • The pre-oxidation and air phase were consistent when similar modelling options were used. • All code versions were in fair agreement with the experimental data. - Abstract: The PSI air oxidation model has been successfully implemented in the lump parameter code MELCOR. The PSI air oxidation model treats oxygen as an active species and nitrogen as a catalyst that accelerates the oxidation kinetics. The essential feature of the model is the transition from parabolic to linear kinetics. The implementation has been assessed against the previous post-test analyses for the air ingress experiment QUENCH-16 performed with a local version of RELAP5/SCDAPSim3.5. This version contains the PSI air oxidation model. The pre-oxidation and air phase were consistent when similar modelling options were used and all code versions were in fair agreement with the experimental data, showing consistency in the implementation of the model. The PSI air oxidation model will be used in the future for analysis of spent fuel pool uncovery sequences where steam/air mixture is the prototypical environment

  15. Hierarchical modeling and its numerical implementation for layered thin elastic structures

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jin-Rae [Hongik University, Sejong (Korea, Republic of)

    2017-05-15

    Thin elastic structures such as beam- and plate-like structures and laminates are characterized by the small thickness, which lead to classical plate and laminate theories in which the displacement fields through the thickness are assumed linear or higher-order polynomials. These classical theories are either insufficient to represent the complex stress variation through the thickness or may encounter the accuracy-computational cost dilemma. In order to overcome the inherent problem of classical theories, the concept of hierarchical modeling has been emerged. In the hierarchical modeling, the hierarchical models with different model levels are selected and combined within a structure domain, in order to make the modeling error be distributed as uniformly as possible throughout the problem domain. The purpose of current study is to explore the potential of hierarchical modeling for the effective numerical analysis of layered structures such as laminated composite. For this goal, the hierarchical models are constructed and the hierarchical modeling is implemented by selectively adjusting the level of hierarchical models. As well, the major characteristics of hierarchical models are investigated through the numerical experiments.

  16. Profit Analysis Model of Smart Item Implementation in Integrated Supply Chain Process

    Science.gov (United States)

    Tritularsih, Yustina; Rinanto, Andhy; Prasetyo, Hoedi; Nur Rosyidi, Cucuk

    2018-03-01

    Nowadays all links of the entire supply chain need to integrate their different infrastructures and they have better control of them to drive better profits. This integration should offer the ability for companies in order to have an overall and transparent insight to its supply chain activities. An intelligent supply chain which is mainly supported by Smart Items technology can satisfy the need of those integration. By means of Smart Items, a company can benefit some advantages. Those are cost reduction and value creation. However, currently there is no comprehensive Smart Item infrastructure exists yet so it is difficult to calculate the true benefit information. This paper attempts to recommend a model for estimating the benefits of implementing Smart Items in a company which has an integrated supply chain process. The integrated supply chain means that three echelons (supplier, shipper and retailer) of supply chain are belonged to a company. The proposed model was used to determine the shrinkage value and RFID tag price which can give the maximum benefit of Smart Items implementation. A numerical example is also provided to give a better comprehension on model calculation.

  17. Domestic policy consequences of new implementation models. Consequences for industrial niches; Industripolitiske konsekvenser av nye gjennomfoeringsmodeller. Konsekvenser for nisjebedriftene

    Energy Technology Data Exchange (ETDEWEB)

    Johannessen, T.

    1995-12-31

    The paper relates to the consequences of domestic policy with the focus on new implementation models used for cost reduction of offshore development projects in Norway. The paper puts the attention to the consequences from implementation models on industrial niches (subcontractors)

  18. Implementation of geomechanical models for engineered clay barriers in multi-physic partial differential equation solvers

    International Nuclear Information System (INIS)

    Navarro, V.; Alonso, J.; Asensio, L.; Yustres, A.; Pintado, X.

    2012-01-01

    Document available in extended abstract form only. The use of numerical methods, especially the Finite Element Method (FEM), for solving boundary problems in Unsaturated Soil Mechanics has experienced significant progress. Several codes, both built mainly for research purposes and commercial software, are now available. In the last years, Multi-physic Partial Differentiation Equation Solvers (MPDES) have turned out to be an interesting proposal. In this family of solvers, the user defines the governing equations and the behaviour models, generally using a computer algebra environment. The code automatically assembles and solves the equation systems, saving the user having to redefine the structures of memory storage or to implement solver algorithms. The user can focus on the definition of the physics of the problem, while it is possible to couple virtually any physical or chemical process that can be described by a PDE. This can be done, for instance, in COMSOL Multiphysics (CM). Nonetheless, the versatility of CM is compromised by the impossibility to implement models with variables defined by implicit functions. Elasto-plastic models involve an implicit coupling among stress increments, plastic strains and plastic variables increments. For this reason, they cannot be implemented in CM in a straightforward way. This means a very relevant limitation for the use of this tool in the analysis of geomechanical boundary value problems. In this work, a strategy to overcome this problem using the multi-physics concept is presented. A mixed method is proposed, considering the constitutive stresses, the pre-consolidation pressure and the plastic variables as main unknowns of the model. Mixed methods usually present stability problems. However, the algorithmics present in CM include several numerical strategies to minimise this kind of problems. Besides, CM is based on the application of the FEM with Lagrange multipliers, an approach that significantly contributes stability

  19. Technical report on implementation of reactor internal 3D modeling and visual database system

    International Nuclear Information System (INIS)

    Kim, Yeun Seung; Eom, Young Sam; Lee, Suk Hee; Ryu, Seung Hyun

    1996-06-01

    In this report was described a prototype of reactor internal 3D modeling and VDB system for NSSS design quality improvement. For improving NSSS design quality several cases of the nuclear developed nation's integrated computer aided engineering system, such as Mitsubishi's NUWINGS (Japan), AECL's CANDID (Canada) and Duke Power's PASCE (USA) were studied. On the basis of these studies the strategy for NSSS design improvement system was extracted and detail work scope was implemented as follows : 3D modelling of the reactor internals were implemented by using the parametric solid modeler, a prototype system of design document computerization and database was suggested, and walk-through simulation integrated with 3D modeling and VDB was accomplished. Major effects of NSSS design quality improvement system by using 3D modeling and VDB are the plant design optimization by simulation, improving the reliability through the single design database system and engineering cost reduction by improving productivity and efficiency. For applying the VDB to full scope of NSSS system design, 3D modelings of reactor coolant system and nuclear fuel assembly and fuel rod were attached as appendix. 2 tabs., 31 figs., 7 refs. (Author) .new

  20. Technical report on implementation of reactor internal 3D modeling and visual database system

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yeun Seung; Eom, Young Sam; Lee, Suk Hee; Ryu, Seung Hyun [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1996-06-01

    In this report was described a prototype of reactor internal 3D modeling and VDB system for NSSS design quality improvement. For improving NSSS design quality several cases of the nuclear developed nation`s integrated computer aided engineering system, such as Mitsubishi`s NUWINGS (Japan), AECL`s CANDID (Canada) and Duke Power`s PASCE (USA) were studied. On the basis of these studies the strategy for NSSS design improvement system was extracted and detail work scope was implemented as follows : 3D modelling of the reactor internals were implemented by using the parametric solid modeler, a prototype system of design document computerization and database was suggested, and walk-through simulation integrated with 3D modeling and VDB was accomplished. Major effects of NSSS design quality improvement system by using 3D modeling and VDB are the plant design optimization by simulation, improving the reliability through the single design database system and engineering cost reduction by improving productivity and efficiency. For applying the VDB to full scope of NSSS system design, 3D modelings of reactor coolant system and nuclear fuel assembly and fuel rod were attached as appendix. 2 tabs., 31 figs., 7 refs. (Author) .new.

  1. Total Productive Maintenance And Role Of Interpretive Structural Modeling And Structural Equation Modeling In Analyzing Barriers In Its Implementation A Literature Review

    OpenAIRE

    Prasanth S. Poduval; Dr. Jagathy Raj V. P.; Dr. V. R. Pramod

    2015-01-01

    Abstract - The aim of the authors is to present a review of literature of Total Productive Maintenance and the barriers in implementation of Total Productive Maintenance TPM. The paper begins with a brief description of TPM and the barriers in implementation of TPM. Interpretive Structural Modeling ISM and its role in analyzing the barriers in TPM implementation is explained in brief. Applications of ISM in analyzing issues in various fields are highlighted with special emphasis on TPM. T...

  2. A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

    Science.gov (United States)

    Capecchi, V.; Gozzini, B.

    2012-04-01

    The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently

  3. Implementation of New Process Models for Tailored Polymer Composite Structures into Processing Software Packages

    International Nuclear Information System (INIS)

    Nguyen, Ba Nghiep; Jin, Xiaoshi; Wang, Jin; Phelps, Jay; Tucker, Charles L. III; Kunc, Vlastimil; Bapanapalli, Satish K.; Smith, Mark T.

    2010-01-01

    This report describes the work conducted under the Cooperative Research and Development Agreement (CRADA) (Nr. 260) between the Pacific Northwest National Laboratory (PNNL) and Autodesk, Inc. to develop and implement process models for injection-molded long-fiber thermoplastics (LFTs) in processing software packages. The structure of this report is organized as follows. After the Introduction Section (Section 1), Section 2 summarizes the current fiber orientation models developed for injection-molded short-fiber thermoplastics (SFTs). Section 3 provides an assessment of these models to determine their capabilities and limitations, and the developments needed for injection-molded LFTs. Section 4 then focuses on the development of a new fiber orientation model for LFTs. This model is termed the anisotropic rotary diffusion - reduced strain closure (ARD-RSC) model as it explores the concept of anisotropic rotary diffusion to capture the fiber-fiber interaction in long-fiber suspensions and uses the reduced strain closure method of Wang et al. to slow down the orientation kinetics in concentrated suspensions. In contrast to fiber orientation modeling, before this project, no standard model was developed to predict the fiber length distribution in molded fiber composites. Section 5 is therefore devoted to the development of a fiber length attrition model in the mold. Sections 6 and 7 address the implementations of the models in AMI, and the conclusions drawn from this work is presented in Section 8.

  4. Affective Policy Performance Evaluation Model: A Case of an International Trade Policy Implementation

    Directory of Open Access Journals (Sweden)

    Inwon Kang

    2018-01-01

    Full Text Available Firms often superficially adopt policies because of governmental rules and regulations, so as to avoid penalties or to gain benefits. However, the evaluation and characterization of those kinds of adoptions as policy performance distorts the true level of policy performance: social sustainability. This study proposes an affective policy performance evaluation model. The attitudes of employees toward adopting a policy are characterized into genuine and superficial compliance. Their behaviors are explained through voluntary and opportunistic adoptions. In order to validate the proposed model, a survey was conducted on an international trade policy target group (n = 216 for the Strategic Trade Control System (STCS, in order to understand their attitudes toward adopting the policy. The survey data was analyzed by a structural equation modeling method. The measures of the factors in the proposed model are adopted and modified from existing studies. The most effective resources of policy implementation on the firms’ genuine and superficial compliance and ultimately on the firms’ voluntary policy adoption are revealed through the analysis. Based on the results, this study presents a strategy for allocating and managing policy implementation resources to exclusively encourage firms’ trade policy adoptions.

  5. Implementing and Assessing a Flipped Classroom Model for First-Year Engineering Design

    Science.gov (United States)

    Saterbak, Ann; Volz, Tracy; Wettergreen, Matthew

    2016-01-01

    Faculty at Rice University are creating instructional resources to support teaching first-year engineering design using a flipped classroom model. This implementation of flipped pedagogy is unusual because content-driven, lecture courses are usually targeted for flipping, not project-based design courses that already incorporate an abundance of…

  6. Implementation of the Multidimensional Modeling Concepts into Object-Relational Databases

    Directory of Open Access Journals (Sweden)

    2007-01-01

    Full Text Available A key to survival in the business world is being able to analyze, plan and react to changing business conditions as fast as possible. With multidimensional models the managers can explore information at different levels of granularity and the decision makers at all levels can quickly respond to changes in the business climate-the ultimate goal of business intelligence. This paper focuses on the implementation of the multidimensional concepts into object-relational databases.

  7. Designing Caregiver-Implemented Shared-Reading Interventions to Overcome Implementation Barriers

    Science.gov (United States)

    Logan, Jessica R.; Damschroder, Laura

    2015-01-01

    Purpose This study presents an application of the theoretical domains framework (TDF; Michie et al., 2005), an integrative framework drawing on behavior-change theories, to speech-language pathology. Methods A multistep procedure was used to identify barriers affecting caregivers' implementation of shared-reading interventions with their children with language impairment (LI). The authors examined caregiver-level data corresponding to implementation issues from two randomized controlled trials and mapped these to domains in the TDF as well as empirically validated behavior-change techniques. Results Four barriers to implementation were identified as potentially affecting caregivers' implementation: time pressures, reading difficulties, discomfort with reading, and lack of awareness of benefits. These were mapped to 3 TDF domains: intentions, beliefs about capabilities, and skills. In turn, 4 behavior-change techniques were identified as potential vehicles for affecting these domains: reward, feedback, model, and encourage. An ongoing study is described that is determining the effects of these techniques for improving caregivers' implementation of a shared-reading intervention. Conclusions A description of the steps to identifying barriers to implementation, in conjunction with an ongoing experiment that will explicitly determine whether behavior-change techniques affect these barriers, provides a model for how implementation science can be used to identify and overcome implementation barriers in the treatment of communication disorders. PMID:26262941

  8. Basic extended Kalman filter: simultaneous localisation and mapping

    CSIR Research Space (South Africa)

    Matsebe, O

    2010-01-01

    Full Text Available in SLAM with a bent towards EKF-SLAM. It will also be helpful in realizing what methods are being employed and what sensors are being used. It presents the 2 – Dimensional (2D) feature based EKF-SLAM technique used for generating robot pose estimates...

  9. An Efficient Role and Object Based Access Control Model Implemented in a PDM System

    Institute of Scientific and Technical Information of China (English)

    HUANG Xiaowen; TAN Jian; HUANG Xiangguo

    2006-01-01

    An effective and reliable access control is crucial to a PDM system. This article has discussed the commonly used access control models, analyzed their advantages and disadvantages, and proposed a new Role and Object based access control model that suits the particular needs of a PDM system. The new model has been implemented in a commercial PDM system, which has demonstrated enhanced flexibility and convenience.

  10. Determining the predictors of innovation implementation in healthcare: a quantitative analysis of implementation effectiveness.

    Science.gov (United States)

    Jacobs, Sara R; Weiner, Bryan J; Reeve, Bryce B; Hofmann, David A; Christian, Michael; Weinberger, Morris

    2015-01-22

    The failure rates for implementing complex innovations in healthcare organizations are high. Estimates range from 30% to 90% depending on the scope of the organizational change involved, the definition of failure, and the criteria to judge it. The innovation implementation framework offers a promising approach to examine the organizational factors that determine effective implementation. To date, the utility of this framework in a healthcare setting has been limited to qualitative studies and/or group level analyses. Therefore, the goal of this study was to quantitatively examine this framework among individual participants in the National Cancer Institute's Community Clinical Oncology Program using structural equation modeling. We examined the innovation implementation framework using structural equation modeling (SEM) among 481 physician participants in the National Cancer Institute's Community Clinical Oncology Program (CCOP). The data sources included the CCOP Annual Progress Reports, surveys of CCOP physician participants and administrators, and the American Medical Association Physician Masterfile. Overall the final model fit well. Our results demonstrated that not only did perceptions of implementation climate have a statistically significant direct effect on implementation effectiveness, but physicians' perceptions of implementation climate also mediated the relationship between organizational implementation policies and practices (IPP) and enrollment (p innovation implementation framework between IPP, implementation climate, and implementation effectiveness among individual physicians. This finding is important, as although the model has been discussed within healthcare organizations before, the studies have been predominately qualitative in nature and/or at the organizational level. In addition, our findings have practical applications. Managers looking to increase implementation effectiveness of an innovation should focus on creating an environment that

  11. How is the Current Nano/Microscopic Knowledge Implemented in Model Approaches?

    International Nuclear Information System (INIS)

    Rotenberg, Benjamin

    2013-01-01

    The recent developments of experimental techniques have opened new opportunities and challenges for the modelling and simulation of clay materials, on various scales. In this communication, several aspects of the interaction between experimental and modelling approaches will be presented and dis-cussed. What levels of modelling are available depending on the target property and what experimental input is required? How can experimental information be used to validate models? What knowledge can modelling on different scale bring to the knowledge on the physical properties of clays? Finally, what can we do when experimental information is not available? Models implement the current nano/microscopic knowledge using experimental input, taking advantage of multi-scale approaches, and providing data or insights complementary to experiments. Future work will greatly benefit from the recent experimental developments, in particular for 3D-imaging on intermediate scales, and should also address other properties, e.g. mechanical or thermal properties. (authors)

  12. Simple cortical and thalamic neuron models for digital arithmetic circuit implementation

    Directory of Open Access Journals (Sweden)

    Takuya eNanami

    2016-05-01

    Full Text Available Trade-off between reproducibility of neuronal activities and computational efficiency is one ofcrucial subjects in computational neuroscience and neuromorphic engineering. A wide variety ofneuronal models have been studied from different viewpoints. The digital spiking silicon neuron(DSSN model is a qualitative model that focuses on efficient implementation by digital arithmeticcircuits. We expanded the DSSN model and found appropriate parameter sets with which itreproduces the dynamical behaviors of the ionic-conductance models of four classes of corticaland thalamic neurons. We first developed a 4-variable model by reducing the number of variablesin the ionic-conductance models and elucidated its mathematical structures using bifurcationanalysis. Then, expanded DSSN models were constructed that reproduce these mathematicalstructures and capture the characteristic behavior of each neuron class. We confirmed thatstatistics of the neuronal spike sequences are similar in the DSSN and the ionic-conductancemodels. Computational cost of the DSSN model is larger than that of the recent sophisticatedIntegrate-and-Fire-based models, but smaller than the ionic-conductance models. This modelis intended to provide another meeting point for above trade-off that satisfies the demand forlarge-scale neuronal network simulation with closer-to-biology models.

  13. A Study of Synchronous Machine Model Implementations in Matlab/Simulink Simulations for New and Renewable Energy Systems

    DEFF Research Database (Denmark)

    Chen, Zhe; Blaabjerg, Frede; Iov, Florin

    2005-01-01

    A direct phase model of synchronous machines implemented in MA TLAB/SIMULINK is presented. The effects of the machine saturation have been included. Simulation studies are performed under various conditions. It has been demonstrated that the MATLAB/SIMULINK is an effective tool to study the compl...... synchronous machine and the implemented model could be used for studies of various applications of synchronous machines including in renewable and DG generation systems....

  14. Filtering in Hybrid Dynamic Bayesian Networks

    Science.gov (United States)

    Andersen, Morten Nonboe; Andersen, Rasmus Orum; Wheeler, Kevin

    2000-01-01

    We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).

  15. Electro-kinetic remediation coupled with phytoremediation to remove lead, arsenic and cesium from contaminated paddy soil.

    Science.gov (United States)

    Mao, Xinyu; Han, Fengxiang X; Shao, Xiaohou; Guo, Kai; McComb, Jacqueline; Arslan, Zikri; Zhang, Zhanyu

    2016-03-01

    The objectives of this study were to investigate distribution and solubility of Pb, Cs and As in soils under electrokinetic field and examine the processes of coupled electrokinetic phytoremediation of polluted soils. The elevated bioavailability and bioaccumulation of Pb, As and Cs in paddy soil under an electro-kinetic field (EKF) were studied. The results show that the EKF treatment is effective on lowering soil pH to around 1.5 near the anode which is beneficial for the dissolution of metal(loid)s, thus increasing their overall solubility. The acidification in the anode soil efficiently increased the water soluble (SOL) and exchangeable (EXC) Pb, As and Cs, implying enhanced solubility and elevated overall potential bioavailability in the anode region while lower solubility in the cathode areas. Bioaccumulations of Pb, As and Cs were largely determined by the nature of elements, loading levels and EKF treatment. The native Pb in soil usually is not bioavailable. However, EKF treatment tends to transfer Pb to the SOL and EXC fractions improving the phytoextraction efficiency. Similarly, EKF transferred more EXC As and Cs to the SOL fraction significantly increasing their bioaccumulation in plant roots and shoots. Pb and As were accumulated more in plant roots than in shoots while Cs was accumulated more in shoots due to its similarity of chemical properties to potassium. Indian mustard, spinach and cabbage are good accumulators for Cs. Translocation of Pb, As and Cs from plant roots to shoots were enhanced by EKF. However, this study indicated the overall low phytoextraction efficiency of these plants. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Implementation of a participatory management model: analysis from a political perspective.

    Science.gov (United States)

    Bernardes, Andrea; G Cummings, Greta; Gabriel, Carmen Silvia; Martinez Évora, Yolanda Dora; Gomes Maziero, Vanessa; Coleman-Miller, Glenda

    2015-10-01

    To analyse experiences of managers and nursing staff in the implementation of participatory management, specifically processes of decision-making, communication and power in a Canadian hospital. Implementing a Participatory Management Model involves change because it is focused on the needs of patients and encourages decentralisation of power and shared decisions. The study design is qualitative using observational sessions and content analysis for data analysis. We used Bolman and Deal's four-frame theoretical framework to interpret our findings. Participatory management led to advances in care, because it allowed for more dialogue and shared decision making. However, the biggest challenge has been that all major changes are still being decided centrally by the provincial executive board. Managers and directors are facing difficulties related to this change process, such as the resistance to change by some employees and limited input to decision-making affecting their areas of responsibility; however, they and their teams are working to utilise the values and principles underlying participatory management in their daily work practices. Innovative management models encourage accountability, increased motivation and satisfaction of nursing staff, and improve the quality of care. © 2014 John Wiley & Sons Ltd.

  17. Cleanliness Policy Implementation: Evaluating Retribution Model to Rise Public Satisfaction

    Science.gov (United States)

    Dailiati, Surya; Hernimawati; Prihati; Chintia Utami, Bunga

    2018-05-01

    This research is based on the principal issues concerning the evaluation of cleanliness retribution policy which has not been optimally be able to improve the Local Revenue of Pekanbaru City and has not improved the cleanliness of Pekanbaru City. It was estimated to be caused by the performance of Garden and Sanitation Department are not in accordance with the requirement of society of Pekanbaru City. The research method used in this study is a mixed method with sequential exploratory strategy. The data collection used are observation, interview and documentation for qualitative research as well as questionnaires for quantitative research. The collected data were analyzed with interactive model of Miles and Huberman for qualitative research and multiple regression analysis for quantitative research. The research result indicated that the model of cleanliness policy implementation that can increase of PAD Pekanbaru City and be able to improve people’s satisfaction divided into two (2) which are the evaluation model and the society satisfaction model. The evaluation model influence by criteria/variable of effectiveness, efficiency, adequacy, equity, responsiveness, and appropriateness, while the society satisfaction model influence by variables of society satisfaction, intentions, goals, plans, programs, and appropriateness of cleanliness retribution collection policy.

  18. Barriers and facilitators to implementing a patient-centered model of contraceptive provision in community health centers.

    Science.gov (United States)

    Politi, Mary C; Estlund, Amy; Milne, Anne; Buckel, Christina M; Peipert, Jeffrey F; Madden, Tessa

    2016-01-01

    The Contraceptive CHOICE Project developed a patient-centered model for contraceptive provision including: (1) structured, evidence-based counseling; (2) staff and health care provider education; and (3) removal of barriers such as cost and multiple appointments to initiate contraception. In preparation for conducting a research study of the CHOICE model in three community health settings, we sought to identify potential barriers and facilitators to implementation. Using a semi-structured interview guide guided by a framework of implementation research, we conducted 31 qualitative interviews with female patients, staff, and health care providers assessing attitudes, beliefs, and barriers to receiving contraception. We also asked about current contraceptive provision and explored organizational practices relevant to implementing the CHOICE model. We used a grounded theory approach to identify major themes. Many participants felt that current contraceptive provision could be improved by the CHOICE model. Potential facilitators included agreement about the necessity for improved contraceptive knowledge among patients and staff; importance of patient-centered contraceptive counseling; and benefits to same-day insertion of long-acting reversible contraception (LARC). Potential barriers included misconceptions about contraception held by staff and providers; resistance to new practices; costs associated with LARC; and scheduling challenges required for same-day insertion of LARC. In addition to staff and provider training, implementing a patient-centered model of contraceptive provision needs to be supplemented by strategies to manage patient and system-level barriers. Community health center staff, providers, and patients support patient-centered contraceptive counseling to improve contraception provision if organizations can address these barriers.

  19. System health monitoring using multiple-model adaptive estimation techniques

    Science.gov (United States)

    Sifford, Stanley Ryan

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

  20. Integration of GPS precise point positioning and MEMS-based INS using unscented particle filter.

    Science.gov (United States)

    Abd Rabbou, Mahmoud; El-Rabbany, Ahmed

    2015-03-25

    Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) integrated system involves nonlinear motion state and measurement models. However, the extended Kalman filter (EKF) is commonly used as the estimation filter, which might lead to solution divergence. This is usually encountered during GPS outages, when low-cost micro-electro-mechanical sensors (MEMS) inertial sensors are used. To enhance the navigation system performance, alternatives to the standard EKF should be considered. Particle filtering (PF) is commonly considered as a nonlinear estimation technique to accommodate severe MEMS inertial sensor biases and noise behavior. However, the computation burden of PF limits its use. In this study, an improved version of PF, the unscented particle filter (UPF), is utilized, which combines the unscented Kalman filter (UKF) and PF for the integration of GPS precise point positioning and MEMS-based inertial systems. The proposed filter is examined and compared with traditional estimation filters, namely EKF, UKF and PF. Tightly coupled mechanization is adopted, which is developed in the raw GPS and INS measurement domain. Un-differenced ionosphere-free linear combinations of pseudorange and carrier-phase measurements are used for PPP. The performance of the UPF is analyzed using a real test scenario in downtown Kingston, Ontario. It is shown that the use of UPF reduces the number of samples needed to produce an accurate solution, in comparison with the traditional PF, which in turn reduces the processing time. In addition, UPF enhances the positioning accuracy by up to 15% during GPS outages, in comparison with EKF. However, all filters produce comparable results when the GPS measurement updates are available.