The NASA F-15 Intelligent Flight Control Systems: Generation II

NASA Technical Reports Server (NTRS)

Buschbacher, Mark; Bosworth, John

2006-01-01

The Second Generation (Gen II) control system for the F-15 Intelligent Flight Control System (IFCS) program implements direct adaptive neural networks to demonstrate robust tolerance to faults and failures. The direct adaptive tracking controller integrates learning neural networks (NNs) with a dynamic inversion control law. The term direct adaptive is used because the error between the reference model and the aircraft response is being compensated or directly adapted to minimize error without regard to knowing the cause of the error. No parameter estimation is needed for this direct adaptive control system. In the Gen II design, the feedback errors are regulated with a proportional-plus-integral (PI) compensator. This basic compensator is augmented with an online NN that changes the system gains via an error-based adaptation law to improve aircraft performance at all times, including normal flight, system failures, mispredicted behavior, or changes in behavior resulting from damage.

Development and experimental verification of a robust active noise control system for a diesel engine in submarines

NASA Astrophysics Data System (ADS)

Sachau, D.; Jukkert, S.; Hövelmann, N.

2016-08-01

This paper presents the development and experimental validation of an ANC (active noise control)-system designed for a particular application in the exhaust line of a submarine. Thereby, tonal components of the exhaust noise in the frequency band from 75 Hz to 120 Hz are reduced by more than 30 dB. The ANC-system is based on the feedforward leaky FxLMS-algorithm. The observability of the sound pressure in standing wave field is ensured by using two error microphones. The noninvasive online plant identification method is used to increase the robustness of the controller. Online plant identification is extended by a time-varying convergence gain to improve the performance in the presence of slight error in the frequency of the reference signal.

Educational intervention together with an on-line quality control program achieve recommended analytical goals for bedside blood glucose monitoring in a 1200-bed university hospital.

PubMed

Sánchez-Margalet, Víctor; Rodriguez-Oliva, Manuel; Sánchez-Pozo, Cristina; Fernández-Gallardo, María Francisca; Goberna, Raimundo

2005-01-01

Portable meters for blood glucose concentrations are used at the patients bedside, as well as by patients for self-monitoring of blood glucose. Even though most devices have important technological advances that decrease operator error, the analytical goals proposed for the performance of glucose meters have been recently changed by the American Diabetes Association (ADA) to reach <5% analytical error and <7.9% total error. We studied 80 meters throughout the Virgen Macarena Hospital and we found most devices with performance error higher than 10%. The aim of the present study was to establish a new system to control portable glucose meters together with an educational program for nurses in a 1200-bed University Hospital to achieve recommended analytical goals, so that we could improve the quality of diabetes care. We used portable glucose meters connected on-line to the laboratory after an educational program for nurses with responsibilities in point-of-care testing. We evaluated the system by assessing total error of the glucometers using high- and low-level glucose control solutions. In a period of 6 months, we collected data from 5642 control samples obtained by 14 devices (Precision PCx) directly from the control program (QC manager). The average total error for the low-level glucose control (2.77 mmol/l) was 6.3% (range 5.5-7.6%), and even lower for the high-level glucose control (16.66 mmol/l), at 4.8% (range 4.1-6.5%). In conclusion, the performance of glucose meters used in our University Hospital with more than 1000 beds not only improved after the intervention, but the meters achieved the analytical goals of the suggested ADA/National Academy of Clinical Biochemistry criteria for total error (<7.9% in the range 2.77-16.66 mmol/l glucose) and optimal total error for high glucose concentrations of <5%, which will improve the quality of care of our patients.

Quiet eye facilitates sensorimotor preprograming and online control of precision aiming in golf putting.

PubMed

Causer, Joe; Hayes, Spencer J; Hooper, James M; Bennett, Simon J

2017-02-01

An occlusion protocol was used to elucidate the respective roles of preprograming and online control during the quiet eye period of golf putting. Twenty-one novice golfers completed golf putts to 6-ft and 11-ft targets under full vision or with vision occluded on initiation of the backswing. Radial error (RE) was higher, and quiet eye was longer, when putting to the 11-ft versus 6-ft target, and in the occluded versus full vision condition. Quiet eye durations, as well as preprograming, online and dwell durations, were longer in low-RE compared to high-RE trials. The preprograming component of quiet eye was significantly longer in the occluded vision condition, whereas the online and dwell components were significantly longer in the full vision condition. These findings demonstrate an increase in preprograming when vision is occluded. However, this was not sufficient to overcome the need for online visual control during the quiet eye period. These findings suggest the quiet eye period is composed of preprograming and online control elements; however, online visual control of action is critical to performance.

Growth monitoring and control in complex medium: a case study employing fed-batch penicillin fermentation and computer-aided on-line mass balancing.

PubMed

Mou, D G; Cooney, C L

1983-01-01

To broaden the practicality of on-line growth monitoring and control, its application in fedbatch penicillin fermentation using high corn steep liquor (CSL) concentration (53 g/L) is demonstrated. By employing a calculation method that considers the vagaries of CSL consumption, overall and instantaneous carbon-balancing equations are successfully used to calculate, on-line, the cell concentration and instantaneous specific growth rate in the penicillin production phase. As a consequence, these equations, together with a feedback control strategy, enable the computer control of glucose feed and maintenance of the preselected production-phase growth rate with error less than 0.002 h(-1).

Improving integrity of on-line grammage measurement with traceable basic calibration.

PubMed

Kangasrääsiö, Juha

2010-07-01

The automatic control of grammage (basis weight) in paper and board production is based upon on-line grammage measurement. Furthermore, the automatic control of other quality variables such as moisture, ash content and coat weight, may rely on the grammage measurement. The integrity of Kr-85 based on-line grammage measurement systems was studied, by performing basic calibrations with traceably calibrated plastic reference standards. The calibrations were performed according to the EN ISO/IEC 17025 standard, which is a requirement for calibration laboratories. The observed relative measurement errors were 3.3% in the first time calibrations at the 95% confidence level. With the traceable basic calibration method, however, these errors can be reduced to under 0.5%, thus improving the integrity of on-line grammage measurements. Also a standardised algorithm, based on the experience from the performed calibrations, is proposed to ease the adjustment of the different grammage measurement systems. The calibration technique can basically be applied to all beta-radiation based grammage measurements. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Intelligent complementary sliding-mode control for LUSMS-based X-Y-theta motion control stage.

PubMed

Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai; Liu, Yen-Hung

2010-07-01

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-theta motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.

Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.

PubMed

Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R

2016-03-01

This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

NASA Technical Reports Server (NTRS)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.

PubMed

Najjar-Khodabakhsh, Abbas; Soltani, Jafar

2016-03-01

In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Linear Parameter Varying Control for Actuator Failure

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

A robust linear parameter varying (LPV) control synthesis is carried out for an HiMAT vehicle subject to loss of control effectiveness. The scheduling parameter is selected to be a function of the estimates of the control effectiveness factors. The estimates are provided on-line by a two-stage Kalman estimator. The inherent conservatism of the LPV design is reducing through the use of a scaling factor on the uncertainty block that represents the estimation errors of the effectiveness factors. Simulations of the controlled system with the on-line estimator show that a superior fault-tolerance can be achieved.

Context Specificity of Post-Error and Post-Conflict Cognitive Control Adjustments

PubMed Central

Forster, Sarah E.; Cho, Raymond Y.

2014-01-01

There has been accumulating evidence that cognitive control can be adaptively regulated by monitoring for processing conflict as an index of online control demands. However, it is not yet known whether top-down control mechanisms respond to processing conflict in a manner specific to the operative task context or confer a more generalized benefit. While previous studies have examined the taskset-specificity of conflict adaptation effects, yielding inconsistent results, control-related performance adjustments following errors have been largely overlooked. This gap in the literature underscores recent debate as to whether post-error performance represents a strategic, control-mediated mechanism or a nonstrategic consequence of attentional orienting. In the present study, evidence of generalized control following both high conflict correct trials and errors was explored in a task-switching paradigm. Conflict adaptation effects were not found to generalize across tasksets, despite a shared response set. In contrast, post-error slowing effects were found to extend to the inactive taskset and were predictive of enhanced post-error accuracy. In addition, post-error performance adjustments were found to persist for several trials and across multiple task switches, a finding inconsistent with attentional orienting accounts of post-error slowing. These findings indicate that error-related control adjustments confer a generalized performance benefit and suggest dissociable mechanisms of post-conflict and post-error control. PMID:24603900

Quick foot placement adjustments during gait are less accurate in individuals with focal cerebellar lesions.

PubMed

Hoogkamer, Wouter; Potocanac, Zrinka; Van Calenbergh, Frank; Duysens, Jacques

2017-10-01

Online gait corrections are frequently used to restore gait stability and prevent falling. They require shorter response times than voluntary movements which suggests that subcortical pathways contribute to the execution of online gait corrections. To evaluate the potential role of the cerebellum in these pathways we tested the hypotheses that online gait corrections would be less accurate in individuals with focal cerebellar damage than in neurologically intact controls and that this difference would be more pronounced for shorter available response times and for short step gait corrections. We projected virtual stepping stones on an instrumented treadmill while some of the approaching stepping stones were shifted forward or backward, requiring participants to adjust their foot placement. Varying the timing of those shifts allowed us to address the effect of available response time on foot placement error. In agreement with our hypothesis, individuals with focal cerebellar lesions were less accurate in adjusting their foot placement in reaction to suddenly shifted stepping stones than neurologically intact controls. However, the cerebellar lesion group's foot placement error did not increase more with decreasing available response distance or for short step versus long step adjustments compared to the control group. Furthermore, foot placement error for the non-shifting stepping stones was also larger in the cerebellar lesion group as compared to the control group. Consequently, the reduced ability to accurately adjust foot placement during walking in individuals with focal cerebellar lesions appears to be a general movement control deficit, which could contribute to increased fall risk. Copyright © 2017 Elsevier B.V. All rights reserved.

Exponential parameter and tracking error convergence guarantees for adaptive controllers without persistency of excitation

NASA Astrophysics Data System (ADS)

Chowdhary, Girish; Mühlegg, Maximilian; Johnson, Eric

2014-08-01

In model reference adaptive control (MRAC) the modelling uncertainty is often assumed to be parameterised with time-invariant unknown ideal parameters. The convergence of parameters of the adaptive element to these ideal parameters is beneficial, as it guarantees exponential stability, and makes an online learned model of the system available. Most MRAC methods, however, require persistent excitation of the states to guarantee that the adaptive parameters converge to the ideal values. Enforcing PE may be resource intensive and often infeasible in practice. This paper presents theoretical analysis and illustrative examples of an adaptive control method that leverages the increasing ability to record and process data online by using specifically selected and online recorded data concurrently with instantaneous data for adaptation. It is shown that when the system uncertainty can be modelled as a combination of known nonlinear bases, simultaneous exponential tracking and parameter error convergence can be guaranteed if the system states are exciting over finite intervals such that rich data can be recorded online; PE is not required. Furthermore, the rate of convergence is directly proportional to the minimum singular value of the matrix containing online recorded data. Consequently, an online algorithm to record and forget data is presented and its effects on the resulting switched closed-loop dynamics are analysed. It is also shown that when radial basis function neural networks (NNs) are used as adaptive elements, the method guarantees exponential convergence of the NN parameters to a compact neighbourhood of their ideal values without requiring PE. Flight test results on a fixed-wing unmanned aerial vehicle demonstrate the effectiveness of the method.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

NASA Astrophysics Data System (ADS)

Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai

2014-05-01

We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

Real-time auto-adaptive margin generation for MLC-tracked radiotherapy

NASA Astrophysics Data System (ADS)

Glitzner, M.; Fast, M. F.; de Senneville, B. Denis; Nill, S.; Oelfke, U.; Lagendijk, J. J. W.; Raaymakers, B. W.; Crijns, S. P. M.

2017-01-01

In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing {{V}90 %} in the underdosed area about 47 % and 41 % , respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors.

Research on On-Line Modeling of Fed-Batch Fermentation Process Based on v-SVR

NASA Astrophysics Data System (ADS)

Ma, Yongjun

The fermentation process is very complex and non-linear, many parameters are not easy to measure directly on line, soft sensor modeling is a good solution. This paper introduces v-support vector regression (v-SVR) for soft sensor modeling of fed-batch fermentation process. v-SVR is a novel type of learning machine. It can control the accuracy of fitness and prediction error by adjusting the parameter v. An on-line training algorithm is discussed in detail to reduce the training complexity of v-SVR. The experimental results show that v-SVR has low error rate and better generalization with appropriate v.

SBL-Online: Implementing Studio-Based Learning Techniques in an Online Introductory Programming Course to Address Common Programming Errors and Misconceptions

ERIC Educational Resources Information Center

Polo, Blanca J.

2013-01-01

Much research has been done in regards to student programming errors, online education and studio-based learning (SBL) in computer science education. This study furthers this area by bringing together this knowledge and applying it to proactively help students overcome impasses caused by common student programming errors. This project proposes a…

Learning by (video) example: a randomized study of communication skills training for end-of-life and error disclosure family care conferences.

PubMed

Schmitz, Connie C; Braman, Jonathan P; Turner, Norman; Heller, Stephanie; Radosevich, David M; Yan, Yelena; Miller, Jane; Chipman, Jeffrey G

2016-11-01

Teaching residents to lead end of life (EOL) and error disclosure (ED) conferences is important. We developed and tested an intervention using videotapes of EOL and error disclosure encounters from previous Objective Structured Clinical Exams. Residents (n = 72) from general and orthopedic surgery programs at 2 sites were enrolled. Using a prospective, pre-post, block group design with stratified randomization, we hypothesized the treatment group would outperform the control on EOL and ED cases. We also hypothesized that online course usage would correlate positively with post-test scores. All residents improved (pre-post). At the group level, treatment effects were insignificant, and post-test performance was unrelated to course usage. At the subgroup level for EOL, low performers assigned to treatment scored higher than controls at post-test; and within the treatment group, post graduate year 3 residents outperformed post graduate year ​1 residents. To be effective, online curricula illustrating communication behaviors need face-to-face interaction, individual role play with feedback and discussion. Copyright © 2016 Elsevier Inc. All rights reserved.

Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach.

PubMed

Liu, Derong; Wang, Ding; Li, Hongliang

2014-02-01

In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.

Hybrid adaptive ascent flight control for a flexible launch vehicle

NASA Astrophysics Data System (ADS)

Lefevre, Brian D.

For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the hybrid adaptive flight controller, development of a Newton's method based online parameter update that is modified to include a step size which regulates the rate of change in the parameter estimates, comparison of the modified Newton's method and recursive least squares online parameter update algorithms, modification of the neural network's input structure to accommodate for the nature of the nonlinearities present in a launch vehicle's ascent flight, examination of both tracking error based and modeling error based neural network weight update laws, and integration of feedback filters for the purpose of preventing harmful interaction between the flight control system and flexible structural modes. To validate the hybrid adaptive controller, a high-fidelity Ares I ascent flight simulator and a classical gain-scheduled proportional-integral-derivative (PID) ascent flight controller were obtained from the NASA Marshall Space Flight Center. The classical PID flight controller is used as a benchmark when analyzing the performance of the hybrid adaptive flight controller. Simulations are conducted which model both nominal and off-nominal flight conditions with structural flexibility of the vehicle either enabled or disabled. First, rigid body ascent simulations are performed with the hybrid adaptive controller under nominal flight conditions for the purpose of selecting the update laws which drive the indirect and direct adaptive components. With the neural network disabled, the results revealed that the recursive least squares online parameter update caused high frequency oscillations to appear in the engine gimbal commands. This is highly undesirable for long and slender launch vehicles, such as the Ares I, because such oscillation of the rocket nozzle could excite unstable structural flex modes. In contrast, the modified Newton's method online parameter update produced smooth control signals and was thus selected for use in the hybrid adaptive launch vehicle flight controller. In the simulations where the online parameter identification algorithm was disabled, the tracking error based neural network weight update law forced the network's output to diverge despite repeated reductions of the adaptive learning rate. As a result, the modeling error based neural network weight update law (which generated bounded signals) is utilized by the hybrid adaptive controller in all subsequent simulations. Comparing the PID and hybrid adaptive flight controllers under nominal flight conditions in rigid body ascent simulations showed that their tracking error magnitudes are similar for a period of time during the middle of the ascent phase. Though the PID controller performs better for a short interval around the 20 second mark, the hybrid adaptive controller performs far better from roughly 70 to 120 seconds. Elevating the aerodynamic loads by increasing the force and moment coefficients produced results very similar to the nominal case. However, applying a 5% or 10% thrust reduction to the first stage rocket motor causes the tracking error magnitude observed by the PID controller to be significantly elevated and diverge rapidly as the simulation concludes. In contrast, the hybrid adaptive controller steadily maintains smaller errors (often less than 50% of the corresponding PID value). Under the same sets of flight conditions with flexibility enabled, the results exhibit similar trends with the hybrid adaptive controller performing even better in each case. Again, the reduction of the first stage rocket motor's thrust clearly illustrated the superior robustness of the hybrid adaptive flight controller.

LANDSAT-4 MSS Geometric Correction: Methods and Results

NASA Technical Reports Server (NTRS)

Brooks, J.; Kimmer, E.; Su, J.

1984-01-01

An automated image registration system such as that developed for LANDSAT-4 can produce all of the information needed to verify and calibrate the software and to evaluate system performance. The on-line MSS archive generation process which upgrades systematic correction data to geodetic correction data is described as well as the control point library build subsystem which generates control point chips and support data for on-line upgrade of correction data. The system performance was evaluated for both temporal and geodetic registration. For temporal registration, 90% errors were computed to be .36 IFOV (instantaneous field of view) = 82.7 meters) cross track, and .29 IFOV along track. Also, for actual production runs monitored, the 90% errors were .29 IFOV cross track and .25 IFOV along track. The system specification is .3 IFOV, 90% of the time, both cross and along track. For geodetic registration performance, the model bias was measured by designating control points in the geodetically corrected imagery.

Advanced Interactive Display Formats for Terminal Area Traffic Control

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Shaviv, G. E.

1999-01-01

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.

PubMed

Krüger, Thomas; Schnetter, Philipp; Placzek, Robin; Vörsmann, Peter

2012-08-01

An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Error Reporting in the ATLAS TDAQ System

NASA Astrophysics Data System (ADS)

Kolos, Serguei; Kazarov, Andrei; Papaevgeniou, Lykourgos

2015-05-01

The ATLAS Error Reporting provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service (ERS), gives to software applications the opportunity to collect and send comprehensive data about run-time errors, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the ERS as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When an application sends information to ERS, depending on the configuration, it may end up in a local file, a database, distributed middleware which can transport it to an expert system or display it to users. Thanks to the open framework design of ERS, new information destinations can be added at any moment without touching the reporting and receiving applications. The ERS Application Program Interface (API) is provided in three programming languages used in the ATLAS online environment: C++, Java and Python. All APIs use exceptions for error reporting but each of them exploits advanced features of a given language to simplify the end-user program writing. For example, as C++ lacks language support for exceptions, a number of macros have been designed to generate hierarchies of C++ exception classes at compile time. Using this approach a software developer can write a single line of code to generate a boilerplate code for a fully qualified C++ exception class declaration with arbitrary number of parameters and multiple constructors, which encapsulates all relevant static information about the given type of issues. When a corresponding error occurs at run time, the program just need to create an instance of that class passing relevant values to one of the available class constructors and send this instance to ERS. This paper presents the original design solutions exploited for the ERS implementation and describes how it was used during the first ATLAS run period. The cross-system error reporting standardization introduced by ERS was one of the key points for the successful implementation of automated mechanisms for online error recovery.

Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control

NASA Astrophysics Data System (ADS)

Chen, Syuan-Yi; Gong, Sheng-Sian

2017-09-01

This study aims to develop an adaptive high-precision control system for controlling the speed of a vane-type air motor (VAM) pneumatic servo system. In practice, the rotor speed of a VAM depends on the input mass air flow, which can be controlled by the effective orifice area (EOA) of an electronic throttle valve (ETV). As the control variable of a second-order pneumatic system is the integral of the EOA, an observation-based adaptive dynamic sliding-mode control (ADSMC) system is proposed to derive the differential of the control variable, namely, the EOA control signal. In the ADSMC system, a proportional-integral-derivative fuzzy neural network (PIDFNN) observer is used to achieve an ideal dynamic sliding-mode control (DSMC), and a supervisor compensator is designed to eliminate the approximation error. As a result, the ADSMC incorporates the robustness of a DSMC and the online learning ability of a PIDFNN. To ensure the convergence of the tracking error, a Lyapunov-based analytical method is employed to obtain the adaptive algorithms required to tune the control parameters of the online ADSMC system. Finally, our experimental results demonstrate the precision and robustness of the ADSMC system for highly nonlinear and time-varying VAM pneumatic servo systems.

Quantitative evaluation of patient-specific quality assurance using online dosimetry system

NASA Astrophysics Data System (ADS)

Jung, Jae-Yong; Shin, Young-Ju; Sohn, Seung-Chang; Min, Jung-Whan; Kim, Yon-Lae; Kim, Dong-Su; Choe, Bo-Young; Suh, Tae-Suk

2018-01-01

In this study, we investigated the clinical performance of an online dosimetry system (Mobius FX system, MFX) by 1) dosimetric plan verification using gamma passing rates and dose volume metrics and 2) error-detection capability evaluation by deliberately introduced machine error. Eighteen volumetric modulated arc therapy (VMAT) plans were studied. To evaluate the clinical performance of the MFX, we used gamma analysis and dose volume histogram (DVH) analysis. In addition, to evaluate the error-detection capability, we used gamma analysis and DVH analysis utilizing three types of deliberately introduced errors (Type 1: gantry angle-independent multi-leaf collimator (MLC) error, Type 2: gantry angle-dependent MLC error, and Type 3: gantry angle error). A dosimetric verification comparison of physical dosimetry system (Delt4PT) and online dosimetry system (MFX), gamma passing rates of the two dosimetry systems showed very good agreement with treatment planning system (TPS) calculation. For the average dose difference between the TPS calculation and the MFX measurement, most of the dose metrics showed good agreement within a tolerance of 3%. For the error-detection comparison of Delta4PT and MFX, the gamma passing rates of the two dosimetry systems did not meet the 90% acceptance criterion with the magnitude of error exceeding 2 mm and 1.5 ◦, respectively, for error plans of Types 1, 2, and 3. For delivery with all error types, the average dose difference of PTV due to error magnitude showed good agreement between calculated TPS and measured MFX within 1%. Overall, the results of the online dosimetry system showed very good agreement with those of the physical dosimetry system. Our results suggest that a log file-based online dosimetry system is a very suitable verification tool for accurate and efficient clinical routines for patient-specific quality assurance (QA).

Design of a self-adaptive fuzzy PID controller for piezoelectric ceramics micro-displacement system

NASA Astrophysics Data System (ADS)

Zhang, Shuang; Zhong, Yuning; Xu, Zhongbao

2008-12-01

In order to improve control precision of the piezoelectric ceramics (PZT) micro-displacement system, a self-adaptive fuzzy Proportional Integration Differential (PID) controller is designed based on the traditional digital PID controller combining with fuzzy control. The arithmetic gives a fuzzy control rule table with the fuzzy control rule and fuzzy reasoning, through this table, the PID parameters can be adjusted online in real time control. Furthermore, the automatic selective control is achieved according to the change of the error. The controller combines the good dynamic capability of the fuzzy control and the high stable precision of the PID control, adopts the method of using fuzzy control and PID control in different segments of time. In the initial and middle stage of the transition process of system, that is, when the error is larger than the value, fuzzy control is used to adjust control variable. It makes full use of the fast response of the fuzzy control. And when the error is smaller than the value, the system is about to be in the steady state, PID control is adopted to eliminate static error. The problems of PZT existing in the field of precise positioning are overcome. The results of the experiments prove that the project is correct and practicable.

Integrated model reference adaptive control and time-varying angular rate estimation for micro-machined gyroscopes

NASA Astrophysics Data System (ADS)

Tsai, Nan-Chyuan; Sue, Chung-Yang

2010-02-01

Owing to the imposed but undesired accelerations such as quadrature error and cross-axis perturbation, the micro-machined gyroscope would not be unconditionally retained at resonant mode. Once the preset resonance is not sustained, the performance of the micro-gyroscope is accordingly degraded. In this article, a direct model reference adaptive control loop which is integrated with a modified disturbance estimating observer (MDEO) is proposed to guarantee the resonant oscillations at drive mode and counterbalance the undesired disturbance mainly caused by quadrature error and cross-axis perturbation. The parameters of controller are on-line innovated by the dynamic error between the MDEO output and expected response. In addition, Lyapunov stability theory is employed to examine the stability of the closed-loop control system. Finally, the efficacy of numerical evaluation on the exerted time-varying angular rate, which is to be detected and measured by the gyroscope, is verified by intensive simulations.

Climbing fibers predict movement kinematics and performance errors.

PubMed

Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

2017-09-01

Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each parameter. In contrast with the view that CSs carry feedback signals, the CSs are predominantly predictive of upcoming position errors and kinematics. Therefore, climbing fibers carry multiple and predictive signals for online motor control. Copyright © 2017 the American Physiological Society.

Synthesis of Arbitrary Quantum Circuits to Topological Assembly: Systematic, Online and Compact.

PubMed

Paler, Alexandru; Fowler, Austin G; Wille, Robert

2017-09-05

It is challenging to transform an arbitrary quantum circuit into a form protected by surface code quantum error correcting codes (a variant of topological quantum error correction), especially if the goal is to minimise overhead. One of the issues is the efficient placement of magic state distillation sub circuits, so-called distillation boxes, in the space-time volume that abstracts the computation's required resources. This work presents a general, systematic, online method for the synthesis of such circuits. Distillation box placement is controlled by so-called schedulers. The work introduces a greedy scheduler generating compact box placements. The implemented software, whose source code is available at www.github.com/alexandrupaler/tqec, is used to illustrate and discuss synthesis examples. Synthesis and optimisation improvements are proposed.

Adaptive near-optimal neuro controller for continuous-time nonaffine nonlinear systems with constrained input.

PubMed

Esfandiari, Kasra; Abdollahi, Farzaneh; Talebi, Heidar Ali

2017-09-01

In this paper, an identifier-critic structure is introduced to find an online near-optimal controller for continuous-time nonaffine nonlinear systems having saturated control signal. By employing two Neural Networks (NNs), the solution of Hamilton-Jacobi-Bellman (HJB) equation associated with the cost function is derived without requiring a priori knowledge about system dynamics. Weights of the identifier and critic NNs are tuned online and simultaneously such that unknown terms are approximated accurately and the control signal is kept between the saturation bounds. The convergence of NNs' weights, identification error, and system states is guaranteed using Lyapunov's direct method. Finally, simulation results are performed on two nonlinear systems to confirm the effectiveness of the proposed control strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.

PubMed

Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun

2017-03-01

H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.

Feedback control by online learning an inverse model.

PubMed

Waegeman, Tim; Wyffels, Francis; Schrauwen, Francis

2012-10-01

A model, predictor, or error estimator is often used by a feedback controller to control a plant. Creating such a model is difficult when the plant exhibits nonlinear behavior. In this paper, a novel online learning control framework is proposed that does not require explicit knowledge about the plant. This framework uses two learning modules, one for creating an inverse model, and the other for actually controlling the plant. Except for their inputs, they are identical. The inverse model learns by the exploration performed by the not yet fully trained controller, while the actual controller is based on the currently learned model. The proposed framework allows fast online learning of an accurate controller. The controller can be applied on a broad range of tasks with different dynamic characteristics. We validate this claim by applying our control framework on several control tasks: 1) the heating tank problem (slow nonlinear dynamics); 2) flight pitch control (slow linear dynamics); and 3) the balancing problem of a double inverted pendulum (fast linear and nonlinear dynamics). The results of these experiments show that fast learning and accurate control can be achieved. Furthermore, a comparison is made with some classical control approaches, and observations concerning convergence and stability are made.

The planning coordinator: A design architecture for autonomous error recovery and on-line planning of intelligent tasks

NASA Technical Reports Server (NTRS)

Farah, Jeffrey J.

1992-01-01

Developing a robust, task level, error recovery and on-line planning architecture is an open research area. There is previously published work on both error recovery and on-line planning; however, none incorporates error recovery and on-line planning into one integrated platform. The integration of these two functionalities requires an architecture that possesses the following characteristics. The architecture must provide for the inclusion of new information without the destruction of existing information. The architecture must provide for the relating of pieces of information, old and new, to one another in a non-trivial rather than trivial manner (e.g., object one is related to object two under the following constraints, versus, yes, they are related; no, they are not related). Finally, the architecture must be not only a stand alone architecture, but also one that can be easily integrated as a supplement to some existing architecture. This thesis proposal addresses architectural development. Its intent is to integrate error recovery and on-line planning onto a single, integrated, multi-processor platform. This intelligent x-autonomous platform, called the Planning Coordinator, will be used initially to supplement existing x-autonomous systems and eventually replace them.

Assessing the Library Homepages of COPLAC Institutions for Section 508 Accessibility Errors: Who's Accessible, Who's Not, and How the Online WebXACT Assessment Tool Can Help

ERIC Educational Resources Information Center

Huprich, Julia; Green, Ravonne

2007-01-01

The Council on Public Liberal Arts Colleges (COPLAC) libraries websites were assessed for Section 508 errors using the online WebXACT tool. Only three of the twenty-one institutions (14%) had zero accessibility errors. Eighty-six percent of the COPLAC institutions had an average of 1.24 errors. Section 508 compliance is required for institutions…

Online patient safety education programme for junior doctors: is it worthwhile?

PubMed

McCarthy, S E; O'Boyle, C A; O'Shaughnessy, A; Walsh, G

2016-02-01

Increasing demand exists for blended approaches to the development of professionalism. Trainees of the Royal College of Physicians of Ireland participated in an online patient safety programme. Study aims were: (1) to determine whether the programme improved junior doctors' knowledge, attitudes and skills relating to error reporting, open communication and care for the second victim and (2) to establish whether the methodology facilitated participants' learning. 208 junior doctors who completed the programme completed a pre-online questionnaire. Measures were "patient safety knowledge and attitudes", "medical safety climate" and "experience of learning". Sixty-two completed the post-questionnaire, representing a 30 % matched response rate. Participating in the programme resulted in immediate (p < 0.01) improvement in skills such as knowing when and how to complete incident forms and disclosing errors to patients, in self-rated knowledge (p < 0.01) and attitudes towards error reporting (p < 0.01). Sixty-three per cent disagreed that doctors routinely report medical errors and 42 % disagreed that doctors routinely share information about medical errors and what caused them. Participants rated interactive features as the most positive elements of the programme. An online training programme on medical error improved self-rated knowledge, attitudes and skills in junior doctors and was deemed an effective learning tool. Perceptions of work issues such as a poor culture of error reporting among doctors may prevent improved attitudes being realised in practice. Online patient safety education has a role in practice-based initiatives aimed at developing professionalism and improving safety.

Crowdsourcing for error detection in cortical surface delineations.

PubMed

Ganz, Melanie; Kondermann, Daniel; Andrulis, Jonas; Knudsen, Gitte Moos; Maier-Hein, Lena

2017-01-01

With the recent trend toward big data analysis, neuroimaging datasets have grown substantially in the past years. While larger datasets potentially offer important insights for medical research, one major bottleneck is the requirement for resources of medical experts needed to validate automatic processing results. To address this issue, the goal of this paper was to assess whether anonymous nonexperts from an online community can perform quality control of MR-based cortical surface delineations derived by an automatic algorithm. So-called knowledge workers from an online crowdsourcing platform were asked to annotate errors in automatic cortical surface delineations on 100 central, coronal slices of MR images. On average, annotations for 100 images were obtained in less than an hour. When using expert annotations as reference, the crowd on average achieves a sensitivity of 82 % and a precision of 42 %. Merging multiple annotations per image significantly improves the sensitivity of the crowd (up to 95 %), but leads to a decrease in precision (as low as 22 %). Our experiments show that the detection of errors in automatic cortical surface delineations generated by anonymous untrained workers is feasible. Future work will focus on increasing the sensitivity of our method further, such that the error detection tasks can be handled exclusively by the crowd and expert resources can be focused on error correction.

Electronic laboratory system reduces errors in National Tuberculosis Program: a cluster randomized controlled trial.

PubMed

Blaya, J A; Shin, S S; Yale, G; Suarez, C; Asencios, L; Contreras, C; Rodriguez, P; Kim, J; Cegielski, P; Fraser, H S F

2010-08-01

To evaluate the impact of the e-Chasqui laboratory information system in reducing reporting errors compared to the current paper system. Cluster randomized controlled trial in 76 health centers (HCs) between 2004 and 2008. Baseline data were collected every 4 months for 12 months. HCs were then randomly assigned to intervention (e-Chasqui) or control (paper). Further data were collected for the same months the following year. Comparisons were made between intervention and control HCs, and before and after the intervention. Intervention HCs had respectively 82% and 87% fewer errors in reporting results for drug susceptibility tests (2.1% vs. 11.9%, P = 0.001, OR 0.17, 95%CI 0.09-0.31) and cultures (2.0% vs. 15.1%, P < 0.001, OR 0.13, 95%CI 0.07-0.24), than control HCs. Preventing missing results through online viewing accounted for at least 72% of all errors. e-Chasqui users sent on average three electronic error reports per week to the laboratories. e-Chasqui reduced the number of missing laboratory results at point-of-care health centers. Clinical users confirmed viewing electronic results not available on paper. Reporting errors to the laboratory using e-Chasqui promoted continuous quality improvement. The e-Chasqui laboratory information system is an important part of laboratory infrastructure improvements to support multidrug-resistant tuberculosis care in Peru.

Unscented predictive variable structure filter for satellite attitude estimation with model errors when using low precision sensors

NASA Astrophysics Data System (ADS)

Cao, Lu; Li, Hengnian

2016-10-01

For the satellite attitude estimation problem, the serious model errors always exist and hider the estimation performance of the Attitude Determination and Control System (ACDS), especially for a small satellite with low precision sensors. To deal with this problem, a new algorithm for the attitude estimation, referred to as the unscented predictive variable structure filter (UPVSF) is presented. This strategy is proposed based on the variable structure control concept and unscented transform (UT) sampling method. It can be implemented in real time with an ability to estimate the model errors on-line, in order to improve the state estimation precision. In addition, the model errors in this filter are not restricted only to the Gaussian noises; therefore, it has the advantages to deal with the various kinds of model errors or noises. It is anticipated that the UT sampling strategy can further enhance the robustness and accuracy of the novel UPVSF. Numerical simulations show that the proposed UPVSF is more effective and robustness in dealing with the model errors and low precision sensors compared with the traditional unscented Kalman filter (UKF).

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-09-07

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

Target Uncertainty Mediates Sensorimotor Error Correction

PubMed Central

Vijayakumar, Sethu; Wolpert, Daniel M.

2017-01-01

Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects’ scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one’s response. By suggesting that subjects’ decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated. PMID:28129323

Target Uncertainty Mediates Sensorimotor Error Correction.

PubMed

Acerbi, Luigi; Vijayakumar, Sethu; Wolpert, Daniel M

2017-01-01

Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects' scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one's response. By suggesting that subjects' decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated.

A Sequential Analysis of Responses in Online Debates to Postings of Students Exhibiting High Versus Low Grammar and Spelling Errors

ERIC Educational Resources Information Center

Jeong, Allan; Li, Haiying; Pan, Andy Jiaren

2017-01-01

Given that grammatical and spelling errors have been found to influence perceived competence and credibility in written communication, this study examined how a student's grammar and spelling errors affect how other students respond to the student's postings in four online debates hosted in asynchronous threaded discussions. Message-response…

Binocular and Monocular Depth Cues in Online Feedback Control of 3-D Pointing Movement

PubMed Central

Hu, Bo; Knill, David C.

2012-01-01

Previous work has shown that humans continuously use visual feedback of the hand to control goal-directed movements online. In most studies, visual error signals were predominantly in the image plane and thus were available in an observer’s retinal image. We investigate how humans use visual feedback about finger depth provided by binocular and monocular depth cues to control pointing movements. When binocularly viewing a scene in which the hand movement was made in free space, subjects were about 60 ms slower in responding to perturbations in depth than in the image plane. When monocularly viewing a scene designed to maximize the available monocular cues to finger depth (motion, changing size and cast shadows), subjects showed no response to perturbations in depth. Thus, binocular cues from the finger are critical to effective online control of hand movements in depth. An optimal feedback controller that takes into account of the low peripheral stereoacuity and inherent ambiguity in cast shadows can explain the difference in response time in the binocular conditions and lack of response in monocular conditions. PMID:21724567

Stable modeling based control methods using a new RBF network.

PubMed

Beyhan, Selami; Alci, Musa

2010-10-01

This paper presents a novel model with radial basis functions (RBFs), which is applied successively for online stable identification and control of nonlinear discrete-time systems. First, the proposed model is utilized for direct inverse modeling of the plant to generate the control input where it is assumed that inverse plant dynamics exist. Second, it is employed for system identification to generate a sliding-mode control input. Finally, the network is employed to tune PID (proportional + integrative + derivative) controller parameters automatically. The adaptive learning rate (ALR), which is employed in the gradient descent (GD) method, provides the global convergence of the modeling errors. Using the Lyapunov stability approach, the boundedness of the tracking errors and the system parameters are shown both theoretically and in real time. To show the superiority of the new model with RBFs, its tracking results are compared with the results of a conventional sigmoidal multi-layer perceptron (MLP) neural network and the new model with sigmoid activation functions. To see the real-time capability of the new model, the proposed network is employed for online identification and control of a cascaded parallel two-tank liquid-level system. Even though there exist large disturbances, the proposed model with RBFs generates a suitable control input to track the reference signal better than other methods in both simulations and real time. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles

NASA Astrophysics Data System (ADS)

Zheng, Yuejiu; Ouyang, Minggao; Han, Xuebing; Lu, Languang; Li, Jianqiu

2018-02-01

Sate of charge (SOC) estimation is generally acknowledged as one of the most important functions in battery management system for lithium-ion batteries in new energy vehicles. Though every effort is made for various online SOC estimation methods to reliably increase the estimation accuracy as much as possible within the limited on-chip resources, little literature discusses the error sources for those SOC estimation methods. This paper firstly reviews the commonly studied SOC estimation methods from a conventional classification. A novel perspective focusing on the error analysis of the SOC estimation methods is proposed. SOC estimation methods are analyzed from the views of the measured values, models, algorithms and state parameters. Subsequently, the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation methods in new energy vehicles. Finally, with the consideration of the working conditions, choosing more reliable and applicable SOC estimation methods is discussed, and the future development of the promising online SOC estimation methods is suggested.

[On-line monitoring of biomass in 1,3-propanediol fermentation by Fourier-transformed near-infrared spectra analysis].

PubMed

Wang, Lu; Liu, Tao; Chen, Yang; Sun, Yaqin; Xiu, Zhilong

2017-01-25

Biomass is an important parameter reflecting the fermentation dynamics. Real-time monitoring of biomass can be used to control and optimize a fermentation process. To overcome the deficiencies of measurement delay and manual errors from offline measurement, we designed an experimental platform for online monitoring the biomass during a 1,3-propanediol fermentation process, based on using the fourier-transformed near-infrared (FT-NIR) spectra analysis. By pre-processing the real-time sampled spectra and analyzing the sensitive spectra bands, a partial least-squares algorithm was proposed to establish a dynamic prediction model for the biomass change during a 1,3-propanediol fermentation process. The fermentation processes with substrate glycerol concentrations of 60 g/L and 40 g/L were used as the external validation experiments. The root mean square error of prediction (RMSEP) obtained by analyzing experimental data was 0.341 6 and 0.274 3, respectively. These results showed that the established model gave good prediction and could be effectively used for on-line monitoring the biomass during a 1,3-propanediol fermentation process.

Adaptive control of nonlinear uncertain active suspension systems with prescribed performance.

PubMed

Huang, Yingbo; Na, Jing; Wu, Xing; Liu, Xiaoqin; Guo, Yu

2015-01-01

This paper proposes adaptive control designs for vehicle active suspension systems with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise linear damper dynamics). An adaptive control is first proposed to stabilize the vertical vehicle displacement and thus to improve the ride comfort and to guarantee other suspension requirements (e.g., road holding and suspension space limitation) concerning the vehicle safety and mechanical constraints. An augmented neural network is developed to online compensate for the unknown nonlinearities, and a novel adaptive law is developed to estimate both NN weights and uncertain model parameters (e.g., sprung mass), where the parameter estimation error is used as a leakage term superimposed on the classical adaptations. To further improve the control performance and simplify the parameter tuning, a prescribed performance function (PPF) characterizing the error convergence rate, maximum overshoot and steady-state error is used to propose another adaptive control. The stability for the closed-loop system is proved and particular performance requirements are analyzed. Simulations are included to illustrate the effectiveness of the proposed control schemes. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Online measurement of bead geometry in GMAW-based additive manufacturing using passive vision

NASA Astrophysics Data System (ADS)

Xiong, Jun; Zhang, Guangjun

2013-11-01

Additive manufacturing based on gas metal arc welding is an advanced technique for depositing fully dense components with low cost. Despite this fact, techniques to achieve accurate control and automation of the process have not yet been perfectly developed. The online measurement of the deposited bead geometry is a key problem for reliable control. In this work a passive vision-sensing system, comprising two cameras and composite filtering techniques, was proposed for real-time detection of the bead height and width through deposition of thin walls. The nozzle to the top surface distance was monitored for eliminating accumulated height errors during the multi-layer deposition process. Various image processing algorithms were applied and discussed for extracting feature parameters. A calibration procedure was presented for the monitoring system. Validation experiments confirmed the effectiveness of the online measurement system for bead geometry in layered additive manufacturing.

Prediction of Safety Stock Using Fuzzy Time Series (FTS) and Technology of Radio Frequency Identification (RFID) for Stock Control at Vendor Managed Inventory (VMI)

NASA Astrophysics Data System (ADS)

Mashuri, Chamdan; Suryono; Suseno, Jatmiko Endro

2018-02-01

This research was conducted by prediction of safety stock using Fuzzy Time Series (FTS) and technology of Radio Frequency Identification (RFID) for stock control at Vendor Managed Inventory (VMI). Well-controlled stock influenced company revenue and minimized cost. It discussed about information system of safety stock prediction developed through programming language of PHP. Input data consisted of demand got from automatic, online and real time acquisition using technology of RFID, then, sent to server and stored at online database. Furthermore, data of acquisition result was predicted by using algorithm of FTS applying universe of discourse defining and fuzzy sets determination. Fuzzy set result was continued to division process of universe of discourse in order to be to final step. Prediction result was displayed at information system dashboard developed. By using 60 data from demand data, prediction score was 450.331 and safety stock was 135.535. Prediction result was done by error deviation validation using Mean Square Percent Error of 15%. It proved that FTS was good enough in predicting demand and safety stock for stock control. For deeper analysis, researchers used data of demand and universe of discourse U varying at FTS to get various result based on test data used.

Lattice Commissioning Stretgy Simulation for the B Factory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, M.; Whittum, D.; Yan, Y.

2011-08-26

To prepare for the PEP-II turn on, we have studied one commissioning strategy with simulated lattice errors. Features such as difference and absolute orbit analysis and correction are discussed. To prepare for the commissioning of the PEP-II injection line and high energy ring (HER), we have developed a system for on-line orbit analysis by merging two existing codes: LEGO and RESOLVE. With the LEGO-RESOLVE system, we can study the problem of finding quadrupole alignment and beam position (BPM) offset errors with simulated data. We have increased the speed and versatility of the orbit analysis process by using a command filemore » written in a script language designed specifically for RESOLVE. In addition, we have interfaced the LEGO-RESOLVE system to the control system of the B-Factory. In this paper, we describe online analysis features of the LEGO-RESOLVE system and present examples of practical applications.« less

A hand and a field effect in on-line motor control in unilateral optic ataxia.

PubMed

Blangero, Annabelle; Gaveau, Valérie; Luauté, Jacques; Rode, Gilles; Salemme, Romeo; Guinard, Marine; Boisson, Dominique; Rossetti, Yves; Pisella, Laure

2008-05-01

Patients with bilateral optic ataxia fail to show rapid perturbation-induced corrections during manual aiming movements. Based on this, it has been proposed that this pathology results from a disruption of processes of on-line motor control in the posterior parietal cortex (PPC). Here, we show that on-line motor control performance in a patient with unilateral optic ataxia is similar to that of pointing towards stationary targets in peripheral vision, showing the same combination of hand and field effects. We also show that in the patient, manual correction towards his ataxic field was possible only when a preceding saccade (100msec earlier) rapidly provides foveal information about the new target location. In control subjects, manual correction was often, but not necessarily preceded by a saccade. These results allow us to put forward a model of visuo-manual transformation, which involves updating of the reach plan based on the target-eye error, and rely upon two dissociated spatial representations (of the hand and of the target, respectively) within the PPC.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Dynamic modelling and estimation of the error due to asynchronism in a redundant asynchronous multiprocessor system

NASA Technical Reports Server (NTRS)

Huynh, Loc C.; Duval, R. W.

1986-01-01

The use of Redundant Asynchronous Multiprocessor System to achieve ultrareliable Fault Tolerant Control Systems shows great promise. The development has been hampered by the inability to determine whether differences in the outputs of redundant CPU's are due to failures or to accrued error built up by slight differences in CPU clock intervals. This study derives an analytical dynamic model of the difference between redundant CPU's due to differences in their clock intervals and uses this model with on-line parameter identification to idenitify the differences in the clock intervals. The ability of this methodology to accurately track errors due to asynchronisity generate an error signal with the effect of asynchronisity removed and this signal may be used to detect and isolate actual system failures.

Output feedback control of a quadrotor UAV using neural networks.

PubMed

Dierks, Travis; Jagannathan, Sarangapani

2010-01-01

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

Caveat emptor: Erroneous safety information about opioids in online drug-information compendia.

PubMed

Talwar, Sonia R; Randhawa, Amarita S; Dankiewicz, Erica H; Crudele, Nancy T; Haddox, J David

2016-01-01

Healthcare professionals and consumers refer to online drug-information compendia (eg, Epocrates and WebMD) to learn about prescription medications, including opioid analgesics. With the significant risks associated with opioids, including abuse, misuse, and addiction, any of which can result in life-threatening overdose, it is important for those seeking information from online compendia to have access to current, accurate, and complete drug information to help support clinical treatment decisions. Although compendia are informative, readily available, and user friendly, studies have shown that they may contain errors. To review and identify misinformation in drug summaries of online drug-information compendia for selected opioid analgesic products and submit content corrections to the respective editors. Between 2011 and 2013, drug summaries for Purdue's prescription opioid analgesic products from seven leading online drug-information compendia were systematically reviewed, and the requests for corrections were retrospectively categorized and classified. At least 2 months following requests, the same compendia were then reexamined to assess the degree of error resolution. A total of 859 errors were identified, with the greatest percentage in Safety and Patient Education categories. Across the seven compendia, the complete or partial resolution of errors was 34 percent; therefore, nearly two thirds of the identified errors remain. The results of this analysis, consistent with past studies, demonstrate that online drug-information compendia may contain inaccurate information. Healthcare professionals and consumers must be informed of potential misinformation so they may consider using multiple resources to obtain accurate and current drug information, thereby helping to ensure safer use of prescription medications, such as opioids.

A New KE-Free Online ICALL System Featuring Error Contingent Feedback

ERIC Educational Resources Information Center

Tokuda, Naoyuki; Chen, Liang

2004-01-01

As a first step towards implementing a human language teacher, we have developed a new template-based on-line ICALL (intelligent computer assisted language learning) system capable of automatically diagnosing learners' free-format translated inputs and returning error contingent feedback. The system architecture we have adopted allows language…

Masked and unmasked error-related potentials during continuous control and feedback

NASA Astrophysics Data System (ADS)

Lopes Dias, Catarina; Sburlea, Andreea I.; Müller-Putz, Gernot R.

2018-06-01

The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in tasks with continuous feedback is still in its early stages. Objective. We developed a task in which subjects have continuous control of a cursor’s position by means of a joystick. The cursor’s position was shown to the participants in two different modalities of continuous feedback: normal and jittered. The jittered feedback was created to mimic the instability that could exist if participants controlled the trajectory directly with brain signals. Approach. This paper studies the electroencephalographic (EEG)—measurable signatures caused by a loss of control over the cursor’s trajectory, causing a target miss. Main results. In both feedback modalities, time-locked potentials revealed the typical frontal-central components of error-related potentials. Errors occurring during the jittered feedback (masked errors) were delayed in comparison to errors occurring during normal feedback (unmasked errors). Masked errors displayed lower peak amplitudes than unmasked errors. Time-locked classification analysis allowed a good distinction between correct and error classes (average Cohen-, average TPR  =  81.8% and average TNR  =  96.4%). Time-locked classification analysis between masked error and unmasked error classes revealed results at chance level (average Cohen-, average TPR  =  60.9% and average TNR  =  58.3%). Afterwards, we performed asynchronous detection of ErrPs, combining both masked and unmasked trials. The asynchronous detection of ErrPs in a simulated online scenario resulted in an average TNR of 84.0% and in an average TPR of 64.9%. Significance. The time-locked classification results suggest that the masked and unmasked errors were indistinguishable in terms of classification. The asynchronous classification results suggest that the feedback modality did not hinder the asynchronous detection of ErrPs.

IIR filtering based adaptive active vibration control methodology with online secondary path modeling using PZT actuators

NASA Astrophysics Data System (ADS)

Boz, Utku; Basdogan, Ipek

2015-12-01

Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.

Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation

NASA Astrophysics Data System (ADS)

Shankar, Praveen

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network based adaptive controller. While the fixed RBF network based controller which is tuned to compensate for control surface failures fails to achieve the same performance under modeling uncertainty and disturbances, the SORBFN is able to achieve good tracking convergence under all error conditions.

An adaptive nonlinear internal-model control for the speed control of homopolar salient-pole BLDC motor

NASA Astrophysics Data System (ADS)

CheshmehBeigi, Hassan Moradi

2018-05-01

In this paper, a novel speed control method for Homopolar Brushless DC (HBLDC) motor based on the adaptive nonlinear internal-model control (ANIMC) is presented. Rotor position information is obtained online by the Hall-Effect sensors placed on the motor's shaft, and is used to calculate the accurate model and accurate inverse model of the HBLDC motor. The online inverse model of the motor is used in the controller structure. To suppress the reference ? error, the negative feedback of difference between the motor speed and its model output ? is applied in the proposed controller. An appropriate signal is the output of the controller, which drives the power switches to converge the motor speed to the constant desired speed. Simulations and experiments are carried out on a ? three-phase HBLDC motor. The proposed drive system operates well in the speed response and has good robustness with respect to the disturbances. To validate the theoretical analysis, several experimental results are discussed in this paper.

Continuous performance measurement in flight systems. [sequential control model

NASA Technical Reports Server (NTRS)

Connelly, E. M.; Sloan, N. A.; Zeskind, R. M.

1975-01-01

The desired response of many man machine control systems can be formulated as a solution to an optimal control synthesis problem where the cost index is given and the resulting optimal trajectories correspond to the desired trajectories of the man machine system. Optimal control synthesis provides the reference criteria and the significance of error information required for performance measurement. The synthesis procedure described provides a continuous performance measure (CPM) which is independent of the mechanism generating the control action. Therefore, the technique provides a meaningful method for online evaluation of man's control capability in terms of total man machine performance.

A comparison of the use of bony anatomy and internal markers for offline verification and an evaluation of the potential benefit of online and offline verification protocols for prostate radiotherapy.

PubMed

McNair, Helen A; Hansen, Vibeke N; Parker, Christopher C; Evans, Phil M; Norman, Andrew; Miles, Elizabeth; Harris, Emma J; Del-Acroix, Louise; Smith, Elizabeth; Keane, Richard; Khoo, Vincent S; Thompson, Alan C; Dearnaley, David P

2008-05-01

To evaluate the utility of intraprostatic markers in the treatment verification of prostate cancer radiotherapy. Specific aims were: to compare the effectiveness of offline correction protocols, either using gold markers or bony anatomy; to estimate the potential benefit of online correction protocol's using gold markers; to determine the presence and effect of intrafraction motion. Thirty patients with three gold markers inserted had pretreatment and posttreatment images acquired and were treated using an offline correction protocol and gold markers. Retrospectively, an offline protocol was applied using bony anatomy and an online protocol using gold markers. The systematic errors were reduced from 1.3, 1.9, and 2.5 mm to 1.1, 1.1, and 1.5 mm in the right-left (RL), superoinferior (SI), and anteroposterior (AP) directions, respectively, using the offline correction protocol and gold markers instead of bony anatomy. The subsequent decrease in margins was 1.7, 3.3, and 4 mm in the RL, SI, and AP directions, respectively. An offline correction protocol combined with an online correction protocol in the first four fractions reduced random errors further to 0.9, 1.1, and 1.0 mm in the RL, SI, and AP directions, respectively. A daily online protocol reduced all errors to <1 mm. Intrafraction motion had greater impact on the effectiveness of the online protocol than the offline protocols. An offline protocol using gold markers is effective in reducing the systematic error. The value of online protocols is reduced by intrafraction motion.

DC servomechanism parameter identification: a Closed Loop Input Error approach.

PubMed

Garrido, Ruben; Miranda, Roger

2012-01-01

This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control law employed for closing the loop. The model contains four parameters that depend on the servo inertia, viscous, and Coulomb friction as well as on a constant disturbance. Lyapunov stability theory permits assessing boundedness of the signals associated to the identification algorithm. Experiments on a laboratory prototype allows evaluating the performance of the approach. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Learning a visuomotor rotation: simultaneous visual and proprioceptive information is crucial for visuomotor remapping.

PubMed

Shabbott, Britne A; Sainburg, Robert L

2010-05-01

Visuomotor adaptation is mediated by errors between intended and sensory-detected arm positions. However, it is not clear whether visual-based errors that are shown during the course of motion lead to qualitatively different or more efficient adaptation than errors shown after movement. For instance, continuous visual feedback mediates online error corrections, which may facilitate or inhibit the adaptation process. We addressed this question by manipulating the timing of visual error information and task instructions during a visuomotor adaptation task. Subjects were exposed to a visuomotor rotation, during which they received continuous visual feedback (CF) of hand position with instructions to correct or not correct online errors, or knowledge-of-results (KR), provided as a static hand-path at the end of each trial. Our results showed that all groups improved performance with practice, and that online error corrections were inconsequential to the adaptation process. However, in contrast to the CF groups, the KR group showed relatively small reductions in mean error with practice, increased inter-trial variability during rotation exposure, and more limited generalization across target distances and workspace. Further, although the KR group showed improved performance with practice, after-effects were minimal when the rotation was removed. These findings suggest that simultaneous visual and proprioceptive information is critical in altering neural representations of visuomotor maps, although delayed error information may elicit compensatory strategies to offset perturbations.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

NASA Astrophysics Data System (ADS)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

Quality Control of Meteorological Observations

NASA Technical Reports Server (NTRS)

Collins, William; Dee, Dick; Rukhovets, Leonid

1999-01-01

For the first time, a problem of the meteorological observation quality control (QC) was formulated by L.S. Gandin at the Main Geophysical Observatory in the 70's. Later in 1988 L.S. Gandin began adapting his ideas in complex quality control (CQC) to the operational environment at the National Centers for Environmental Prediction. The CQC was first applied by L.S.Gandin and his colleagues to detection and correction of errors in rawinsonde heights and temperatures using a complex of hydrostatic residuals.Later, a full complex of residuals, vertical and horizontal optimal interpolations and baseline checks were added for the checking and correction of a wide range of meteorological variables. some other of Gandin's ideas were applied and substantially developed at other meteorological centers. A new statistical QC was recently implemented in the Goddard Data Assimilation System. The central component of any quality control is a buddy check which is a test of individual suspect observations against available nearby non-suspect observations. A novel feature of this test is that the error variances which are used for QC decision are re-estimated on-line. As a result, the allowed tolerances for suspect observations can depend on local atmospheric conditions. The system is then better able to accept extreme values observed in deep cyclones, jet streams and so on. The basic statements of this adaptive buddy check are described. Some results of the on-line QC including moisture QC are presented.

Adaptive fuzzy logic controller with direct action type structures for InnoSAT attitude control system

NASA Astrophysics Data System (ADS)

Bakri, F. A.; Mashor, M. Y.; Sharun, S. M.; Bibi Sarpinah, S. N.; Abu Bakar, Z.

2016-10-01

This study proposes an adaptive fuzzy controller for attitude control system (ACS) of Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new methods used in satellite attitude control, this paper presents three structures of controllers: Fuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the time response and tracking performance among the three different structures of controllers. The parameters of controller were tuned on-line by adjustment mechanism, which was an approach similar to a PID error that could minimize errors between actual and model reference output. This paper also presents a Model References Adaptive Control (MRAC) as a control scheme to control time varying systems where the performance specifications were given in terms of the reference model. All the controllers were tested using InnoSAT system under some operating conditions such as disturbance, varying gain, measurement noise and time delay. In conclusion, among all considered DA-type structures, AFPID controller was observed as the best structure since it outperformed other controllers in most conditions.

Dynamic Analyses of Result Quality in Energy-Aware Approximate Programs

NASA Astrophysics Data System (ADS)

RIngenburg, Michael F.

Energy efficiency is a key concern in the design of modern computer systems. One promising approach to energy-efficient computation, approximate computing, trades off output precision for energy efficiency. However, this tradeoff can have unexpected effects on computation quality. This thesis presents dynamic analysis tools to study, debug, and monitor the quality and energy efficiency of approximate computations. We propose three styles of tools: prototyping tools that allow developers to experiment with approximation in their applications, online tools that instrument code to determine the key sources of error, and online tools that monitor the quality of deployed applications in real time. Our prototyping tool is based on an extension to the functional language OCaml. We add approximation constructs to the language, an approximation simulator to the runtime, and profiling and auto-tuning tools for studying and experimenting with energy-quality tradeoffs. We also present two online debugging tools and three online monitoring tools. The first online tool identifies correlations between output quality and the total number of executions of, and errors in, individual approximate operations. The second tracks the number of approximate operations that flow into a particular value. Our online tools comprise three low-cost approaches to dynamic quality monitoring. They are designed to monitor quality in deployed applications without spending more energy than is saved by approximation. Online monitors can be used to perform real time adjustments to energy usage in order to meet specific quality goals. We present prototype implementations of all of these tools and describe their usage with several applications. Our prototyping, profiling, and autotuning tools allow us to experiment with approximation strategies and identify new strategies, our online tools succeed in providing new insights into the effects of approximation on output quality, and our monitors succeed in controlling output quality while still maintaining significant energy efficiency gains.

Bibliographic Instruction and the Development of Online Catalogs.

ERIC Educational Resources Information Center

McDonald, David R.; Searing, Susan E.

1983-01-01

Discusses the definition of an online library catalog; five factors to be considered by the online catalog designer; user-computer communication (error messages, help screens, prompts, unnatural language); online tutorials and offline instruction offered by bibliographic instruction librarians; and the current situation. Nine references are…

WE-D-BRA-04: Online 3D EPID-Based Dose Verification for Optimum Patient Safety

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spreeuw, H; Rozendaal, R; Olaciregui-Ruiz, I

2015-06-15

Purpose: To develop an online 3D dose verification tool based on EPID transit dosimetry to ensure optimum patient safety in radiotherapy treatments. Methods: A new software package was developed which processes EPID portal images online using a back-projection algorithm for the 3D dose reconstruction. The package processes portal images faster than the acquisition rate of the portal imager (∼ 2.5 fps). After a portal image is acquired, the software seeks for “hot spots” in the reconstructed 3D dose distribution. A hot spot is in this study defined as a 4 cm{sup 3} cube where the average cumulative reconstructed dose exceedsmore » the average total planned dose by at least 20% and 50 cGy. If a hot spot is detected, an alert is generated resulting in a linac halt. The software has been tested by irradiating an Alderson phantom after introducing various types of serious delivery errors. Results: In our first experiment the Alderson phantom was irradiated with two arcs from a 6 MV VMAT H&N treatment having a large leaf position error or a large monitor unit error. For both arcs and both errors the linac was halted before dose delivery was completed. When no error was introduced, the linac was not halted. The complete processing of a single portal frame, including hot spot detection, takes about 220 ms on a dual hexacore Intel Xeon 25 X5650 CPU at 2.66 GHz. Conclusion: A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for various kinds of gross delivery errors. The detection of hot spots was proven to be effective for the timely detection of these errors. Current work is focused on hot spot detection criteria for various treatment sites and the introduction of a clinical pilot program with online verification of hypo-fractionated (lung) treatments.« less

Stable adaptive PI control for permanent magnet synchronous motor drive based on improved JITL technique.

PubMed

Zheng, Shiqi; Tang, Xiaoqi; Song, Bao; Lu, Shaowu; Ye, Bosheng

2013-07-01

In this paper, a stable adaptive PI control strategy based on the improved just-in-time learning (IJITL) technique is proposed for permanent magnet synchronous motor (PMSM) drive. Firstly, the traditional JITL technique is improved. The new IJITL technique has less computational burden and is more suitable for online identification of the PMSM drive system which is highly real-time compared to traditional JITL. In this way, the PMSM drive system is identified by IJITL technique, which provides information to an adaptive PI controller. Secondly, the adaptive PI controller is designed in discrete time domain which is composed of a PI controller and a supervisory controller. The PI controller is capable of automatically online tuning the control gains based on the gradient descent method and the supervisory controller is developed to eliminate the effect of the approximation error introduced by the PI controller upon the system stability in the Lyapunov sense. Finally, experimental results on the PMSM drive system show accurate identification and favorable tracking performance. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

PubMed

Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

2011-04-01

This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

Distributed cooperative H∞ optimal tracking control of MIMO nonlinear multi-agent systems in strict-feedback form via adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Luy, N. T.

2018-04-01

The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

PubMed Central

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks. PMID:28932180

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

PubMed

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

Research on the Error Characteristics of a 110 kV Optical Voltage Transformer under Three Conditions: In the Laboratory, Off-Line in the Field and During On-Line Operation

PubMed Central

Xiao, Xia; Hu, Haoliang; Xu, Yan; Lei, Min; Xiong, Qianzhu

2016-01-01

Optical voltage transformers (OVTs) have been applied in power systems. When performing accuracy performance tests of OVTs large differences exist between the electromagnetic environment and the temperature variation in the laboratory and on-site. Therefore, OVTs may display different error characteristics under different conditions. In this paper, OVT prototypes with typical structures were selected to be tested for the error characteristics with the same testing equipment and testing method. The basic accuracy, the additional error caused by temperature and the adjacent phase in the laboratory, the accuracy in the field off-line, and the real-time monitoring error during on-line operation were tested. The error characteristics under the three conditions—laboratory, in the field off-line and during on-site operation—were compared and analyzed. The results showed that the effect of the transportation process, electromagnetic environment and the adjacent phase on the accuracy of OVTs could be ignored for level 0.2, but the error characteristics of OVTs are dependent on the environmental temperature and are sensitive to the temperature gradient. The temperature characteristics during on-line operation were significantly superior to those observed in the laboratory. PMID:27537895

Research on the Error Characteristics of a 110 kV Optical Voltage Transformer under Three Conditions: In the Laboratory, Off-Line in the Field and During On-Line Operation.

PubMed

Xiao, Xia; Hu, Haoliang; Xu, Yan; Lei, Min; Xiong, Qianzhu

2016-08-16

Optical voltage transformers (OVTs) have been applied in power systems. When performing accuracy performance tests of OVTs large differences exist between the electromagnetic environment and the temperature variation in the laboratory and on-site. Therefore, OVTs may display different error characteristics under different conditions. In this paper, OVT prototypes with typical structures were selected to be tested for the error characteristics with the same testing equipment and testing method. The basic accuracy, the additional error caused by temperature and the adjacent phase in the laboratory, the accuracy in the field off-line, and the real-time monitoring error during on-line operation were tested. The error characteristics under the three conditions-laboratory, in the field off-line and during on-site operation-were compared and analyzed. The results showed that the effect of the transportation process, electromagnetic environment and the adjacent phase on the accuracy of OVTs could be ignored for level 0.2, but the error characteristics of OVTs are dependent on the environmental temperature and are sensitive to the temperature gradient. The temperature characteristics during on-line operation were significantly superior to those observed in the laboratory.

Adaptive integral robust control and application to electromechanical servo systems.

PubMed

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Armstrong, Jeffrey B.; Garg, Sanjay

2012-01-01

An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.

Model-Free Adaptive Control for Unknown Nonlinear Zero-Sum Differential Game.

PubMed

Zhong, Xiangnan; He, Haibo; Wang, Ding; Ni, Zhen

2018-05-01

In this paper, we present a new model-free globalized dual heuristic dynamic programming (GDHP) approach for the discrete-time nonlinear zero-sum game problems. First, the online learning algorithm is proposed based on the GDHP method to solve the Hamilton-Jacobi-Isaacs equation associated with optimal regulation control problem. By setting backward one step of the definition of performance index, the requirement of system dynamics, or an identifier is relaxed in the proposed method. Then, three neural networks are established to approximate the optimal saddle point feedback control law, the disturbance law, and the performance index, respectively. The explicit updating rules for these three neural networks are provided based on the data generated during the online learning along the system trajectories. The stability analysis in terms of the neural network approximation errors is discussed based on the Lyapunov approach. Finally, two simulation examples are provided to show the effectiveness of the proposed method.

A Comparison of the Use of Bony Anatomy and Internal Markers for Offline Verification and an Evaluation of the Potential Benefit of Online and Offline Verification Protocols for Prostate Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

McNair, Helen A.; Hansen, Vibeke N.; Parker, Christopher

2008-05-01

Purpose: To evaluate the utility of intraprostatic markers in the treatment verification of prostate cancer radiotherapy. Specific aims were: to compare the effectiveness of offline correction protocols, either using gold markers or bony anatomy; to estimate the potential benefit of online correction protocol's using gold markers; to determine the presence and effect of intrafraction motion. Methods and Materials: Thirty patients with three gold markers inserted had pretreatment and posttreatment images acquired and were treated using an offline correction protocol and gold markers. Retrospectively, an offline protocol was applied using bony anatomy and an online protocol using gold markers. Results: Themore » systematic errors were reduced from 1.3, 1.9, and 2.5 mm to 1.1, 1.1, and 1.5 mm in the right-left (RL), superoinferior (SI), and anteroposterior (AP) directions, respectively, using the offline correction protocol and gold markers instead of bony anatomy. The subsequent decrease in margins was 1.7, 3.3, and 4 mm in the RL, SI, and AP directions, respectively. An offline correction protocol combined with an online correction protocol in the first four fractions reduced random errors further to 0.9, 1.1, and 1.0 mm in the RL, SI, and AP directions, respectively. A daily online protocol reduced all errors to <1 mm. Intrafraction motion had greater impact on the effectiveness of the online protocol than the offline protocols. Conclusions: An offline protocol using gold markers is effective in reducing the systematic error. The value of online protocols is reduced by intrafraction motion.« less

An online detection system for aggregate sizes and shapes based on digital image processing

NASA Astrophysics Data System (ADS)

Yang, Jianhong; Chen, Sijia

2017-02-01

Traditional aggregate size measuring methods are time-consuming, taxing, and do not deliver online measurements. A new online detection system for determining aggregate size and shape based on a digital camera with a charge-coupled device, and subsequent digital image processing, have been developed to overcome these problems. The system captures images of aggregates while falling and flat lying. Using these data, the particle size and shape distribution can be obtained in real time. Here, we calibrate this method using standard globules. Our experiments show that the maximum particle size distribution error was only 3 wt%, while the maximum particle shape distribution error was only 2 wt% for data derived from falling aggregates, having good dispersion. In contrast, the data for flat-lying aggregates had a maximum particle size distribution error of 12 wt%, and a maximum particle shape distribution error of 10 wt%; their accuracy was clearly lower than for falling aggregates. However, they performed well for single-graded aggregates, and did not require a dispersion device. Our system is low-cost and easy to install. It can successfully achieve online detection of aggregate size and shape with good reliability, and it has great potential for aggregate quality assurance.

Using Analysis Increments (AI) to Estimate and Correct Systematic Errors in the Global Forecast System (GFS) Online

NASA Astrophysics Data System (ADS)

Bhargava, K.; Kalnay, E.; Carton, J.; Yang, F.

2017-12-01

Systematic forecast errors, arising from model deficiencies, form a significant portion of the total forecast error in weather prediction models like the Global Forecast System (GFS). While much effort has been expended to improve models, substantial model error remains. The aim here is to (i) estimate the model deficiencies in the GFS that lead to systematic forecast errors, (ii) implement an online correction (i.e., within the model) scheme to correct GFS following the methodology of Danforth et al. [2007] and Danforth and Kalnay [2008, GRL]. Analysis Increments represent the corrections that new observations make on, in this case, the 6-hr forecast in the analysis cycle. Model bias corrections are estimated from the time average of the analysis increments divided by 6-hr, assuming that initial model errors grow linearly and first ignoring the impact of observation bias. During 2012-2016, seasonal means of the 6-hr model bias are generally robust despite changes in model resolution and data assimilation systems, and their broad continental scales explain their insensitivity to model resolution. The daily bias dominates the sub-monthly analysis increments and consists primarily of diurnal and semidiurnal components, also requiring a low dimensional correction. Analysis increments in 2015 and 2016 are reduced over oceans, which is attributed to improvements in the specification of the SSTs. These results encourage application of online correction, as suggested by Danforth and Kalnay, for mean, seasonal and diurnal and semidiurnal model biases in GFS to reduce both systematic and random errors. As the error growth in the short-term is still linear, estimated model bias corrections can be added as a forcing term in the model tendency equation to correct online. Preliminary experiments with GFS, correcting temperature and specific humidity online show reduction in model bias in 6-hr forecast. This approach can then be used to guide and optimize the design of sub-grid scale physical parameterizations, more accurate discretization of the model dynamics, boundary conditions, radiative transfer codes, and other potential model improvements which can then replace the empirical correction scheme. The analysis increments also provide guidance in testing new physical parameterizations.

Development of a Versatile Laser-Ultrasonic System and Application to the Online Measurement for Process Control of Wall Thickness and Eccentricity of Seamless Tubes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert V. Kolarik II

2002-10-23

A system for the online, non-contact measurement of wall thickness in steel seamless mechanical tubing has been developed and demonstrated at a tubing production line at the Timken Company in Canton, Ohio. The system utilizes laser-generation of ultrasound and laser-detection of time of flight with interferometry, laser-doppler velocimetry and pyrometry, all with fiber coupling. Accuracy (<1% error) and precision (1.5%) are at targeted levels. Cost and energy savings have exceeded estimates. The system has shown good reliability in measuring over 200,000 tubes in its first six months of deployment.

Fast online generalized multiscale finite element method using constraint energy minimization

NASA Astrophysics Data System (ADS)

Chung, Eric T.; Efendiev, Yalchin; Leung, Wing Tat

2018-02-01

Local multiscale methods often construct multiscale basis functions in the offline stage without taking into account input parameters, such as source terms, boundary conditions, and so on. These basis functions are then used in the online stage with a specific input parameter to solve the global problem at a reduced computational cost. Recently, online approaches have been introduced, where multiscale basis functions are adaptively constructed in some regions to reduce the error significantly. In multiscale methods, it is desired to have only 1-2 iterations to reduce the error to a desired threshold. Using Generalized Multiscale Finite Element Framework [10], it was shown that by choosing sufficient number of offline basis functions, the error reduction can be made independent of physical parameters, such as scales and contrast. In this paper, our goal is to improve this. Using our recently proposed approach [4] and special online basis construction in oversampled regions, we show that the error reduction can be made sufficiently large by appropriately selecting oversampling regions. Our numerical results show that one can achieve a three order of magnitude error reduction, which is better than our previous methods. We also develop an adaptive algorithm and enrich in selected regions with large residuals. In our adaptive method, we show that the convergence rate can be determined by a user-defined parameter and we confirm this by numerical simulations. The analysis of the method is presented.

Analysis of Online Composite Mirror Descent Algorithm.

PubMed

Lei, Yunwen; Zhou, Ding-Xuan

2017-03-01

We study the convergence of the online composite mirror descent algorithm, which involves a mirror map to reflect the geometry of the data and a convex objective function consisting of a loss and a regularizer possibly inducing sparsity. Our error analysis provides convergence rates in terms of properties of the strongly convex differentiable mirror map and the objective function. For a class of objective functions with Hölder continuous gradients, the convergence rates of the excess (regularized) risk under polynomially decaying step sizes have the order [Formula: see text] after [Formula: see text] iterates. Our results improve the existing error analysis for the online composite mirror descent algorithm by avoiding averaging and removing boundedness assumptions, and they sharpen the existing convergence rates of the last iterate for online gradient descent without any boundedness assumptions. Our methodology mainly depends on a novel error decomposition in terms of an excess Bregman distance, refined analysis of self-bounding properties of the objective function, and the resulting one-step progress bounds.

Exploiting Task Constraints for Self-Calibrated Brain-Machine Interface Control Using Error-Related Potentials

PubMed Central

Iturrate, Iñaki; Grizou, Jonathan; Omedes, Jason; Oudeyer, Pierre-Yves; Lopes, Manuel; Montesano, Luis

2015-01-01

This paper presents a new approach for self-calibration BCI for reaching tasks using error-related potentials. The proposed method exploits task constraints to simultaneously calibrate the decoder and control the device, by using a robust likelihood function and an ad-hoc planner to cope with the large uncertainty resulting from the unknown task and decoder. The method has been evaluated in closed-loop online experiments with 8 users using a previously proposed BCI protocol for reaching tasks over a grid. The results show that it is possible to have a usable BCI control from the beginning of the experiment without any prior calibration. Furthermore, comparisons with simulations and previous results obtained using standard calibration hint that both the quality of recorded signals and the performance of the system were comparable to those obtained with a standard calibration approach. PMID:26131890

Recommendations of the DNA Commission of the International Society for Forensic Genetics (ISFG) on quality control of autosomal Short Tandem Repeat allele frequency databasing (STRidER).

PubMed

Bodner, Martin; Bastisch, Ingo; Butler, John M; Fimmers, Rolf; Gill, Peter; Gusmão, Leonor; Morling, Niels; Phillips, Christopher; Prinz, Mechthild; Schneider, Peter M; Parson, Walther

2016-09-01

The statistical evaluation of autosomal Short Tandem Repeat (STR) genotypes is based on allele frequencies. These are empirically determined from sets of randomly selected human samples, compiled into STR databases that have been established in the course of population genetic studies. There is currently no agreed procedure of performing quality control of STR allele frequency databases, and the reliability and accuracy of the data are largely based on the responsibility of the individual contributing research groups. It has been demonstrated with databases of haploid markers (EMPOP for mitochondrial mtDNA, and YHRD for Y-chromosomal loci) that centralized quality control and data curation is essential to minimize error. The concepts employed for quality control involve software-aided likelihood-of-genotype, phylogenetic, and population genetic checks that allow the researchers to compare novel data to established datasets and, thus, maintain the high quality required in forensic genetics. Here, we present STRidER (http://strider.online), a publicly available, centrally curated online allele frequency database and quality control platform for autosomal STRs. STRidER expands on the previously established ENFSI DNA WG STRbASE and applies standard concepts established for haploid and autosomal markers as well as novel tools to reduce error and increase the quality of autosomal STR data. The platform constitutes a significant improvement and innovation for the scientific community, offering autosomal STR data quality control and reliable STR genotype estimates. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Algorithms for adaptive stochastic control for a class of linear systems

NASA Technical Reports Server (NTRS)

Toda, M.; Patel, R. V.

1977-01-01

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.

Shared internal models for feedforward and feedback control.

PubMed

Wagner, Mark J; Smith, Maurice A

2008-10-15

A child often learns to ride a bicycle in the driveway, free of unforeseen obstacles. Yet when she first rides in the street, we hope that if a car suddenly pulls out in front of her, she will combine her innate goal of avoiding an accident with her learned knowledge of the bicycle, and steer away or brake. In general, when we train to perform a new motor task, our learning is most robust if it updates the rules of online error correction to reflect the rules and goals of the new task. Here we provide direct evidence that, after a new feedforward motor adaptation, motor feedback responses to unanticipated errors become precisely task appropriate, even when such errors were never experienced during training. To study this ability, we asked how, if at all, do online responses to occasional, unanticipated force pulses during reaching arm movements change after adapting to altered arm dynamics? Specifically, do they change in a task-appropriate manner? In our task, subjects learned novel velocity-dependent dynamics. However, occasional force-pulse perturbations produced unanticipated changes in velocity. Therefore, after adaptation, task-appropriate responses to unanticipated pulses should compensate corresponding changes in velocity-dependent dynamics. We found that after adaptation, pulse responses precisely compensated these changes, although they were never trained to do so. These results provide evidence for a smart feedback controller which automatically produces responses specific to the learned dynamics of the current task. To accomplish this, the neural processes underlying feedback control must (1) be capable of accurate real-time state prediction for velocity via a forward model and (2) have access to recently learned changes in internal models of limb dynamics.

Paradigm Shifts in Voluntary Force Control and Motor Unit Behaviors with the Manipulated Size of Visual Error Perception

PubMed Central

Chen, Yi-Ching; Lin, Yen-Ting; Chang, Gwo-Ching; Hwang, Ing-Shiou

2017-01-01

The detection of error information is an essential prerequisite of a feedback-based movement. This study investigated the differential behavior and neurophysiological mechanisms of a cyclic force-tracking task using error-reducing and error-enhancing feedback. The discharge patterns of a relatively large number of motor units (MUs) were assessed with custom-designed multi-channel surface electromyography following mathematical decomposition of the experimentally-measured signals. Force characteristics, force-discharge relation, and phase-locking cortical activities in the contralateral motor cortex to individual MUs were contrasted among the low (LSF), normal (NSF), and high scaling factor (HSF) conditions, in which the sizes of online execution errors were displayed with various amplification ratios. Along with a spectral shift of the force output toward a lower band, force output with a more phase-lead became less irregular, and tracking accuracy was worse in the LSF condition than in the HSF condition. The coherent discharge of high phasic (HP) MUs with the target signal was greater, and inter-spike intervals were larger, in the LSF condition than in the HSF condition. Force-tracking in the LSF condition manifested with stronger phase-locked EEG activity in the contralateral motor cortex to discharge of the (HP) MUs (LSF > NSF, HSF). The coherent discharge of the (HP) MUs during the cyclic force-tracking predominated the force-discharge relation, which increased inversely to the error scaling factor. In conclusion, the size of visualized error gates motor unit discharge, force-discharge relation, and the relative influences of the feedback and feedforward processes on force control. A smaller visualized error size favors voluntary force control using a feedforward process, in relation to a selective central modulation that enhance the coherent discharge of (HP) MUs. PMID:28348530

Paradigm Shifts in Voluntary Force Control and Motor Unit Behaviors with the Manipulated Size of Visual Error Perception.

PubMed

Chen, Yi-Ching; Lin, Yen-Ting; Chang, Gwo-Ching; Hwang, Ing-Shiou

2017-01-01

The detection of error information is an essential prerequisite of a feedback-based movement. This study investigated the differential behavior and neurophysiological mechanisms of a cyclic force-tracking task using error-reducing and error-enhancing feedback. The discharge patterns of a relatively large number of motor units (MUs) were assessed with custom-designed multi-channel surface electromyography following mathematical decomposition of the experimentally-measured signals. Force characteristics, force-discharge relation, and phase-locking cortical activities in the contralateral motor cortex to individual MUs were contrasted among the low (LSF), normal (NSF), and high scaling factor (HSF) conditions, in which the sizes of online execution errors were displayed with various amplification ratios. Along with a spectral shift of the force output toward a lower band, force output with a more phase-lead became less irregular, and tracking accuracy was worse in the LSF condition than in the HSF condition. The coherent discharge of high phasic (HP) MUs with the target signal was greater, and inter-spike intervals were larger, in the LSF condition than in the HSF condition. Force-tracking in the LSF condition manifested with stronger phase-locked EEG activity in the contralateral motor cortex to discharge of the (HP) MUs (LSF > NSF, HSF). The coherent discharge of the (HP) MUs during the cyclic force-tracking predominated the force-discharge relation, which increased inversely to the error scaling factor. In conclusion, the size of visualized error gates motor unit discharge, force-discharge relation, and the relative influences of the feedback and feedforward processes on force control. A smaller visualized error size favors voluntary force control using a feedforward process, in relation to a selective central modulation that enhance the coherent discharge of (HP) MUs.

Magneto-optical tracking of flexible laparoscopic ultrasound: model-based online detection and correction of magnetic tracking errors.

PubMed

Feuerstein, Marco; Reichl, Tobias; Vogel, Jakob; Traub, Joerg; Navab, Nassir

2009-06-01

Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.

Application of Energy Function as a Measure of Error in the Numerical Solution for Online Transient Stability Assessment

NASA Astrophysics Data System (ADS)

Sarojkumar, K.; Krishna, S.

2016-08-01

Online dynamic security assessment (DSA) is a computationally intensive task. In order to reduce the amount of computation, screening of contingencies is performed. Screening involves analyzing the contingencies with the system described by a simpler model so that computation requirement is reduced. Screening identifies those contingencies which are sure to not cause instability and hence can be eliminated from further scrutiny. The numerical method and the step size used for screening should be chosen with a compromise between speed and accuracy. This paper proposes use of energy function as a measure of error in the numerical solution used for screening contingencies. The proposed measure of error can be used to determine the most accurate numerical method satisfying the time constraint of online DSA. Case studies on 17 generator system are reported.

Prevention of prescription errors by computerized, on-line, individual patient related surveillance of drug order entry.

PubMed

Oliven, A; Zalman, D; Shilankov, Y; Yeshurun, D; Odeh, M

2002-01-01

Computerized prescription of drugs is expected to reduce the number of many preventable drug ordering errors. In the present study we evaluated the usefullness of a computerized drug order entry (CDOE) system in reducing prescription errors. A department of internal medicine using a comprehensive CDOE, which included also patient-related drug-laboratory, drug-disease and drug-allergy on-line surveillance was compared to a similar department in which drug orders were handwritten. CDOE reduced prescription errors to 25-35%. The causes of errors remained similar, and most errors, on both departments, were associated with abnormal renal function and electrolyte balance. Residual errors remaining on the CDOE-using department were due to handwriting on the typed order, failure to feed patients' diseases, and system failures. The use of CDOE was associated with a significant reduction in mean hospital stay and in the number of changes performed in the prescription. The findings of this study both quantity the impact of comprehensive CDOE on prescription errors and delineate the causes for remaining errors.

Testing the Recognition and Perception of Errors in Context

ERIC Educational Resources Information Center

Brandenburg, Laura C.

2015-01-01

This study tests the recognition of errors in context and whether the presence of errors affects the reader's perception of the writer's ethos. In an experimental, posttest only design, participants were randomly assigned a memo to read in an online survey: one version with errors and one version without. Of the six intentional errors in version…

Distributed adaptive neural network control for a class of heterogeneous nonlinear multi-agent systems subject to actuation failures

NASA Astrophysics Data System (ADS)

Cui, Bing; Zhao, Chunhui; Ma, Tiedong; Feng, Chi

2017-02-01

In this paper, the cooperative adaptive consensus tracking problem for heterogeneous nonlinear multi-agent systems on directed graph is addressed. Each follower is modelled as a general nonlinear system with the unknown and nonidentical nonlinear dynamics, disturbances and actuator failures. Cooperative fault tolerant neural network tracking controllers with online adaptive learning features are proposed to guarantee that all agents synchronise to the trajectory of one leader with bounded adjustable synchronisation errors. With the help of linear quadratic regulator-based optimal design, a graph-dependent Lyapunov proof provides error bounds that depend on the graph topology, one virtual matrix and some design parameters. Of particular interest is that if the control gain is selected appropriately, the proposed control scheme can be implemented in a unified framework no matter whether there are faults or not. Furthermore, the fault detection and isolation are not needed to implement. Finally, a simulation is given to verify the effectiveness of the proposed method.

Correction to: Apatinib: A Review in Advanced Gastric Cancer and Other Advanced Cancers.

PubMed

Scott, Lesley J

2018-05-04

An Online First version of this article was made available online at http://link.springer.com/journal/40265/onlineFirst/page/1 on 16 April 2018. Errors were subsequently identified in the article, and the following corrections should be noted.

Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas

NASA Astrophysics Data System (ADS)

Chestek, Cynthia A.; Gilja, Vikash; Blabe, Christine H.; Foster, Brett L.; Shenoy, Krishna V.; Parvizi, Josef; Henderson, Jaimie M.

2013-04-01

Objective. Brain-machine interface systems translate recorded neural signals into command signals for assistive technology. In individuals with upper limb amputation or cervical spinal cord injury, the restoration of a useful hand grasp could significantly improve daily function. We sought to determine if electrocorticographic (ECoG) signals contain sufficient information to select among multiple hand postures for a prosthetic hand, orthotic, or functional electrical stimulation system.Approach. We recorded ECoG signals from subdural macro- and microelectrodes implanted in motor areas of three participants who were undergoing inpatient monitoring for diagnosis and treatment of intractable epilepsy. Participants performed five distinct isometric hand postures, as well as four distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with two participants. Main results. Classification rates were 68%, 84% and 81% for correct identification of 5 isometric hand postures offline. Using 3 potential controls for removing sensory signals, error rates were approximately doubled on average (2.1×). A similar increase in errors (2.6×) was noted when the participant was asked to make simultaneous wrist movements along with the hand postures. In online experiments, fist versus rest was successfully classified on 97% of trials; the classification output drove a prosthetic hand. Online classification performance for a larger number of hand postures remained above chance, but substantially below offline performance. In addition, the long integration windows used would preclude the use of decoded signals for control of a BCI system. Significance. These results suggest that ECoG is a plausible source of command signals for prosthetic grasp selection. Overall, avenues remain for improvement through better electrode designs and placement, better participant training, and characterization of non-stationarities such that ECoG could be a viable signal source for grasp control for amputees or individuals with paralysis.

Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

2017-12-01

In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

It Pays to Go Off-Track: Practicing with Error-Augmenting Haptic Feedback Facilitates Learning of a Curve-Tracing Task

PubMed Central

Williams, Camille K.; Tremblay, Luc; Carnahan, Heather

2016-01-01

Researchers in the domain of haptic training are now entering the long-standing debate regarding whether or not it is best to learn a skill by experiencing errors. Haptic training paradigms provide fertile ground for exploring how various theories about feedback, errors and physical guidance intersect during motor learning. Our objective was to determine how error minimizing, error augmenting and no haptic feedback while learning a self-paced curve-tracing task impact performance on delayed (1 day) retention and transfer tests, which indicate learning. We assessed performance using movement time and tracing error to calculate a measure of overall performance – the speed accuracy cost function. Our results showed that despite exhibiting the worst performance during skill acquisition, the error augmentation group had significantly better accuracy (but not overall performance) than the error minimization group on delayed retention and transfer tests. The control group’s performance fell between that of the two experimental groups but was not significantly different from either on the delayed retention test. We propose that the nature of the task (requiring online feedback to guide performance) coupled with the error augmentation group’s frequent off-target experience and rich experience of error-correction promoted information processing related to error-detection and error-correction that are essential for motor learning. PMID:28082937

The Neural-fuzzy Thermal Error Compensation Controller on CNC Machining Center

NASA Astrophysics Data System (ADS)

Tseng, Pai-Chung; Chen, Shen-Len

The geometric errors and structural thermal deformation are factors that influence the machining accuracy of Computer Numerical Control (CNC) machining center. Therefore, researchers pay attention to thermal error compensation technologies on CNC machine tools. Some real-time error compensation techniques have been successfully demonstrated in both laboratories and industrial sites. The compensation results still need to be enhanced. In this research, the neural-fuzzy theory has been conducted to derive a thermal prediction model. An IC-type thermometer has been used to detect the heat sources temperature variation. The thermal drifts are online measured by a touch-triggered probe with a standard bar. A thermal prediction model is then derived by neural-fuzzy theory based on the temperature variation and the thermal drifts. A Graphic User Interface (GUI) system is also built to conduct the user friendly operation interface with Insprise C++ Builder. The experimental results show that the thermal prediction model developed by neural-fuzzy theory methodology can improve machining accuracy from 80µm to 3µm. Comparison with the multi-variable linear regression analysis the compensation accuracy is increased from ±10µm to ±3µm.

Real-Time Decentralized Neural Control via Backstepping for a Robotic Arm Powered by Industrial Servomotors.

PubMed

Vazquez, Luis A; Jurado, Francisco; Castaneda, Carlos E; Santibanez, Victor

2018-02-01

This paper presents a continuous-time decentralized neural control scheme for trajectory tracking of a two degrees of freedom direct drive vertical robotic arm. A decentralized recurrent high-order neural network (RHONN) structure is proposed to identify online, in a series-parallel configuration and using the filtered error learning law, the dynamics of the plant. Based on the RHONN subsystems, a local neural controller is derived via backstepping approach. The effectiveness of the decentralized neural controller is validated on a robotic arm platform, of our own design and unknown parameters, which uses industrial servomotors to drive the joints.

Online and offline effects of cerebellar transcranial direct current stimulation on motor learning in healthy older adults: a randomized double-blind sham-controlled study.

PubMed

Samaei, Afshin; Ehsani, Fatemeh; Zoghi, Maryam; Hafez Yosephi, Mohaddese; Jaberzadeh, Shapour

2017-05-01

The aim of this randomized double blinded sham-controlled study was to determine the effect of cerebellar anodal transcranial direct current stimulation (a-tDCS) on online and offline motor learning in healthy older individuals. Thirty participants were randomly assigned in experimental (n = 15) or sham tDCS (n = 15) groups. Participants in experimental group received 2 mA cerebellar a-tDCS for 20 min. However, the tDCS was turned off after 30 seconds in sham group. Response time (RT) and error rate (ER) in serial RT test were assessed before, during 35 minutes and 48 h after the intervention. Reduction of RT and ER following the intervention session was considered as short-term (35 min post intervention) and long-term offline learning (48 h post intervention), respectively. Online RT and ER reduction were similar in both groups (P > 0.05). RT was significantly reduced 48 hours post intervention in cerebellar a-tDCS group (P = 0.03). Moreover, RT was significantly increased after 35 minutes and 48 hours in sham tDCS group (P = 0.03, P = 0.007), which indicates a lack of short-term and long-term offline learning in older adults. A-tDCS on cerebellar region produced more short-term and long-term offline improvement in RT (P = 0.014, P = 0.01) compared to sham tDCS. In addition, online, short-term and long-term (48 h) offline error reduced in cerebellar a-tDCS as compared to sham-control group, although this reduction was not significant (P > 0.05). A deficit suggests that a direct comparison to a younger group was made. The findings suggested that cerebellar a-tDCS might be useful for improvement of offline motor learning in older individuals. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Warning: This keyboard will deconstruct--the role of the keyboard in skilled typewriting.

PubMed

Crump, Matthew J C; Logan, Gordon D

2010-06-01

Skilled actions are commonly assumed to be controlled by precise internal schemas or cognitive maps. We challenge these ideas in the context of skilled typing, where prominent theories assume that typing is controlled by a well-learned cognitive map that plans finger movements without feedback. In two experiments, we demonstrate that online physical interaction with the keyboard critically mediates typing skill. Typists performed single-word and paragraph typing tasks on a regular keyboard, a laser-projection keyboard, and two deconstructed keyboards, made by removing successive layers of a regular keyboard. Averaged over the laser and deconstructed keyboards, response times for the first keystroke increased by 37%, the interval between keystrokes increased by 120%, and error rate increased by 177%, relative to those of the regular keyboard. A schema view predicts no influence of external motor feedback, because actions could be planned internally with high precision. We argue that the expert knowledge mediating action control emerges during online interaction with the physical environment.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Intelligent voltage control strategy for three-phase UPS inverters with output LC filter

NASA Astrophysics Data System (ADS)

Jung, J. W.; Leu, V. Q.; Dang, D. Q.; Do, T. D.; Mwasilu, F.; Choi, H. H.

2015-08-01

This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.

Single Crystal Diffractometry

NASA Astrophysics Data System (ADS)

Arndt, U. W.; Willis, B. T. M.

2009-06-01

Preface; Acknowledgements; Part I. Introduction; Part II. Diffraction Geometry; Part III. The Design of Diffractometers; Part IV. Detectors; Part V. Electronic Circuits; Part VI. The Production of the Primary Beam (X-rays); Part VII. The Production of the Primary Beam (Neutrons); Part VIII. The Background; Part IX. Systematic Errors in Measuring Relative Integrated Intensities; Part X. Procedure for Measuring Integrated Intensities; Part XI. Derivation and Accuracy of Structure Factors; Part XII. Computer Programs and On-line Control; Appendix; References; Index.

Compensation of significant parametric uncertainties using sliding mode online learning

NASA Astrophysics Data System (ADS)

Schnetter, Philipp; Kruger, Thomas

An augmented nonlinear inverse dynamics (NID) flight control strategy using sliding mode online learning for a small unmanned aircraft system (UAS) is presented. Because parameter identification for this class of aircraft often is not valid throughout the complete flight envelope, aerodynamic parameters used for model based control strategies may show significant deviations. For the concept of feedback linearization this leads to inversion errors that in combination with the distinctive susceptibility of small UAS towards atmospheric turbulence pose a demanding control task for these systems. In this work an adaptive flight control strategy using feedforward neural networks for counteracting such nonlinear effects is augmented with the concept of sliding mode control (SMC). SMC-learning is derived from variable structure theory. It considers a neural network and its training as a control problem. It is shown that by the dynamic calculation of the learning rates, stability can be guaranteed and thus increase the robustness against external disturbances and system failures. With the resulting higher speed of convergence a wide range of simultaneously occurring disturbances can be compensated. The SMC-based flight controller is tested and compared to the standard gradient descent (GD) backpropagation algorithm under the influence of significant model uncertainties and system failures.

Colour-induced relationship between affect and reaching kinematics during a goal-directed aiming task.

PubMed

Williams, Camille K; Grierson, Lawrence E M; Carnahan, Heather

2011-08-01

A link between affect and action has been supported by the discovery that threat information is prioritized through an action-centred pathway--the dorsal visual stream. Magnocellular afferents, which originate from the retina and project to dorsal stream structures, are suppressed by exposure to diffuse red light, which diminishes humans' perception of threat-based images. In order to explore the role of colour in the relationship between affect and action, participants donned different pairs of coloured glasses (red, yellow, green, blue and clear) and completed Positive and Negative Affect Scale questionnaires as well as a series of target-directed aiming movements. Analyses of affect scores revealed a significant main effect for affect valence and a significant interaction between colour and valence: perceived positive affect was significantly smaller for the red condition. Kinematic analyses of variable error in the primary movement direction and Pearson correlation analyses between the displacements travelled prior to and following peak velocity indicated reduced accuracy and application of online control processes while wearing red glasses. Variable error of aiming was also positively and significantly correlated with negative affect scores under the red condition. These results suggest that only red light modulates the affect-action link by suppressing magnocellular activity, which disrupts visual processing for movement control. Furthermore, previous research examining the effect of the colour red on psychomotor tasks and perceptual acceleration of threat-based imagery suggest that stimulus-driven motor performance tasks requiring online control may be particularly susceptible to this effect.

Online beam energy measurement of Beijing electron positron collider II linear accelerator

NASA Astrophysics Data System (ADS)

Wang, S.; Iqbal, M.; Liu, R.; Chi, Y.

2016-02-01

This paper describes online beam energy measurement of Beijing Electron Positron Collider upgraded version II linear accelerator (linac) adequately. It presents the calculation formula, gives the error analysis in detail, discusses the realization in practice, and makes some verification. The method mentioned here measures the beam energy by acquiring the horizontal beam position with three beam position monitors (BPMs), which eliminates the effect of orbit fluctuation, and is much better than the one using the single BPM. The error analysis indicates that this online measurement has further potential usage such as a part of beam energy feedback system. The reliability of this method is also discussed and demonstrated in this paper.

Online beam energy measurement of Beijing electron positron collider II linear accelerator.

PubMed

Wang, S; Iqbal, M; Liu, R; Chi, Y

2016-02-01

This paper describes online beam energy measurement of Beijing Electron Positron Collider upgraded version II linear accelerator (linac) adequately. It presents the calculation formula, gives the error analysis in detail, discusses the realization in practice, and makes some verification. The method mentioned here measures the beam energy by acquiring the horizontal beam position with three beam position monitors (BPMs), which eliminates the effect of orbit fluctuation, and is much better than the one using the single BPM. The error analysis indicates that this online measurement has further potential usage such as a part of beam energy feedback system. The reliability of this method is also discussed and demonstrated in this paper.

Robust reinforcement learning.

PubMed

Morimoto, Jun; Doya, Kenji

2005-02-01

This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both offline learning using simulations and for online action planning. However, the difference between the model and the real environment can lead to unpredictable, and often unwanted, results. Based on the theory of H(infinity) control, we consider a differential game in which a "disturbing" agent tries to make the worst possible disturbance while a "control" agent tries to make the best control input. The problem is formulated as finding a min-max solution of a value function that takes into account the amount of the reward and the norm of the disturbance. We derive online learning algorithms for estimating the value function and for calculating the worst disturbance and the best control in reference to the value function. We tested the paradigm, which we call robust reinforcement learning (RRL), on the control task of an inverted pendulum. In the linear domain, the policy and the value function learned by online algorithms coincided with those derived analytically by the linear H(infinity) control theory. For a fully nonlinear swing-up task, RRL achieved robust performance with changes in the pendulum weight and friction, while a standard reinforcement learning algorithm could not deal with these changes. We also applied RRL to the cart-pole swing-up task, and a robust swing-up policy was acquired.

On-line diagnosis of sequential systems

NASA Technical Reports Server (NTRS)

Sundstrom, R. J.

1973-01-01

A model for on-line diagnosis was investigated for discrete-time systems, and resettable sequential systems. Generalized notions of a realization are discussed along with fault tolerance and errors. Further investigation into the theory of on-line diagnosis is recommended for three levels: binary state-assigned level, logical circuit level, and the subsystem-network level.

Author Correction to: Pooled Analyses of Phase III Studies of ADS-5102 (Amantadine) Extended-Release Capsules for Dyskinesia in Parkinson's Disease.

PubMed

Elmer, Lawrence W; Juncos, Jorge L; Singer, Carlos; Truong, Daniel D; Criswell, Susan R; Parashos, Sotirios; Felt, Larissa; Johnson, Reed; Patni, Rajiv

2018-04-01

An Online First version of this article was made available online at http://link.springer.com/journal/40263/onlineFirst/page/1 on 12 March 2018. An error was subsequently identified in the article, and the following correction should be noted.

Continuous processing and the applications of online tools in pharmaceutical product manufacture: developments and examples.

PubMed

Ooi, Shing Ming; Sarkar, Srimanta; van Varenbergh, Griet; Schoeters, Kris; Heng, Paul Wan Sia

2013-04-01

Continuous processing and production in pharmaceutical manufacturing has received increased attention in recent years mainly due to the industries' pressing needs for more efficient, cost-effective processes and production, as well as regulatory facilitation. To achieve optimum product quality, the traditional trial-and-error method for the optimization of different process and formulation parameters is expensive and time consuming. Real-time evaluation and the control of product quality using an online process analyzer in continuous processing can provide high-quality production with very high-throughput at low unit cost. This review focuses on continuous processing and the application of different real-time monitoring tools used in the pharmaceutical industry for continuous processing from powder to tablets.

Electro-Optical Inspection For Tolerance Control As An Integral Part Of A Flexible Machining Cell

NASA Astrophysics Data System (ADS)

Renaud, Blaise

1986-11-01

Institut CERAC has been involved in optical metrology and 3-dimensional surface control for the last couple of years. Among the industrial applications considered is the on-line shape evaluation of machined parts within the manufacturing cell. The specific objective is to measure the machining errors and to compare them with the tolerances set by designers. An electro-optical sensing technique has been developed which relies on a projection Moire contouring optical method. A prototype inspection system has been designed, making use of video detection and computer image processing. Moire interferograms are interpreted, and the metrological information automatically retrieved. A structured database can be generated for subsequent data analysis and for real-time closed-loop corrective actions. A real-time kernel embedded into a synchronisation network (Petri-net) for the control of concurrent processes in the Electra-Optical Inspection (E0I) station was realised and implemented in a MODULA-2 program DIN01. The prototype system for on-line automatic tolerance control taking place within a flexible machining cell is described in this paper, together with the fast-prototype synchronisation program.

Real-time orbit estimation for ATS-6 from redundant attitude sensors

NASA Technical Reports Server (NTRS)

Englar, T. S., Jr.

1975-01-01

A program installed in the ATSOCC on-line computer operates with attitude sensor data to produce a smoothed real-time orbit estimate. This estimate is obtained from a Kalman filter which enables the estimate to be maintained in the absence of T/M data. The results are described of analytical and numerical investigations into the sensitivity of Control Center output to the position errors resulting from the real-time estimation. The results of the numerical investigation, which used several segments of ATS-6 data gathered during the Sensor Data Acquisition run on August 19, 1974, show that the implemented system can achieve absolute position determination with an error of about 100 km, implying pointing errors of less than 0.2 deg in latitude and longitude. This compares very favorably with ATS-6 specifications of approximately 0.5 deg in latitude-longitude.

Mark-Up-Based Writing Error Analysis Model in an On-Line Classroom.

ERIC Educational Resources Information Center

Feng, Cheng; Yano, Yoneo; Ogata, Hiroaki

2000-01-01

Describes a new component called "Writing Error Analysis Model" (WEAM) in the CoCoA system for teaching writing composition in Japanese as a foreign language. The Weam can be used for analyzing learners' morphological errors and selecting appropriate compositions for learners' revising exercises. (Author/VWL)

Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

NASA Astrophysics Data System (ADS)

Tiwari, Shivendra N.; Padhi, Radhakant

2018-01-01

Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

The Seven Deadly Sins of Online Microcomputing.

ERIC Educational Resources Information Center

King, Alan

1989-01-01

Offers suggestions for avoiding common errors in online microcomputer use. Areas discussed include learning the basics; hardware protection; backup options; hard disk organization; software selection; file security; and the use of dedicated communications lines. (CLB)

Development of online use of theory of mind during adolescence: An eye-tracking study.

PubMed

Symeonidou, Irene; Dumontheil, Iroise; Chow, Wing-Yee; Breheny, Richard

2016-09-01

We investigated the development of theory of mind use through eye-tracking in children (9-13years old, n=14), adolescents (14-17.9years old, n=28), and adults (19-29years old, n=23). Participants performed a computerized task in which a director instructed them to move objects placed on a set of shelves. Some of the objects were blocked off from the director's point of view; therefore, participants needed to take into consideration the director's ignorance of these objects when following the director's instructions. In a control condition, participants performed the same task in the absence of the director and were told that the instructions would refer only to items in slots without a back panel, controlling for general cognitive demands of the task. Participants also performed two inhibitory control tasks. We replicated previous findings, namely that in the director-present condition, but not in the control condition, children and adolescents made more errors than adults, suggesting that theory of mind use improves between adolescence and adulthood. Inhibitory control partly accounted for errors on the director task, indicating that it is a factor of developmental change in perspective taking. Eye-tracking data revealed early eye gaze differences between trials where the director's perspective was taken into account and those where it was not. Once differences in accuracy rates were considered, all age groups engaged in the same kind of online processing during perspective taking but differed in how often they engaged in perspective taking. When perspective is correctly taken, all age groups' gaze data point to an early influence of perspective information. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Simultaneous Online Measurement of H2O and CO2 in the Humid CO2 Adsorption/Desorption Process.

PubMed

Yu, Qingni; Ye, Sha; Zhu, Jingke; Lei, Lecheng; Yang, Bin

2015-01-01

A dew point meter (DP) and an infrared (IR) CO2 analyzer were assembled in a humid CO2 adsorption/desorption system in series for simultaneous online measurements of H2O and CO2, respectively. The humidifier, by using surface-flushing on a saturated brine solution was self-made for the generation of humid air flow. It was found that by this method it became relatively easy to obtain a low H2O content in air flow and that its fluctuation could be reduced compared to the bubbling method. Water calibration for the DP-IR detector is necessary to be conducted for minimizing the measurement error of H2O. It demonstrated that the relative error (RA) for simultaneous online measurements H2O and CO2 in the desorption process is lower than 0.1%. The high RA in the adsorption of H2O is attributed to H2O adsorption on the transfer pipe and amplification of the measurement error. The high accuracy of simultaneous online measurements of H2O and CO2 is promising for investigating their co-adsorption/desorption behaviors, especially for direct CO2 capture from ambient air.

Sensorless Load Torque Estimation and Passivity Based Control of Buck Converter Fed DC Motor

PubMed Central

Kumar, S. Ganesh; Thilagar, S. Hosimin

2015-01-01

Passivity based control of DC motor in sensorless configuration is proposed in this paper. Exact tracking error dynamics passive output feedback control is used for stabilizing the speed of Buck converter fed DC motor under various load torques such as constant type, fan type, propeller type, and unknown load torques. Under load conditions, sensorless online algebraic approach is proposed, and it is compared with sensorless reduced order observer approach. The former produces better response in estimating the load torque. Sensitivity analysis is also performed to select the appropriate control variables. Simulation and experimental results fully confirm the superiority of the proposed approach suggested in this paper. PMID:25893208

Neural networks for tracking of unknown SISO discrete-time nonlinear dynamic systems.

PubMed

Aftab, Muhammad Saleheen; Shafiq, Muhammad

2015-11-01

This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator parameters. The controller and estimator error convergence and closed-loop system stability analysis is performed by Lyapunov stability theory. Moreover, two simulation examples and one real-time experiment are investigated as case studies. The achieved results successfully validate the controller performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Online monitoring of P(3HB) produced from used cooking oil with near-infrared spectroscopy.

PubMed

Cruz, Madalena V; Sarraguça, Mafalda Cruz; Freitas, Filomena; Lopes, João Almeida; Reis, Maria A M

2015-01-20

Online monitoring process for the production of polyhydroxyalkanoates (PHA), using cooking oil (UCO) as the sole carbon source and Cupriavidus necator, was developed. A batch reactor was operated and hydroxybutyrate homopolymer was obtained. The biomass reached a maximum concentration of 11.6±1.7gL(-1) with a polymer content of 63±10.7% (w/w). The yield of product on substrate was 0.77±0.04gg(-1). Near-infrared (NIR) spectroscopy was used for online monitoring of the fermentation, using a transflectance probe. Partial least squares regression was applied to relate NIR spectra with biomass, UCO and PHA concentrations in the broth. The NIR predictions were compared with values obtained by offline reference methods. Prediction errors to these parameters were 1.18, 2.37 and 1.58gL(-1) for biomass, UCO and PHA, respectively, which indicate the suitability of the NIR spectroscopy method for online monitoring and as a method to assist bioreactor control. Copyright © 2014 Elsevier B.V. All rights reserved.

On-line estimation of error covariance parameters for atmospheric data assimilation

NASA Technical Reports Server (NTRS)

Dee, Dick P.

1995-01-01

A simple scheme is presented for on-line estimation of covariance parameters in statistical data assimilation systems. The scheme is based on a maximum-likelihood approach in which estimates are produced on the basis of a single batch of simultaneous observations. Simple-sample covariance estimation is reasonable as long as the number of available observations exceeds the number of tunable parameters by two or three orders of magnitude. Not much is known at present about model error associated with actual forecast systems. Our scheme can be used to estimate some important statistical model error parameters such as regionally averaged variances or characteristic correlation length scales. The advantage of the single-sample approach is that it does not rely on any assumptions about the temporal behavior of the covariance parameters: time-dependent parameter estimates can be continuously adjusted on the basis of current observations. This is of practical importance since it is likely to be the case that both model error and observation error strongly depend on the actual state of the atmosphere. The single-sample estimation scheme can be incorporated into any four-dimensional statistical data assimilation system that involves explicit calculation of forecast error covariances, including optimal interpolation (OI) and the simplified Kalman filter (SKF). The computational cost of the scheme is high but not prohibitive; on-line estimation of one or two covariance parameters in each analysis box of an operational bozed-OI system is currently feasible. A number of numerical experiments performed with an adaptive SKF and an adaptive version of OI, using a linear two-dimensional shallow-water model and artificially generated model error are described. The performance of the nonadaptive versions of these methods turns out to depend rather strongly on correct specification of model error parameters. These parameters are estimated under a variety of conditions, including uniformly distributed model error and time-dependent model error statistics.

Predictive and Feedback Performance Errors are Signaled in the Simple Spike Discharge of Individual Purkinje Cells

PubMed Central

Popa, Laurentiu S.; Hewitt, Angela L.; Ebner, Timothy J.

2012-01-01

The cerebellum has been implicated in processing motor errors required for online control of movement and motor learning. The dominant view is that Purkinje cell complex spike discharge signals motor errors. This study investigated whether errors are encoded in the simple spike discharge of Purkinje cells in monkeys trained to manually track a pseudo-randomly moving target. Four task error signals were evaluated based on cursor movement relative to target movement. Linear regression analyses based on firing residuals ensured that the modulation with a specific error parameter was independent of the other error parameters and kinematics. The results demonstrate that simple spike firing in lobules IV–VI is significantly correlated with position, distance and directional errors. Independent of the error signals, the same Purkinje cells encode kinematics. The strongest error modulation occurs at feedback timing. However, in 72% of cells at least one of the R2 temporal profiles resulting from regressing firing with individual errors exhibit two peak R2 values. For these bimodal profiles, the first peak is at a negative τ (lead) and a second peak at a positive τ (lag), implying that Purkinje cells encode both prediction and feedback about an error. For the majority of the bimodal profiles, the signs of the regression coefficients or preferred directions reverse at the times of the peaks. The sign reversal results in opposing simple spike modulation for the predictive and feedback components. Dual error representations may provide the signals needed to generate sensory prediction errors used to update a forward internal model. PMID:23115173

A service evaluation of on-line image-guided radiotherapy to lower extremity sarcoma: Investigating the workload implications of a 3 mm action level for image assessment and correction prior to delivery.

PubMed

Taylor, C; Parker, J; Stratford, J; Warren, M

2018-05-01

Although all systematic and random positional setup errors can be corrected for in entirety during on-line image-guided radiotherapy, the use of a specified action level, below which no correction occurs, is also an option. The following service evaluation aimed to investigate the use of this 3 mm action level for on-line image assessment and correction (online, systematic set-up error and weekly evaluation) for lower extremity sarcoma, and understand the impact on imaging frequency and patient positioning error within one cancer centre. All patients were immobilised using a thermoplastic shell attached to a plastic base and an individual moulded footrest. A retrospective analysis of 30 patients was performed. Patient setup and correctional data derived from cone beam CT analysis was retrieved. The timing, frequency and magnitude of corrections were evaluated. The population systematic and random error was derived. 20% of patients had no systematic corrections over the duration of treatment, and 47% had one. The maximum number of systematic corrections per course of radiotherapy was 4, which occurred for 2 patients. 34% of episodes occurred within the first 5 fractions. All patients had at least one observed translational error during their treatment greater than 0.3 cm, and 80% of patients had at least one observed translational error during their treatment greater than 0.5 cm. The population systematic error was 0.14 cm, 0.10 cm, 0.14 cm and random error was 0.27 cm, 0.22 cm, 0.23 cm in the lateral, caudocranial and anteroposterial directions. The required Planning Target Volume margin for the study population was 0.55 cm, 0.41 cm and 0.50 cm in the lateral, caudocranial and anteroposterial directions. The 3 mm action level for image assessment and correction prior to delivery reduced the imaging burden and focussed intervention on patients that exhibited greater positional variability. This strategy could be an efficient deployment of departmental resources if full daily correction of positional setup error is not possible. Copyright © 2017. Published by Elsevier Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Z.; Pike, R.W.; Hertwig, T.A.

An effective approach for source reduction in chemical plants has been demonstrated using on-line optimization with flowsheeting (ASPEN PLUS) for process optimization and parameter estimation and the Tjao-Biegler algorithm implemented in a mathematical programming language (GAMS/MINOS) for data reconciliation and gross error detection. Results for a Monsanto sulfuric acid plant with a Bailey distributed control system showed a 25% reduction in the sulfur dioxide emissions and a 17% improvement in the profit over the current operating conditions. Details of the methods used are described.

Detection of Error Related Neuronal Responses Recorded by Electrocorticography in Humans during Continuous Movements

PubMed Central

Milekovic, Tomislav; Ball, Tonio; Schulze-Bonhage, Andreas; Aertsen, Ad; Mehring, Carsten

2013-01-01

Background Brain-machine interfaces (BMIs) can translate the neuronal activity underlying a user’s movement intention into movements of an artificial effector. In spite of continuous improvements, errors in movement decoding are still a major problem of current BMI systems. If the difference between the decoded and intended movements becomes noticeable, it may lead to an execution error. Outcome errors, where subjects fail to reach a certain movement goal, are also present during online BMI operation. Detecting such errors can be beneficial for BMI operation: (i) errors can be corrected online after being detected and (ii) adaptive BMI decoding algorithm can be updated to make fewer errors in the future. Methodology/Principal Findings Here, we show that error events can be detected from human electrocorticography (ECoG) during a continuous task with high precision, given a temporal tolerance of 300–400 milliseconds. We quantified the error detection accuracy and showed that, using only a small subset of 2×2 ECoG electrodes, 82% of detection information for outcome error and 74% of detection information for execution error available from all ECoG electrodes could be retained. Conclusions/Significance The error detection method presented here could be used to correct errors made during BMI operation or to adapt a BMI algorithm to make fewer errors in the future. Furthermore, our results indicate that smaller ECoG implant could be used for error detection. Reducing the size of an ECoG electrode implant used for BMI decoding and error detection could significantly reduce the medical risk of implantation. PMID:23383315

Quaternion error-based optimal control applied to pinpoint landing

NASA Astrophysics Data System (ADS)

Ghiglino, Pablo

Accurate control techniques for pinpoint planetary landing - i.e., the goal of achieving landing errors in the order of 100m for unmanned missions - is a complex problem that have been tackled in different ways in the available literature. Among other challenges, this kind of control is also affected by the well known trade-off in UAV control that for complex underlying models the control is sub-optimal, while optimal control is applied to simplifed models. The goal of this research has been the development new control algorithms that would be able to tackle these challenges and the result are two novel optimal control algorithms namely: OQTAL and HEX2OQTAL. These controllers share three key properties that are thoroughly proven and shown in this thesis; stability, accuracy and adaptability. Stability is rigorously demonstrated for both controllers. Accuracy is shown in results of comparing these novel controllers with other industry standard algorithms in several different scenarios: there is a gain in accuracy of at least 15% for each controller, and in many cases much more than that. A new tuning algorithm based on swarm heuristics optimisation was developed as well as part of this research in order to tune in an online manner the standard Proportional-Integral-Derivative (PID) controllers used for benchmarking. Finally, adaptability of these controllers can be seen as a combination of four elements: mathematical model extensibility, cost matrices tuning, reduced computation time required and finally no prior knowledge of the navigation or guidance strategies needed. Further simulations in real planetary landing trajectories has shown that these controllers have the capacity of achieving landing errors in the order of pinpoint landing requirements, making them not only very precise UAV controllers, but also potential candidates for pinpoint landing unmanned missions.

Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine

2002-01-01

The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.

Fuzzy Control of Robotic Arm

NASA Astrophysics Data System (ADS)

Lin, Kyaw Kyaw; Soe, Aung Kyaw; Thu, Theint Theint

2008-10-01

This research work investigates a Self-Tuning Proportional Derivative (PD) type Fuzzy Logic Controller (STPDFLC) for a two link robot system. The proposed scheme adjusts on-line the output Scaling Factor (SF) by fuzzy rules according to the current trend of the robot. The rule base for tuning the output scaling factor is defined on the error (e) and change in error (de). The scheme is also based on the fact that the controller always tries to manipulate the process input. The rules are in the familiar if-then format. All membership functions for controller inputs (e and de) and controller output (UN) are defined on the common interval [-1,1]; whereas the membership functions for the gain updating factor (α) is defined on [0,1]. There are various methods to calculate the crisp output of the system. Center of Gravity (COG) method is used in this application due to better results it gives. Performances of the proposed STPDFLC are compared with those of their corresponding PD-type conventional Fuzzy Logic Controller (PDFLC). The proposed scheme shows a remarkably improved performance over its conventional counterpart especially under parameters variation (payload). The two-link results of analysis are simulated. These simulation results are illustrated by using MATLAB® programming.

Functional Based Adaptive and Fuzzy Sliding Controller for Non-Autonomous Active Suspension System

NASA Astrophysics Data System (ADS)

Huang, Shiuh-Jer; Chen, Hung-Yi

In this paper, an adaptive sliding controller is developed for controlling a vehicle active suspension system. The functional approximation technique is employed to substitute the unknown non-autonomous functions of the suspension system and release the model-based requirement of sliding mode control algorithm. In order to improve the control performance and reduce the implementation problem, a fuzzy strategy with online learning ability is added to compensate the functional approximation error. The update laws of the functional approximation coefficients and the fuzzy tuning parameters are derived from the Lyapunov theorem to guarantee the system stability. The proposed controller is implemented on a quarter-car hydraulic actuating active suspension system test-rig. The experimental results show that the proposed controller suppresses the oscillation amplitude of the suspension system effectively.

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Subthreshold muscle twitches dissociate oscillatory neural signatures of conflicts from errors.

PubMed

Cohen, Michael X; van Gaal, Simon

2014-02-01

We investigated the neural systems underlying conflict detection and error monitoring during rapid online error correction/monitoring mechanisms. We combined data from four separate cognitive tasks and 64 subjects in which EEG and EMG (muscle activity from the thumb used to respond) were recorded. In typical neuroscience experiments, behavioral responses are classified as "error" or "correct"; however, closer inspection of our data revealed that correct responses were often accompanied by "partial errors" - a muscle twitch of the incorrect hand ("mixed correct trials," ~13% of the trials). We found that these muscle twitches dissociated conflicts from errors in time-frequency domain analyses of EEG data. In particular, both mixed-correct trials and full error trials were associated with enhanced theta-band power (4-9Hz) compared to correct trials. However, full errors were additionally associated with power and frontal-parietal synchrony in the delta band. Single-trial robust multiple regression analyses revealed a significant modulation of theta power as a function of partial error correction time, thus linking trial-to-trial fluctuations in power to conflict. Furthermore, single-trial correlation analyses revealed a qualitative dissociation between conflict and error processing, such that mixed correct trials were associated with positive theta-RT correlations whereas full error trials were associated with negative delta-RT correlations. These findings shed new light on the local and global network mechanisms of conflict monitoring and error detection, and their relationship to online action adjustment. © 2013.

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.

PubMed

Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan

2018-05-21

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.

FPGA-Based Smart Sensor for Online Displacement Measurements Using a Heterodyne Interferometer

PubMed Central

Vera-Salas, Luis Alberto; Moreno-Tapia, Sandra Veronica; Garcia-Perez, Arturo; de Jesus Romero-Troncoso, Rene; Osornio-Rios, Roque Alfredo; Serroukh, Ibrahim; Cabal-Yepez, Eduardo

2011-01-01

The measurement of small displacements on the nanometric scale demands metrological systems of high accuracy and precision. In this context, interferometer-based displacement measurements have become the main tools used for traceable dimensional metrology. The different industrial applications in which small displacement measurements are employed requires the use of online measurements, high speed processes, open architecture control systems, as well as good adaptability to specific process conditions. The main contribution of this work is the development of a smart sensor for large displacement measurement based on phase measurement which achieves high accuracy and resolution, designed to be used with a commercial heterodyne interferometer. The system is based on a low-cost Field Programmable Gate Array (FPGA) allowing the integration of several functions in a single portable device. This system is optimal for high speed applications where online measurement is needed and the reconfigurability feature allows the addition of different modules for error compensation, as might be required by a specific application. PMID:22164040

A dedicated on-line detecting system for auto air dryers

NASA Astrophysics Data System (ADS)

Shi, Chao-yu; Luo, Zai

2013-10-01

According to the correlative automobile industry standard and the requirements of manufacturer, this dedicated on-line detecting system is designed against the shortage of low degree automatic efficiency and detection precision of auto air dryer in the domestic. Fast automatic detection is achieved by combining the technology of computer control, mechatronics and pneumatics. This system can detect the speciality performance of pressure regulating valve and sealability of auto air dryer, in which online analytical processing of test data is available, at the same time, saving and inquiring data is achieved. Through some experimental analysis, it is indicated that efficient and accurate detection of the performance of auto air dryer is realized, and the test errors are less than 3%. Moreover, we carry out the type A evaluation of uncertainty in test data based on Bayesian theory, and the results show that the test uncertainties of all performance parameters are less than 0.5kPa, which can meet the requirements of operating industrial site absolutely.

On-line bolt-loosening detection method of key components of running trains using binocular vision

NASA Astrophysics Data System (ADS)

Xie, Yanxia; Sun, Junhua

2017-11-01

Bolt loosening, as one of hidden faults, affects the running quality of trains and even causes serious safety accidents. However, the developed fault detection approaches based on two-dimensional images cannot detect bolt-loosening due to lack of depth information. Therefore, we propose a novel online bolt-loosening detection method using binocular vision. Firstly, the target detection model based on convolutional neural network (CNN) is used to locate the target regions. And then, stereo matching and three-dimensional reconstruction are performed to detect bolt-loosening faults. The experimental results show that the looseness of multiple bolts can be characterized by the method simultaneously. The measurement repeatability and precision are less than 0.03mm, 0.09mm respectively, and its relative error is controlled within 1.09%.

On-line process control monitoring system

DOEpatents

O'Rourke, Patrick E.; Van Hare, David R.; Prather, William S.

1992-01-01

An on-line, fiber-optic based apparatus for monitoring the concentration of a chemical substance at a plurality of locations in a chemical processing system comprises a plurality of probes, each of which is at a different location in the system, a light source, optic fibers for carrying light to and from the probes, a multiplexer for switching light from the source from one probe to the next in series, a diode array spectrophotometer for producing a spectrum from the light received from the probes, and a computer programmed to analyze the spectra so produced. The probes allow the light to pass through the chemical substance so that a portion of the light is absorbed before being returned to the multiplexer. A standard and a reference cell are included for data validation and error checking.

Can an online clinical data management service help in improving data collection and data quality in a developing country setting?

PubMed

Wildeman, Maarten A; Zandbergen, Jeroen; Vincent, Andrew; Herdini, Camelia; Middeldorp, Jaap M; Fles, Renske; Dalesio, Otilia; van der Donk, Emile; Tan, I Bing

2011-08-08

Data collection by electronic medical record (EMR) systems have been proven to be helpful in data collection for scientific research and in improving healthcare. For a multi-centre trial in Indonesia and the Netherlands a web based system was selected to enable all participating centres to easily access data. This study assesses whether the introduction of a clinical trial data management service (CTDMS) composed of electronic case report forms (eCRF) can result in effective data collection and treatment monitoring. Data items entered were checked for inconsistencies automatically when submitted online. The data were divided into primary and secondary data items. We analysed both the total number of errors and the change in error rate, for both primary and secondary items, over the first five month of the trial. In the first five months 51 patients were entered. The primary data error rate was 1.6%, whilst that for secondary data was 2.7% against acceptable error rates for analysis of 1% and 2.5% respectively. The presented analysis shows that after five months since the introduction of the CTDMS the primary and secondary data error rates reflect acceptable levels of data quality. Furthermore, these error rates were decreasing over time. The digital nature of the CTDMS, as well as the online availability of that data, gives fast and easy insight in adherence to treatment protocols. As such, the CTDMS can serve as a tool to train and educate medical doctors and can improve treatment protocols.

Reconstructing the calibrated strain signal in the Advanced LIGO detectors

NASA Astrophysics Data System (ADS)

Viets, A. D.; Wade, M.; Urban, A. L.; Kandhasamy, S.; Betzwieser, J.; Brown, Duncan A.; Burguet-Castell, J.; Cahillane, C.; Goetz, E.; Izumi, K.; Karki, S.; Kissel, J. S.; Mendell, G.; Savage, R. L.; Siemens, X.; Tuyenbayev, D.; Weinstein, A. J.

2018-05-01

Advanced LIGO’s raw detector output needs to be calibrated to compute dimensionless strain h(t) . Calibrated strain data is produced in the time domain using both a low-latency, online procedure and a high-latency, offline procedure. The low-latency h(t) data stream is produced in two stages, the first of which is performed on the same computers that operate the detector’s feedback control system. This stage, referred to as the front-end calibration, uses infinite impulse response (IIR) filtering and performs all operations at a 16 384 Hz digital sampling rate. Due to several limitations, this procedure currently introduces certain systematic errors in the calibrated strain data, motivating the second stage of the low-latency procedure, known as the low-latency gstlal calibration pipeline. The gstlal calibration pipeline uses finite impulse response (FIR) filtering to apply corrections to the output of the front-end calibration. It applies time-dependent correction factors to the sensing and actuation components of the calibrated strain to reduce systematic errors. The gstlal calibration pipeline is also used in high latency to recalibrate the data, which is necessary due mainly to online dropouts in the calibrated data and identified improvements to the calibration models or filters.

Self-tuning regulators for multicyclic control of helicopter vibration

NASA Technical Reports Server (NTRS)

Johnson, W.

1982-01-01

A class of algorithms for the multicyclic control of helicopter vibration and loads is derived and discussed. This class is characterized by a linear, quasi-static, frequency-domain model of the helicopter response to control; identification of the helicopter model by least-squared-error or Kalman filter methods; and a minimum variance or quadratic performance function controller. Previous research on such controllers is reviewed. The derivations and discussions cover the helicopter model; the identification problem, including both off-line and on-line (recursive) algorithms; the control problem, including both open-loop and closed-loop feedback; and the various regulator configurations possible within this class. Conclusions from analysis and numerical simulations of the regulators provide guidance in the design and selection of algorithms for further development, including wind tunnel and flight tests.

Robot trajectory tracking with self-tuning predicted control

NASA Technical Reports Server (NTRS)

Cui, Xianzhong; Shin, Kang G.

1988-01-01

A controller that combines self-tuning prediction and control is proposed for robot trajectory tracking. The controller has two feedback loops: one is used to minimize the prediction error, and the other is designed to make the system output track the set point input. Because the velocity and position along the desired trajectory are given and the future output of the system is predictable, a feedforward loop can be designed for robot trajectory tracking with self-tuning predicted control (STPC). Parameters are estimated online to account for the model uncertainty and the time-varying property of the system. The authors describe the principle of STPC, analyze the system performance, and discuss the simplification of the robot dynamic equations. To demonstrate its utility and power, the controller is simulated for a Stanford arm.

An Automated Method to Generate e-Learning Quizzes from Online Language Learner Writing

ERIC Educational Resources Information Center

Flanagan, Brendan; Yin, Chengjiu; Hirokawa, Sachio; Hashimoto, Kiyota; Tabata, Yoshiyuki

2013-01-01

In this paper, the entries of Lang-8, which is a Social Networking Site (SNS) site for learning and practicing foreign languages, were analyzed and found to contain similar rates of errors for most error categories reported in previous research. These similarly rated errors were then processed using an algorithm to determine corrections suggested…

Reliable Real-Time Solution of Parametrized Partial Differential Equations: Reduced-Basis Output Bound Methods. Appendix 2

NASA Technical Reports Server (NTRS)

Prudhomme, C.; Rovas, D. V.; Veroy, K.; Machiels, L.; Maday, Y.; Patera, A. T.; Turinici, G.; Zang, Thomas A., Jr. (Technical Monitor)

2002-01-01

We present a technique for the rapid and reliable prediction of linear-functional outputs of elliptic (and parabolic) partial differential equations with affine parameter dependence. The essential components are (i) (provably) rapidly convergent global reduced basis approximations, Galerkin projection onto a space W(sub N) spanned by solutions of the governing partial differential equation at N selected points in parameter space; (ii) a posteriori error estimation, relaxations of the error-residual equation that provide inexpensive yet sharp and rigorous bounds for the error in the outputs of interest; and (iii) off-line/on-line computational procedures, methods which decouple the generation and projection stages of the approximation process. The operation count for the on-line stage, in which, given a new parameter value, we calculate the output of interest and associated error bound, depends only on N (typically very small) and the parametric complexity of the problem; the method is thus ideally suited for the repeated and rapid evaluations required in the context of parameter estimation, design, optimization, and real-time control.

Fault tolerant control of multivariable processes using auto-tuning PID controller.

PubMed

Yu, Ding-Li; Chang, T K; Yu, Ding-Wen

2005-02-01

Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.

Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

PubMed

Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

2014-07-01

In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Distributed Optimal Consensus Control for Multiagent Systems With Input Delay.

PubMed

Zhang, Huaipin; Yue, Dong; Zhao, Wei; Hu, Songlin; Dou, Chunxia; Huaipin Zhang; Dong Yue; Wei Zhao; Songlin Hu; Chunxia Dou; Hu, Songlin; Zhang, Huaipin; Dou, Chunxia; Yue, Dong; Zhao, Wei

2018-06-01

This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.

Correction to: CASPer, an online pre-interview screen for personal/professional characteristics: prediction of national licensure scores.

PubMed

Dore, Kelly L; Reiter, Harold I; Kreuger, Sharyn; Norman, Geoffrey R

2017-12-01

In re-examining the paper "CASPer, an online pre-interview screen for personal/professional characteristics: prediction of national licensure scores" published in AHSE (22(2), 327-336), we recognized two errors of interpretation.

Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments

PubMed Central

Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne

2015-01-01

In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916

Text Classification for Assisting Moderators in Online Health Communities

PubMed Central

Huh, Jina; Yetisgen-Yildiz, Meliha; Pratt, Wanda

2013-01-01

Objectives Patients increasingly visit online health communities to get help on managing health. The large scale of these online communities makes it impossible for the moderators to engage in all conversations; yet, some conversations need their expertise. Our work explores low-cost text classification methods to this new domain of determining whether a thread in an online health forum needs moderators’ help. Methods We employed a binary classifier on WebMD’s online diabetes community data. To train the classifier, we considered three feature types: (1) word unigram, (2) sentiment analysis features, and (3) thread length. We applied feature selection methods based on χ2 statistics and under sampling to account for unbalanced data. We then performed a qualitative error analysis to investigate the appropriateness of the gold standard. Results Using sentiment analysis features, feature selection methods, and balanced training data increased the AUC value up to 0.75 and the F1-score up to 0.54 compared to the baseline of using word unigrams with no feature selection methods on unbalanced data (0.65 AUC and 0.40 F1-score). The error analysis uncovered additional reasons for why moderators respond to patients’ posts. Discussion We showed how feature selection methods and balanced training data can improve the overall classification performance. We present implications of weighing precision versus recall for assisting moderators of online health communities. Our error analysis uncovered social, legal, and ethical issues around addressing community members’ needs. We also note challenges in producing a gold standard, and discuss potential solutions for addressing these challenges. Conclusion Social media environments provide popular venues in which patients gain health-related information. Our work contributes to understanding scalable solutions for providing moderators’ expertise in these large-scale, social media environments. PMID:24025513

Online referrals one way capitated groups gain efficiencies, reduce errors.

PubMed

2002-08-01

An online referral system is just the latest money and time-saving tool in the e-commerce arsenal at Hill Physicians Medical Group. Using a modified version of Healinx Corp.'s secure e-mail messaging platform, Hill is testing a custom-made online referral system at two primary care practices that appear to be helping the practice boost its bottom line under capitation.

Near-infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Parching Process of Traditional Chinese Medicine Based on Two Kinds of Chemical Indicators.

PubMed

Li, Kaiyue; Wang, Weiying; Liu, Yanping; Jiang, Su; Huang, Guo; Ye, Liming

2017-01-01

The active ingredients and thus pharmacological efficacy of traditional Chinese medicine (TCM) at different degrees of parching process vary greatly. Near-infrared spectroscopy (NIR) was used to develop a new method for rapid online analysis of TCM parching process, using two kinds of chemical indicators (5-(hydroxymethyl) furfural [5-HMF] content and 420 nm absorbance) as reference values which were obviously observed and changed in most TCM parching process. Three representative TCMs, Areca ( Areca catechu L.), Malt ( Hordeum Vulgare L.), and Hawthorn ( Crataegus pinnatifida Bge.), were used in this study. With partial least squares regression, calibration models of NIR were generated based on two kinds of reference values, i.e. 5-HMF contents measured by high-performance liquid chromatography (HPLC) and 420 nm absorbance measured by ultraviolet-visible spectroscopy (UV/Vis), respectively. In the optimized models for 5-HMF, the root mean square errors of prediction (RMSEP) for Areca, Malt, and Hawthorn was 0.0192, 0.0301, and 0.2600 and correlation coefficients ( R cal ) were 99.86%, 99.88%, and 99.88%, respectively. Moreover, in the optimized models using 420 nm absorbance as reference values, the RMSEP for Areca, Malt, and Hawthorn was 0.0229, 0.0096, and 0.0409 and R cal were 99.69%, 99.81%, and 99.62%, respectively. NIR models with 5-HMF content and 420 nm absorbance as reference values can rapidly and effectively identify three kinds of TCM in different parching processes. This method has great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online analysis and quality control in TCM industrial manufacturing process. Near-infrared spectroscopy.(NIR) was used to develop a new method for online analysis of traditional Chinese medicine.(TCM) parching processCalibration and validation models of Areca, Malt, and Hawthorn were generated by partial least squares regression using 5.(hydroxymethyl) furfural contents and 420.nm absorbance as reference values, respectively, which were main indicator components during parching process of most TCMThe established NIR models of three TCMs had low root mean square errors of prediction and high correlation coefficientsThe NIR method has great promise for use in TCM industrial manufacturing processes for rapid online analysis and quality control. Abbreviations used: NIR: Near-infrared Spectroscopy; TCM: Traditional Chinese medicine; Areca: Areca catechu L.; Hawthorn: Crataegus pinnatifida Bge.; Malt: Hordeum vulgare L.; 5-HMF: 5-(hydroxymethyl) furfural; PLS: Partial least squares; D: Dimension faction; SLS: Straight line subtraction, MSC: Multiplicative scatter correction; VN: Vector normalization; RMSECV: Root mean square errors of cross-validation; RMSEP: Root mean square errors of validation; R cal : Correlation coefficients; RPD: Residual predictive deviation; PAT: Process analytical technology; FDA: Food and Drug Administration; ICH: International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use.

Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

PubMed

Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher

2013-10-01

This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example.

Intelligent nonsingular terminal sliding-mode control using MIMO Elman neural network for piezo-flexural nanopositioning stage.

PubMed

Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan

2012-12-01

The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.

Analysis of separation test for automatic brake adjuster based on linear radon transformation

NASA Astrophysics Data System (ADS)

Luo, Zai; Jiang, Wensong; Guo, Bin; Fan, Weijun; Lu, Yi

2015-01-01

The linear Radon transformation is applied to extract inflection points for online test system under the noise conditions. The linear Radon transformation has a strong ability of anti-noise and anti-interference by fitting the online test curve in several parts, which makes it easy to handle consecutive inflection points. We applied the linear Radon transformation to the separation test system to solve the separating clearance of automatic brake adjuster. The experimental results show that the feature point extraction error of the gradient maximum optimal method is approximately equal to ±0.100, while the feature point extraction error of linear Radon transformation method can reach to ±0.010, which has a lower error than the former one. In addition, the linear Radon transformation is robust.

A microprocessor controlled pressure scanning system

NASA Technical Reports Server (NTRS)

Anderson, R. C.

1976-01-01

A microprocessor-based controller and data logger for pressure scanning systems is described. The microcomputer positions and manages data from as many as four 48-port electro-mechanical pressure scanners. The maximum scanning rate is 80 pressure measurements per second (20 ports per second on each of four scanners). The system features on-line calibration, position-directed data storage, and once-per-scan display in engineering units of data from a selected port. The system is designed to be interfaced to a facility computer through a shared memory. System hardware and software are described. Factors affecting measurement error in this type of system are also discussed.

On-line measurement of diameter of hot-rolled steel tube

NASA Astrophysics Data System (ADS)

Zhu, Xueliang; Zhao, Huiying; Tian, Ailing; Li, Bin

2015-02-01

In order to design a online diameter measurement system for Hot-rolled seamless steel tube production line. On one hand, it can play a stimulate part in the domestic pipe measuring technique. On the other hand, it can also make our domestic hot rolled seamless steel tube enterprises gain a strong product competitiveness with low input. Through the analysis of various detection methods and techniques contrast, this paper choose a CCD camera-based online caliper system design. The system mainly includes the hardware measurement portion and the image processing section, combining with software control technology and image processing technology, which can complete online measurement of heat tube diameter. Taking into account the complexity of the actual job site situation, it can choose a relatively simple and reasonable layout. The image processing section mainly to solve the camera calibration and the application of a function in Matlab, to achieve the diameter size display directly through the algorithm to calculate the image. I build a simulation platform in the design last phase, successfully, collect images for processing, to prove the feasibility and rationality of the design and make error in less than 2%. The design successfully using photoelectric detection technology to solve real work problems

Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.

Media multitasking and failures of attention in everyday life.

PubMed

Ralph, Brandon C W; Thomson, David R; Cheyne, James Allan; Smilek, Daniel

2014-09-01

Using a series of online self-report measures, we examine media multitasking, a particularly pervasive form of multitasking, and its relations to three aspects of everyday attention: (1) failures of attention and cognitive errors (2) mind wandering, and (3) attentional control with an emphasis on attentional switching and distractibility. We observed a positive correlation between levels of media multitasking and self-reports of attentional failures, as well as with reports of both spontaneous and deliberate mind wandering. No correlation was observed between media multitasking and self-reported memory failures, lending credence to the hypothesis that media multitasking may be specifically related to problems of inattention, rather than cognitive errors in general. Furthermore, media multitasking was not related with self-reports of difficulties in attention switching or distractibility. We offer a plausible causal structural model assessing both direct and indirect effects among media multitasking, attentional failures, mind wandering, and cognitive errors, with the heuristic goal of constraining and motivating theories of the effects of media multitasking on inattention.

Developing an App by Exploiting Web-Based Mobile Technology to Inspect Controlled Substances in Patient Care Units

PubMed Central

2017-01-01

We selected iOS in this study as the App operation system, Objective-C as the programming language, and Oracle as the database to develop an App to inspect controlled substances in patient care units. Using a web-enabled smartphone, pharmacist inspection can be performed on site and the inspection result can be directly recorded into HIS through the Internet, so human error of data translation can be minimized and the work efficiency and data processing can be improved. This system not only is fast and convenient compared to the conventional paperwork, but also provides data security and accuracy. In addition, there are several features to increase inspecting quality: (1) accuracy of drug appearance, (2) foolproof mechanism to avoid input errors or miss, (3) automatic data conversion without human judgments, (4) online alarm of expiry date, and (5) instant inspection result to show not meted items. This study has successfully turned paper-based medication inspection into inspection using a web-based mobile device. PMID:28286761

Developing an App by Exploiting Web-Based Mobile Technology to Inspect Controlled Substances in Patient Care Units.

PubMed

Lu, Ying-Hao; Lee, Li-Yao; Chen, Ying-Lan; Cheng, Hsing-I; Tsai, Wen-Tsung; Kuo, Chen-Chun; Chen, Chung-Yu; Huang, Yaw-Bin

2017-01-01

We selected iOS in this study as the App operation system, Objective-C as the programming language, and Oracle as the database to develop an App to inspect controlled substances in patient care units. Using a web-enabled smartphone, pharmacist inspection can be performed on site and the inspection result can be directly recorded into HIS through the Internet, so human error of data translation can be minimized and the work efficiency and data processing can be improved. This system not only is fast and convenient compared to the conventional paperwork, but also provides data security and accuracy. In addition, there are several features to increase inspecting quality: (1) accuracy of drug appearance, (2) foolproof mechanism to avoid input errors or miss, (3) automatic data conversion without human judgments, (4) online alarm of expiry date, and (5) instant inspection result to show not meted items. This study has successfully turned paper-based medication inspection into inspection using a web-based mobile device.

Image guidance in prostate cancer - can offline corrections be an effective substitute for daily online imaging?

PubMed

Prasad, Devleena; Das, Pinaki; Saha, Niladri S; Chatterjee, Sanjoy; Achari, Rimpa; Mallick, Indranil

2014-01-01

This aim of this study was to determine if a less resource-intensive and established offline correction protocol - the No Action Level (NAL) protocol was as effective as daily online corrections of setup deviations in curative high-dose radiotherapy of prostate cancer. A total of 683 daily megavoltage CT (MVCT) or kilovoltage CT (kvCBCT) images of 30 patients with localized prostate cancer treated with intensity modulated radiotherapy were evaluated. Daily image-guidance was performed and setup errors in three translational axes recorded. The NAL protocol was simulated by using the mean shift calculated from the first five fractions and implemented on all subsequent treatments. Using the imaging data from the remaining fractions, the daily residual error (RE) was determined. The proportion of fractions where the RE was greater than 3,5 and 7 mm was calculated, and also the actual PTV margin that would be required if the offline protocol was followed. Using the NAL protocol reduced the systematic but not the random errors. Corrections made using the NAL protocol resulted in small and acceptable RE in the mediolateral (ML) and superoinferior (SI) directions with 46/533 (8.1%) and 48/533 (5%) residual shifts above 5 mm. However; residual errors greater than 5mm in the anteroposterior (AP) direction remained in 181/533 (34%) of fractions. The PTV margins calculated based on residual errors were 5mm, 5mm and 13 mm in the ML, SI and AP directions respectively. Offline correction using the NAL protocol resulted in unacceptably high residual errors in the AP direction, due to random uncertainties of rectal and bladder filling. Daily online imaging and corrections remain the standard image guidance policy for highly conformal radiotherapy of prostate cancer.

Towards a robust BCI: error potentials and online learning.

PubMed

Buttfield, Anna; Ferrez, Pierre W; Millán, José del R

2006-06-01

Recent advances in the field of brain-computer interfaces (BCIs) have shown that BCIs have the potential to provide a powerful new channel of communication, completely independent of muscular and nervous systems. However, while there have been successful laboratory demonstrations, there are still issues that need to be addressed before BCIs can be used by nonexperts outside the laboratory. At IDIAP Research Institute, we have been investigating several areas that we believe will allow us to improve the robustness, flexibility, and reliability of BCIs. One area is recognition of cognitive error states, that is, identifying errors through the brain's reaction to mistakes. The production of these error potentials (ErrP) in reaction to an error made by the user is well established. We have extended this work by identifying a similar but distinct ErrP that is generated in response to an error made by the interface, (a misinterpretation of a command that the user has given). This ErrP can be satisfactorily identified in single trials and can be demonstrated to improve the theoretical performance of a BCI. A second area of research is online adaptation of the classifier. BCI signals change over time, both between sessions and within a single session, due to a number of factors. This means that a classifier trained on data from a previous session will probably not be optimal for a new session. In this paper, we present preliminary results from our investigations into supervised online learning that can be applied in the initial training phase. We also discuss the future direction of this research, including the combination of these two currently separate issues to create a potentially very powerful BCI.

Monitoring the CMS strip tracker readout system

NASA Astrophysics Data System (ADS)

Mersi, S.; Bainbridge, R.; Baulieu, G.; Bel, S.; Cole, J.; Cripps, N.; Delaere, C.; Drouhin, F.; Fulcher, J.; Giassi, A.; Gross, L.; Hahn, K.; Mirabito, L.; Nikolic, M.; Tkaczyk, S.; Wingham, M.

2008-07-01

The CMS Silicon Strip Tracker at the LHC comprises a sensitive area of approximately 200 m2 and 10 million readout channels. Its data acquisition system is based around a custom analogue front-end chip. Both the control and the readout of the front-end electronics are performed by off-detector VME boards in the counting room, which digitise the raw event data and perform zero-suppression and formatting. The data acquisition system uses the CMS online software framework to configure, control and monitor the hardware components and steer the data acquisition. The first data analysis is performed online within the official CMS reconstruction framework, which provides many services, such as distributed analysis, access to geometry and conditions data, and a Data Quality Monitoring tool based on the online physics reconstruction. The data acquisition monitoring of the Strip Tracker uses both the data acquisition and the reconstruction software frameworks in order to provide real-time feedback to shifters on the operational state of the detector, archiving for later analysis and possibly trigger automatic recovery actions in case of errors. Here we review the proposed architecture of the monitoring system and we describe its software components, which are already in place, the various monitoring streams available, and our experiences of operating and monitoring a large-scale system.

Direct power control of DFIG wind turbine systems based on an intelligent proportional-integral sliding mode control.

PubMed

Li, Shanzhi; Wang, Haoping; Tian, Yang; Aitouch, Abdel; Klein, John

2016-09-01

This paper presents an intelligent proportional-integral sliding mode control (iPISMC) for direct power control of variable speed-constant frequency wind turbine system. This approach deals with optimal power production (in the maximum power point tracking sense) under several disturbance factors such as turbulent wind. This controller is made of two sub-components: (i) an intelligent proportional-integral module for online disturbance compensation and (ii) a sliding mode module for circumventing disturbance estimation errors. This iPISMC method has been tested on FAST/Simulink platform of a 5MW wind turbine system. The obtained results demonstrate that the proposed iPISMC method outperforms the classical PI and intelligent proportional-integral control (iPI) in terms of both active power and response time. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Inner-Loop Rover Control

NASA Technical Reports Server (NTRS)

Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

2006-01-01

Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

Evaluation of causes and frequency of medication errors during information technology downtime.

PubMed

Hanuscak, Tara L; Szeinbach, Sheryl L; Seoane-Vazquez, Enrique; Reichert, Brendan J; McCluskey, Charles F

2009-06-15

The causes and frequency of medication errors occurring during information technology downtime were evaluated. Individuals from a convenience sample of 78 hospitals who were directly responsible for supporting and maintaining clinical information systems (CISs) and automated dispensing systems (ADSs) were surveyed using an online tool between February 2007 and May 2007 to determine if medication errors were reported during periods of system downtime. The errors were classified using the National Coordinating Council for Medication Error Reporting and Prevention severity scoring index. The percentage of respondents reporting downtime was estimated. Of the 78 eligible hospitals, 32 respondents with CIS and ADS responsibilities completed the online survey for a response rate of 41%. For computerized prescriber order entry, patch installations and system upgrades caused an average downtime of 57% over a 12-month period. Lost interface and interface malfunction were reported for centralized and decentralized ADSs, with an average downtime response of 34% and 29%, respectively. The average downtime response was 31% for software malfunctions linked to clinical decision-support systems. Although patient harm did not result from 30 (54%) medication errors, the potential for harm was present for 9 (16%) of these errors. Medication errors occurred during CIS and ADS downtime despite the availability of backup systems and standard protocols to handle periods of system downtime. Efforts should be directed to reduce the frequency and length of down-time in order to minimize medication errors during such downtime.

Improving NGDC Track-line Data Quality Control

NASA Astrophysics Data System (ADS)

Chandler, M. T.; Wessel, P.

2004-12-01

Ship-board gravity, magnetic and bathymetry data archived at the National Geophysical Data Center (NGDC) represent decades of seagoing research, containing over 4,500 cruises. Cruise data remain relevent despite the prominence of satellite altimetry-derived global grids because many geologic processes remain resolvable by oceanographic research alone. Due to the tremendous investment put forth by scientists and taxpayers to compile this vast archive and the significant errors found within it, additional quality assessment and corrections are warranted. These can best be accomplished by adding to existing quality control measures at NGDC. We are currently developing open source software to provide additional quality control. Along with NGDC's current sanity checking, new data at NGDC will also be subjected to an along-track ``sniffer'' which will detect and flag suspicious data for later graphical inspection using a visual editor. If new data pass these tests, they will undergo further scrutinization using a crossover error (COE) calculator which will compare new data values to existing values at points of intersection within the archive. Data passing these tests will be deemed ``quality data`` and suitable for permanent addition to the archive, while data that fail will be returned to the source institution for correction. Crossover errors will be stored and an online COE database will be available. The COE database will allow users to apply corrections to the NGDC track-line database to produce corrected data files. At no time will the archived data itself be modified. An attempt will also be made to reduce navigational errors for pre-GPS navigated cruises. Upon completion these programs will be used to explore and model systematic errors within the archive, generate correction tables for all cruises, and to quantify the error budget in marine geophysical observations. Software will be released and these procedures will be implemented in cooperation with NGDC staff.

OOPS! Retractions, Corrections, and Amplifications in Online Environments.

ERIC Educational Resources Information Center

Ojala, Marydee

1996-01-01

Examines the practice and implications of issuing corrections, retractions, and amplifications in online databases. All database producers do not provide mechanisms to accommodate retractions and corrections, and it can be difficult for a searcher to find evidence of error correction. Sidebars illustrate both the lack of and evidence of…

The Online Translator: Implementing National Standard 4.1.

ERIC Educational Resources Information Center

Burton, Christine

2003-01-01

A pedagogical idea for addressing National Standard 4.1 (Students demonstrate understanding of the nature of language through comparisons of language studied and their own) suggests the deliberate use of the online translator to illustrate to students the syntactical errors that occur when translating idioms from one language to another. (VWL)

Correction to: A Comparison of the Energetic Cost of Running in Marathon Racing Shoes.

PubMed

Hoogkamer, Wouter; Kipp, Shalaya; Frank, Jesse H; Farina, Emily M; Luo, Geng; Kram, Rodger

2018-06-01

An Online First version of this article was made available online at https://link.springer.com/article/10.1007/s40279-017-0811-2 on 16 November 2017. An error was subsequently identified in the article, and the following correction should be noted.

Correction to: Tanner-Whitehouse Skeletal Ages in Male Youth Soccer Players: TW2 or TW3?

PubMed

Malina, Robert M; Coelho-E-Silva, Manuel J; Figueiredo, António J; Philippaerts, Renaat M; Hirose, Norikazu; Reyes, Maria Eugenia Peña; Gilli, Giulio; Benso, Andrea; Vaeyens, Roel; Deprez, Dieter; Guglielmo, Luiz G A; Buranarugsa, Rojapon

2018-04-01

An Online First version of this article was made available online at https://link.springer.com/article/10.1007%2Fs40279-017-0799-7 on 29 October 2017. Errors were subsequently identified in the article, and the following corrections should be noted.

Semantic Typicality Effects in Acquired Dyslexia: Evidence for Semantic Impairment in Deep Dyslexia.

PubMed

Riley, Ellyn A; Thompson, Cynthia K

2010-06-01

BACKGROUND: Acquired deep dyslexia is characterized by impairment in grapheme-phoneme conversion and production of semantic errors in oral reading. Several theories have attempted to explain the production of semantic errors in deep dyslexia, some proposing that they arise from impairments in both grapheme-phoneme and lexical-semantic processing, and others proposing that such errors stem from a deficit in phonological production. Whereas both views have gained some acceptance, the limited evidence available does not clearly eliminate the possibility that semantic errors arise from a lexical-semantic input processing deficit. AIMS: To investigate semantic processing in deep dyslexia, this study examined the typicality effect in deep dyslexic individuals, phonological dyslexic individuals, and controls using an online category verification paradigm. This task requires explicit semantic access without speech production, focusing observation on semantic processing from written or spoken input. METHODS #ENTITYSTARTX00026; PROCEDURES: To examine the locus of semantic impairment, the task was administered in visual and auditory modalities with reaction time as the primary dependent measure. Nine controls, six phonological dyslexic participants, and five deep dyslexic participants completed the study. OUTCOMES #ENTITYSTARTX00026; RESULTS: Controls and phonological dyslexic participants demonstrated a typicality effect in both modalities, while deep dyslexic participants did not demonstrate a typicality effect in either modality. CONCLUSIONS: These findings suggest that deep dyslexia is associated with a semantic processing deficit. Although this does not rule out the possibility of concomitant deficits in other modules of lexical-semantic processing, this finding suggests a direction for treatment of deep dyslexia focused on semantic processing.

The experimental results of a self tuning adaptive controller using online frequency identification. [for Galileo spacecraft

NASA Technical Reports Server (NTRS)

Chiang, W.-W.; Cannon, R. H., Jr.

1985-01-01

A fourth-order laboratory dynamic system featuring very low structural damping and a noncolocated actuator-sensor pair has been used to test a novel real-time adaptive controller, implemented in a minicomputer, which consists of a state estimator, a set of state feedback gains, and a frequency-locked loop for real-time parameter identification. The adaptation algorithm employed can correct controller error and stabilize the system for more than 50 percent variation in the plant's natural frequency, compared with a 10 percent stability margin in frequency variation for a fixed gain controller having the same performance as the nominal plant condition. The very rapid convergence achievable by this adaptive system is demonstrated experimentally, and proven with simple, root-locus methods.

Adaptive relative pose control for autonomous spacecraft rendezvous and proximity operations with thrust misalignment and model uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2017-04-01

An adaptive relative pose control strategy is proposed for a pursue spacecraft in proximity operations on a tumbling target. Relative position vector between two spacecraft is required to direct towards the docking port of the target while the attitude of them must be synchronized. With considering the thrust misalignment of pursuer, an integrated controller for relative translational and relative rotational dynamics is developed by using norm-wise adaptive estimations. Parametric uncertainties, unknown coupled dynamics, and bounded external disturbances are compensated online by adaptive update laws. It is proved via Lyapunov stability theory that the tracking errors of relative pose converge to zero asymptotically. Numerical simulations including six degrees-of-freedom rigid body dynamics are performed to demonstrate the effectiveness of the proposed controller.

Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs.

PubMed

Shi, Wuxi; Luo, Rui; Li, Baoquan

2017-01-01

In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The Men's Safer Sex project: intervention development and feasibility randomised controlled trial of an interactive digital intervention to increase condom use in men.

PubMed

Bailey, Julia V; Webster, Rosie; Hunter, Rachael; Griffin, Mark; Freemantle, Nicholas; Rait, Greta; Estcourt, Claudia; Michie, Susan; Anderson, Jane; Stephenson, Judith; Gerressu, Makeda; Ang, Chee Siang; Murray, Elizabeth

2016-12-01

This report details the development of the Men's Safer Sex website and the results of a feasibility randomised controlled trial (RCT), health economic assessment and qualitative evaluation. (1) Develop the Men's Safer Sex website to address barriers to condom use; (2) determine the best design for an online RCT; (3) inform the methods for collecting and analysing health economic data; (4) assess the Sexual Quality of Life (SQoL) questionnaire and European Quality of Life-5 Dimensions, three-level version (EQ-5D-3L) to calculate quality-adjusted life-years (QALYs); and (5) explore clinic staff and men's views of online research methodology. (1) Website development: we combined evidence from research literature and the views of experts ( n  = 18) and male clinic users ( n  = 43); (2) feasibility RCT: 159 heterosexually active men were recruited from three sexual health clinics and were randomised by computer to the Men's Safer Sex website plus usual care ( n  = 84) or usual clinic care only ( n  = 75). Men were invited to complete online questionnaires at 3, 6, 9 and 12 months, and sexually transmitted infection (STI) diagnoses were recorded from clinic notes at 12 months; (3) health economic evaluation: we investigated the impact of using different questionnaires to calculate utilities and QALYs (the EQ-5D-3L and SQoL questionnaire), and compared different methods to collect resource use; and (4) qualitative evaluation: thematic analysis of interviews with 11 male trial participants and nine clinic staff, as well as free-text comments from online outcome questionnaires. (1) Software errors and clinic Wi-Fi access presented significant challenges. Response rates for online questionnaires were poor but improved with larger vouchers (from 36% with £10 to 50% with £30). Clinical records were located for 94% of participants for STI diagnoses. There were no group differences in condomless sex with female partners [incidence rate ratio (IRR) 1.01, 95% confidence interval (CI) 0.52 to 1.96]. New STI diagnoses were recorded for 8.8% (7/80) of the intervention group and 13.0% (9/69) of the control group (IRR 0.75, 95% CI 0.29 to 1.89). (2) Health-care resource data were more complete using patient files than questionnaires. The probability that the intervention is cost-effective is sensitive to the source of data used and whether or not data on intended pregnancies are included. (3) The pilot RCT fitted well around clinical activities but 37% of the intervention group did not see the Men's Safer Sex website and technical problems were frustrating. Men's views of the Men's Safer Sex website and research procedures were largely positive. It would be feasible to conduct a large-scale RCT using clinic STI diagnoses as a primary outcome; however, technical errors and a poor response rate limited the collection of online self-reported outcomes. The next steps are (1) to optimise software for online trials, (2) to find the best ways to integrate digital health promotion with clinical services, (3) to develop more precise methods for collecting resource use data and (4) to work out how to overcome barriers to digital intervention testing and implementation in the NHS. Current Controlled Trials ISRCTN18649610. This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment ; Vol. 20, No. 91. See the NIHR Journals Library website for further project information.

Finite-Time Attitude Tracking Control for Spacecraft Using Terminal Sliding Mode and Chebyshev Neural Network.

PubMed

An-Min Zou; Kumar, K D; Zeng-Guang Hou; Xi Liu

2011-08-01

A finite-time attitude tracking control scheme is proposed for spacecraft using terminal sliding mode and Chebyshev neural network (NN) (CNN). The four-parameter representations (quaternion) are used to describe the spacecraft attitude for global representation without singularities. The attitude state (i.e., attitude and velocity) error dynamics is transformed to a double integrator dynamics with a constraint on the spacecraft attitude. With consideration of this constraint, a novel terminal sliding manifold is proposed for the spacecraft. In order to guarantee that the output of the NN used in the controller is bounded by the corresponding bound of the approximated unknown function, a switch function is applied to generate a switching between the adaptive NN control and the robust controller. Meanwhile, a CNN, whose basis functions are implemented using only desired signals, is introduced to approximate the desired nonlinear function and bounded external disturbances online, and the robust term based on the hyperbolic tangent function is applied to counteract NN approximation errors in the adaptive neural control scheme. Most importantly, the finite-time stability in both the reaching phase and the sliding phase can be guaranteed by a Lyapunov-based approach. Finally, numerical simulations on the attitude tracking control of spacecraft in the presence of an unknown mass moment of inertia matrix, bounded external disturbances, and control input constraints are presented to demonstrate the performance of the proposed controller.

VizieR Online Data Catalog: Mira Variables in the OGLE Bulge fields (Groenewegen+, 2005)

NASA Astrophysics Data System (ADS)

Groenewegen, M. A. T.; Blommaert, J. A. D. L.

2005-07-01

Table 1 provides the results of the period analysis (up to 3 periods with error and amplitudes with error), and associated 2MASS and DENIS photometry. Table 2 provides the cross-correlation with other objects and special remarks. (4 data files).

Teaching Statistics Online Using "Excel"

ERIC Educational Resources Information Center

Jerome, Lawrence

2011-01-01

As anyone who has taught or taken a statistics course knows, statistical calculations can be tedious and error-prone, with the details of a calculation sometimes distracting students from understanding the larger concepts. Traditional statistics courses typically use scientific calculators, which can relieve some of the tedium and errors but…

Set-up uncertainties: online correction with X-ray volume imaging.

PubMed

Kataria, Tejinder; Abhishek, Ashu; Chadha, Pranav; Nandigam, Janardhan

2011-01-01

To determine interfractional three-dimensional set-up errors using X-ray volumetric imaging (XVI). Between December 2007 and August 2009, 125 patients were taken up for image-guided radiotherapy using online XVI. After matching of reference and acquired volume view images, set-up errors in three translation directions were recorded and corrected online before treatment each day. Mean displacements, population systematic (Σ), and random (σ) errors were calculated and analyzed using SPSS (v16) software. Optimum clinical target volume (CTV) to planning target volume (PTV) margin was calculated using Van Herk's (2.5Σ + 0.7 σ) and Stroom's (2Σ + 0.7 σ) formula. Patients were grouped in 4 cohorts, namely brain, head and neck, thorax, and abdomen-pelvis. The mean vector displacement recorded were 0.18 cm, 0.15 cm, 0.36 cm, and 0.35 cm for brain, head and neck, thorax, and abdomen-pelvis, respectively. Analysis of individual mean set-up errors revealed good agreement with the proposed 0.3 cm isotropic margins for brain and 0.5 cm isotropic margins for head-neck. Similarly, 0.5 cm circumferential and 1 cm craniocaudal proposed margins were in agreement with thorax and abdomen-pelvic cases. The calculated mean displacements were well within CTV-PTV margin estimates of Van Herk (90% population coverage to minimum 95% prescribed dose) and Stroom (99% target volume coverage by 95% prescribed dose). Employing these individualized margins in a particular cohort ensure comparable target coverage as described in literature, which is further improved if XVI-aided set-up error detection and correction is used before treatment.

The Neural Substrates of Cognitive Control Deficits in Autism Spectrum Disorders

PubMed Central

Solomon, Marjorie; Ozonoff, Sally; Ursu, Stefan; Ravizza, Susan; Cummings, Neil; Ly, Stanford; Carter, Cameron

2009-01-01

Executive functions deficits are among the most frequently reported symptoms of autism spectrum disorders (ASDs), however, there have been few functional magnetic resonance imaging (fMRI) studies that investigate the neural substrates of executive functions deficits in ASDs, and only one in adolescents. The current study examined cognitive control –the ability to maintain task context online to support adaptive functioning in the face of response competition—in 22 adolescents aged 12–18 with autism spectrum disorders and 23 age, gender, and IQ matched typically developing subjects. During the cue phase of the task, where subjects must maintain information online to overcome a prepotent response tendency, typically developing subjects recruited significantly more anterior frontal (BA 10), parietal (BA 7, 40), and occipital regions (BA 18) for high control trials (25% of trials) versus low control trials (75% of trials). Both groups showed similar activation for low control cues, however the ASD group exhibited significantly less activation for high control cues. Functional connectivity analysis using time series correlation, factor analysis, and beta series correlation methods provided convergent evidence that the ASD group exhibited lower levels of functional connectivity and less network integration between frontal, parietal, and occipital regions. In the typically developing group, fronto-parietal connectivity was related to lower error rates on high control trials. In the autism group, reduced fronto-parietal connectivity was related to attention deficit hyperactivity disorder symptoms. PMID:19410583

Inverse optimal self-tuning PID control design for an autonomous underwater vehicle

NASA Astrophysics Data System (ADS)

Rout, Raja; Subudhi, Bidyadhar

2017-01-01

This paper presents a new approach to path following control design for an autonomous underwater vehicle (AUV). A NARMAX model of the AUV is derived first and then its parameters are adapted online using the recursive extended least square algorithm. An adaptive Propotional-Integral-Derivative (PID) controller is developed using the derived parameters to accomplish the path following task of an AUV. The gain parameters of the PID controller are tuned using an inverse optimal control technique, which alleviates the problem of solving Hamilton-Jacobian equation and also satisfies an error cost function. Simulation studies were pursued to verify the efficacy of the proposed control algorithm. From the obtained results, it is envisaged that the proposed NARMAX model-based self-tuning adaptive PID control provides good path following performance even in the presence of uncertainty arising due to ocean current or hydrodynamic parameter.

Impedance Control of the Rehabilitation Robot Based on Sliding Mode Control

NASA Astrophysics Data System (ADS)

Zhou, Jiawang; Zhou, Zude; Ai, Qingsong

As an auxiliary treatment, the 6-DOF parallel robot plays an important role in lower limb rehabilitation. In order to improve the efficiency and flexibility of the lower limb rehabilitation training, this paper studies the impedance controller based on the position control. A nonsingular terminal sliding mode control is developed to ensure the trajectory tracking precision and in contrast to traditional PID control strategy in the inner position loop, the system will be more stable. The stability of the system is proved by Lyapunov function to guarantee the convergence of the control errors. Simulation results validate the effectiveness of the target impedance model and show that the parallel robot can adjust gait trajectory online according to the human-machine interaction force to meet the gait request of patients, and changing the impedance parameters can meet the demands of different stages of rehabilitation training.

Fuel-injection control of S.I. engines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, S.B.; Won, M.; Hedrick, J.K.

1994-12-31

It is known that about 50% of air pollutants comes from automotive engine exhaust, and mostly in a transient state operation. However, the wide operating range, the inherent nonlinearities of the induction process and the large modeling uncertainties make the design of the fuel-injection controller very difficult. Also, the unavoidable large time-delay between control action and measurement causes the problem of chattering. In this paper, an observer-based control algorithm based on sliding mode control technique is suggested for fast response and small amplitude chattering of the air-to-fuel ratio. A direct adaptive control using Gaussian networks is applied to the compensationmore » of transient fueling dynamics. The proposed controller is simple enough for on-line computation and is implemented on an automotive engine using a PC-386. The simulation and the experimental results show that this algorithm reduces the chattering magnitude considerably and is robust to modeling errors.« less

Investigation of High School Students' Online Science Information Searching Performance: The Role of Implicit and Explicit Strategies

NASA Astrophysics Data System (ADS)

Tsai, Meng-Jung; Hsu, Chung-Yuan; Tsai, Chin-Chung

2012-04-01

Due to a growing trend of exploring scientific knowledge on the Web, a number of studies have been conducted to highlight examination of students' online searching strategies. The investigation of online searching generally employs methods including a survey, interview, screen-capturing, or transactional logs. The present study firstly intended to utilize a survey, the Online Information Searching Strategies Inventory (OISSI), to examine users' searching strategies in terms of control, orientation, trial and error, problem solving, purposeful thinking, selecting main ideas, and evaluation, which is defined as implicit strategies. Second, this study conducted screen-capturing to investigate the students' searching behaviors regarding the number of keywords, the quantity and depth of Web page exploration, and time attributes, which is defined as explicit strategies. Ultimately, this study explored the role that these two types of strategies played in predicting the students' online science information searching outcomes. A total of 103 Grade 10 students were recruited from a high school in northern Taiwan. Through Pearson correlation and multiple regression analyses, the results showed that the students' explicit strategies, particularly the time attributes proposed in the present study, were more successful than their implicit strategies in predicting their outcomes of searching science information. The participants who spent more time on detailed reading (explicit strategies) and had better skills of evaluating Web information (implicit strategies) tended to have superior searching performance.

Certified dual-corrected radiation patterns of phased antenna arrays by offline–online order reduction of finite-element models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sommer, A., E-mail: a.sommer@lte.uni-saarland.de; Farle, O., E-mail: o.farle@lte.uni-saarland.de; Dyczij-Edlinger, R., E-mail: edlinger@lte.uni-saarland.de

2015-10-15

This paper presents a fast numerical method for computing certified far-field patterns of phased antenna arrays over broad frequency bands as well as wide ranges of steering and look angles. The proposed scheme combines finite-element analysis, dual-corrected model-order reduction, and empirical interpolation. To assure the reliability of the results, improved a posteriori error bounds for the radiated power and directive gain are derived. Both the reduced-order model and the error-bounds algorithm feature offline–online decomposition. A real-world example is provided to demonstrate the efficiency and accuracy of the suggested approach.

Online production validation in a HEP environment

NASA Astrophysics Data System (ADS)

Harenberg, T.; Kuhl, T.; Lang, N.; Mättig, P.; Sandhoff, M.; Schwanenberger, C.; Volkmer, F.

2017-03-01

In high energy physics (HEP) event simulations, petabytes of data are processed and stored requiring millions of CPU-years. This enormous demand for computing resources is handled by centers distributed worldwide, which form part of the LHC computing grid. The consumption of such an important amount of resources demands for an efficient production of simulation and for the early detection of potential errors. In this article we present a new monitoring framework for grid environments, which polls a measure of data quality during job execution. This online monitoring facilitates the early detection of configuration errors (specially in simulation parameters), and may thus contribute to significant savings in computing resources.

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

NASA Technical Reports Server (NTRS)

Liu, Zhong; Heo, Gil

2015-01-01

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

Machine tools error characterization and compensation by on-line measurement of artifact

NASA Astrophysics Data System (ADS)

Wahid Khan, Abdul; Chen, Wuyi; Wu, Lili

2009-11-01

Most manufacturing machine tools are utilized for mass production or batch production with high accuracy at a deterministic manufacturing principle. Volumetric accuracy of machine tools depends on the positional accuracy of the cutting tool, probe or end effector related to the workpiece in the workspace volume. In this research paper, a methodology is presented for volumetric calibration of machine tools by on-line measurement of an artifact or an object of a similar type. The machine tool geometric error characterization was carried out through a standard or an artifact, having similar geometry to the mass production or batch production product. The artifact was measured at an arbitrary position in the volumetric workspace with a calibrated Renishaw touch trigger probe system. Positional errors were stored into a computer for compensation purpose, to further run the manufacturing batch through compensated codes. This methodology was found quite effective to manufacture high precision components with more dimensional accuracy and reliability. Calibration by on-line measurement gives the advantage to improve the manufacturing process by use of deterministic manufacturing principle and found efficient and economical but limited to the workspace or envelop surface of the measured artifact's geometry or the profile.

Metabolic Diet App Suite for inborn errors of amino acid metabolism.

PubMed

Ho, Gloria; Ueda, Keiko; Houben, Roderick F A; Joa, Jeff; Giezen, Alette; Cheng, Barbara; van Karnebeek, Clara D M

2016-03-01

An increasing number of rare inborn errors of metabolism (IEMs) are amenable to targeted metabolic nutrition therapy. Daily adherence is important to attain metabolic control and prevent organ damage. This is challenging however, given the lack of information of disorder specific nutrient content of foods, the limited availability and cost of specialty products as well as difficulties in reliable calculation and tracking of dietary intake and targets. To develop apps for all inborn errors of amino acid metabolism for which the mainstay of treatment is a medical diet, and obtain patient and family feedback throughout the process to incorporate this into subsequent versions. The Metabolic Diet App Suite was created with input from health care professionals as a free, user-friendly, online tool for both mobile devices and desktop computers (http://www.metabolicdietapp.org) for 15 different IEMs. General information is provided for each IEM with links to useful online resources. Nutrient information is based on the MetabolicPro™, a North American food database compiled by the Genetic Metabolic Dietitians International (GMDI) Technology committee. After user registration, a personalized dashboard and management plan including specific nutrient goals are created. Each Diet App has a user-friendly interface and the functions include: nutrient intake counts, adding your own foods and homemade recipes and, managing a daily food diary. Patient and family feedback was overall positive and specific suggestions were used to further improve the App Suite. The Metabolic Diet App Suite aids individuals affected by IEMs to track and plan their meals. Future research should evaluate its impact on patient adherence, metabolic control, quality of life and health-related outcomes. The Suite will be updated and expanded to Apps for other categories of IEMs. Finally, this Suite is a support tool only, and does not replace medical/metabolic nutrition professional advice. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Application of round grating angle measurement composite error amendment in the online measurement accuracy improvement of large diameter

NASA Astrophysics Data System (ADS)

Wang, Biao; Yu, Xiaofen; Li, Qinzhao; Zheng, Yu

2008-10-01

The paper aiming at the influence factor of round grating dividing error, rolling-wheel produce eccentricity and surface shape errors provides an amendment method based on rolling-wheel to get the composite error model which includes all influence factors above, and then corrects the non-circle measurement angle error of the rolling-wheel. We make soft simulation verification and have experiment; the result indicates that the composite error amendment method can improve the diameter measurement accuracy with rolling-wheel theory. It has wide application prospect for the measurement accuracy higher than 5 μm/m.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN.

PubMed

Marques, Luis; Vasconcelos, Verónica; Pedreiras, Paulo; Almeida, Luís

2018-01-11

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN

PubMed Central

Pedreiras, Paulo; Almeida, Luís

2018-01-01

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots. PMID:29324723

Optimised to Fail: Card Readers for Online Banking

NASA Astrophysics Data System (ADS)

Drimer, Saar; Murdoch, Steven J.; Anderson, Ross

The Chip Authentication Programme (CAP) has been introduced by banks in Europe to deal with the soaring losses due to online banking fraud. A handheld reader is used together with the customer’s debit card to generate one-time codes for both login and transaction authentication. The CAP protocol is not public, and was rolled out without any public scrutiny. We reverse engineered the UK variant of card readers and smart cards and here provide the first public description of the protocol. We found numerous weaknesses that are due to design errors such as reusing authentication tokens, overloading data semantics, and failing to ensure freshness of responses. The overall strategic error was excessive optimisation. There are also policy implications. The move from signature to PIN for authorising point-of-sale transactions shifted liability from banks to customers; CAP introduces the same problem for online banking. It may also expose customers to physical harm.

Robust model predictive control for optimal continuous drug administration.

PubMed

Sopasakis, Pantelis; Patrinos, Panagiotis; Sarimveis, Haralambos

2014-10-01

In this paper the model predictive control (MPC) technology is used for tackling the optimal drug administration problem. The important advantage of MPC compared to other control technologies is that it explicitly takes into account the constraints of the system. In particular, for drug treatments of living organisms, MPC can guarantee satisfaction of the minimum toxic concentration (MTC) constraints. A whole-body physiologically-based pharmacokinetic (PBPK) model serves as the dynamic prediction model of the system after it is formulated as a discrete-time state-space model. Only plasma measurements are assumed to be measured on-line. The rest of the states (drug concentrations in other organs and tissues) are estimated in real time by designing an artificial observer. The complete system (observer and MPC controller) is able to drive the drug concentration to the desired levels at the organs of interest, while satisfying the imposed constraints, even in the presence of modelling errors, disturbances and noise. A case study on a PBPK model with 7 compartments, constraints on 5 tissues and a variable drug concentration set-point illustrates the efficiency of the methodology in drug dosing control applications. The proposed methodology is also tested in an uncertain setting and proves successful in presence of modelling errors and inaccurate measurements. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Online and offline awareness deficits: Anosognosia for spatial neglect.

PubMed

Chen, Peii; Toglia, Joan

2018-04-12

Anosognosia for spatial neglect (ASN) can be offline or online. Offline ASN is general unawareness of having experienced spatial deficits. Online ASN is an awareness deficit of underestimating spatial difficulties that likely to occur in an upcoming task (anticipatory ASN) or have just occurred during the task (emergent ASN). We explored the relationships among spatial neglect, offline ASN, anticipatory ASN, and emergent ASN. Research Method/Design: Forty-four survivors of stroke answered questionnaires assessing offline and online self-awareness of spatial problems. The online questionnaire was asked immediately before and after each of 4 tests for spatial neglect, including shape cancellation, address and sentence copying, telephone dialing, and indented paragraph reading. Participants were certain they had difficulties in daily spatial tasks (offline awareness), in the task they were about to perform (anticipatory awareness) and had just performed (emergent awareness). Nonetheless, they consistently overestimated their spatial abilities, indicating ASN. Offline and online ASN appeared independent. Online ASN improved after task execution. Neglect severity was not positively correlated with offline ASN. Greater neglect severity correlated with both greater anticipatory and emergent ASN. Regardless of neglect severity, we found task-specific differences in emergent ASN but not in anticipatory ASN. Individuals with spatial neglect acknowledge their spatial difficulty (certainty of error occurrence) but may not necessarily recognize the extent of their difficulty (accuracy of error estimation). Our findings suggest that offline and online ASN are independent. A potential implication from the study is that familiar and challenging tasks may facilitate emergence of self-awareness. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Online learning and control of attraction basins for the development of sensorimotor control strategies.

PubMed

de Rengervé, Antoine; Andry, Pierre; Gaussier, Philippe

2015-04-01

Imitation and learning from humans require an adequate sensorimotor controller to learn and encode behaviors. We present the Dynamic Muscle Perception-Action(DM-PerAc) model to control a multiple degrees-of-freedom (DOF) robot arm. In the original PerAc model, path-following or place-reaching behaviors correspond to the sensorimotor attractors resulting from the dynamics of learned sensorimotor associations. The DM-PerAc model, inspired by human muscles, permits one to combine impedance-like control with the capability of learning sensorimotor attraction basins. We detail a solution to learn incrementally online the DM-PerAc visuomotor controller. Postural attractors are learned by adapting the muscle activations in the model depending on movement errors. Visuomotor categories merging visual and proprioceptive signals are associated with these muscle activations. Thus, the visual and proprioceptive signals activate the motor action generating an attractor which satisfies both visual and proprioceptive constraints. This visuomotor controller can serve as a basis for imitative behaviors. In addition, the muscle activation patterns can define directions of movement instead of postural attractors. Such patterns can be used in state-action couples to generate trajectories like in the PerAc model. We discuss a possible extension of the DM-PerAc controller by adapting the Fukuyori's controller based on the Langevin's equation. This controller can serve not only to reach attractors which were not explicitly learned, but also to learn the state/action couples to define trajectories.

An on-belt elemental analyser for the cement industry.

PubMed

Lim, C S; Tickner, J R; Sowerby, B D; Abernethy, D A; McEwan, A J; Rainey, S; Stevens, R; Manias, C; Retallack, D

2001-01-01

On-line control of raw mill feed composition is a key factor in the improved control of cement plants. A new and improved on-conveyor belt elemental analyser for cement raw mill feed based on neutron inelastic scatter and capture techniques has been developed and tested successfully in Adelaide Brighton's Birkenhead cement plant on highly segregated material with a depth range of 100 to 180 mm. Dynamic tests in the plant have shown analyser RMS total errors of 0.49, 0.52, 0.38 and 0.23 wt% (on a loss free basis) for CaO, SiO2, Al2O3 and Fe2O3 respectively, when 10-minute counting periods are used.

Student Consistency and Implications for Feedback in Online Assessment Systems

ERIC Educational Resources Information Center

Madhyastha, Tara M.; Tanimoto, Steven

2009-01-01

Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…

Online Psychology: Trial and Error in Course Development

ERIC Educational Resources Information Center

Harman, Marsha J.

2009-01-01

Online courses appear to be the future if colleges and universities choose to increase enrollments with students who need more flexibility in scheduling. The challenge has been to create a course that is rigorous with the limitations to physical presence of the instructor and the parameters inherent in technological delivery. This article relates…

The Clinical Practice Library of Medicine (CPLM): An on-line biomedical computer library. System documentation

NASA Technical Reports Server (NTRS)

Grams, R. R.

1982-01-01

A system designed to access a large range of available medical textbook information in an online interactive fashion is described. A high level query type database manager, INQUIRE, is used. Operating instructions, system flow diagrams, database descriptions, text generation, and error messages are discussed. User information is provided.

Towards New Multiplatform Hybrid Online Laboratory Models

ERIC Educational Resources Information Center

Rodriguez-Gil, Luis; García-Zubia, Javier; Orduña, Pablo; López-de-Ipiña, Diego

2017-01-01

Online laboratories have traditionally been split between virtual labs, with simulated components; and remote labs, with real components. The former tend to provide less realism but to be easily scalable and less expensive to maintain, while the latter are fully real but tend to require a higher maintenance effort and be more error-prone. This…

Forecasting daily streamflow using online sequential extreme learning machines

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.

2016-06-01

While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.

The generalization ability of online SVM classification based on Markov sampling.

PubMed

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

Neural Network-Based Self-Tuning PID Control for Underwater Vehicles

PubMed Central

Hernández-Alvarado, Rodrigo; García-Valdovinos, Luis Govinda; Salgado-Jiménez, Tomás; Gómez-Espinosa, Alfonso; Fonseca-Navarro, Fernando

2016-01-01

For decades, PID (Proportional + Integral + Derivative)-like controllers have been successfully used in academia and industry for many kinds of plants. This is thanks to its simplicity and suitable performance in linear or linearized plants, and under certain conditions, in nonlinear ones. A number of PID controller gains tuning approaches have been proposed in the literature in the last decades; most of them off-line techniques. However, in those cases wherein plants are subject to continuous parametric changes or external disturbances, online gains tuning is a desirable choice. This is the case of modular underwater ROVs (Remotely Operated Vehicles) where parameters (weight, buoyancy, added mass, among others) change according to the tool it is fitted with. In practice, some amount of time is dedicated to tune the PID gains of a ROV. Once the best set of gains has been achieved the ROV is ready to work. However, when the vehicle changes its tool or it is subject to ocean currents, its performance deteriorates since the fixed set of gains is no longer valid for the new conditions. Thus, an online PID gains tuning algorithm should be implemented to overcome this problem. In this paper, an auto-tune PID-like controller based on Neural Networks (NN) is proposed. The NN plays the role of automatically estimating the suitable set of PID gains that achieves stability of the system. The NN adjusts online the controller gains that attain the smaller position tracking error. Simulation results are given considering an underactuated 6 DOF (degrees of freedom) underwater ROV. Real time experiments on an underactuated mini ROV are conducted to show the effectiveness of the proposed scheme. PMID:27608018

Neural Network-Based Self-Tuning PID Control for Underwater Vehicles.

PubMed

Hernández-Alvarado, Rodrigo; García-Valdovinos, Luis Govinda; Salgado-Jiménez, Tomás; Gómez-Espinosa, Alfonso; Fonseca-Navarro, Fernando

2016-09-05

For decades, PID (Proportional + Integral + Derivative)-like controllers have been successfully used in academia and industry for many kinds of plants. This is thanks to its simplicity and suitable performance in linear or linearized plants, and under certain conditions, in nonlinear ones. A number of PID controller gains tuning approaches have been proposed in the literature in the last decades; most of them off-line techniques. However, in those cases wherein plants are subject to continuous parametric changes or external disturbances, online gains tuning is a desirable choice. This is the case of modular underwater ROVs (Remotely Operated Vehicles) where parameters (weight, buoyancy, added mass, among others) change according to the tool it is fitted with. In practice, some amount of time is dedicated to tune the PID gains of a ROV. Once the best set of gains has been achieved the ROV is ready to work. However, when the vehicle changes its tool or it is subject to ocean currents, its performance deteriorates since the fixed set of gains is no longer valid for the new conditions. Thus, an online PID gains tuning algorithm should be implemented to overcome this problem. In this paper, an auto-tune PID-like controller based on Neural Networks (NN) is proposed. The NN plays the role of automatically estimating the suitable set of PID gains that achieves stability of the system. The NN adjusts online the controller gains that attain the smaller position tracking error. Simulation results are given considering an underactuated 6 DOF (degrees of freedom) underwater ROV. Real time experiments on an underactuated mini ROV are conducted to show the effectiveness of the proposed scheme.

An intervention to decrease patient identification band errors in a children's hospital.

PubMed

Hain, Paul D; Joers, B; Rush, M; Slayton, J; Throop, P; Hoagg, S; Allen, L; Grantham, J; Deshpande, J K

2010-06-01

Patient misidentification continues to be a quality and safety issue. There is a paucity of US data describing interventions to reduce identification band error rates. Monroe Carell Jr Children's Hospital at Vanderbilt. Percentage of patients with defective identification bands. Web-based surveys were sent, asking hospital personnel to anonymously identify perceived barriers to reaching zero defects with identification bands. Corrective action plans were created and implemented with ideas from leadership, front-line staff and the online survey. Data from unannounced audits of patient identification bands were plotted on statistical process control charts and shared monthly with staff. All hospital personnel were expected to "stop the line" if there were any patient identification questions. The first audit showed a defect rate of 20.4%. The original mean defect rate was 6.5%. After interventions and education, the new mean defect rate was 2.6%. (a) The initial rate of patient identification band errors in the hospital was higher than expected. (b) The action resulting in most significant improvement was staff awareness of the problem, with clear expectations to immediately stop the line if a patient identification error was present. (c) Staff surveys are an excellent source of suggestions for combating patient identification issues. (d) Continued audit and data collection is necessary for sustainable staff focus and continued improvement. (e) Statistical process control charts are both an effective method to track results and an easily understood tool for sharing data with staff.

A hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy.

PubMed

Lei, Yu; Wu, Qiuwen

2010-04-21

Offline adaptive radiotherapy (ART) has been used to effectively correct and compensate for prostate motion and reduce the required margin. The efficacy depends on the characteristics of the patient setup error and interfraction motion through the whole treatment; specifically, systematic errors are corrected and random errors are compensated for through the margins. In online image-guided radiation therapy (IGRT) of prostate cancer, the translational setup error and inter-fractional prostate motion are corrected through pre-treatment imaging and couch correction at each fraction. However, the rotation and deformation of the target are not corrected and only accounted for with margins in treatment planning. The purpose of this study was to investigate whether the offline ART strategy is necessary for an online IGRT protocol and to evaluate the benefit of the hybrid strategy. First, to investigate the rationale of the hybrid strategy, 592 cone-beam-computed tomography (CBCT) images taken before and after each fraction for an online IGRT protocol from 16 patients were analyzed. Specifically, the characteristics of prostate rotation were analyzed. It was found that there exist systematic inter-fractional prostate rotations, and they are patient specific. These rotations, if not corrected, are persistent through the treatment fraction, and rotations detected in early fractions are representative of those in later fractions. These findings suggest that the offline adaptive replanning strategy is beneficial to the online IGRT protocol with further margin reductions. Second, to quantitatively evaluate the benefit of the hybrid strategy, 412 repeated helical CT scans from 25 patients during the course of treatment were included in the replanning study. Both low-risk patients (LRP, clinical target volume, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles) were included in the simulation. The contours of prostate and seminal vesicles were delineated on each CT. The benefit of margin reduction to compensate for both rotation and deformation in the hybrid strategy was evaluated geometrically. With the hybrid strategy, the planning margins can be reduced by 1.4 mm for LRP, and 2.0 mm for IRP, compared with the standard online IGRT only, to maintain the same 99% target volume coverage. The average relative reduction in planning target volume (PTV) based on the internal target volume (ITV) from PTV based on CTV is 19% for LRP, and 27% for IRP.

Online 3D EPID-based dose verification: Proof of concept.

PubMed

Spreeuw, Hanno; Rozendaal, Roel; Olaciregui-Ruiz, Igor; González, Patrick; Mans, Anton; Mijnheer, Ben; van Herk, Marcel

2016-07-01

Delivery errors during radiotherapy may lead to medical harm and reduced life expectancy for patients. Such serious incidents can be avoided by performing dose verification online, i.e., while the patient is being irradiated, creating the possibility of halting the linac in case of a large overdosage or underdosage. The offline EPID-based 3D in vivo dosimetry system clinically employed at our institute is in principle suited for online treatment verification, provided the system is able to complete 3D dose reconstruction and verification within 420 ms, the present acquisition time of a single EPID frame. It is the aim of this study to show that our EPID-based dosimetry system can be made fast enough to achieve online 3D in vivo dose verification. The current dose verification system was sped up in two ways. First, a new software package was developed to perform all computations that are not dependent on portal image acquisition separately, thus removing the need for doing these calculations in real time. Second, the 3D dose reconstruction algorithm was sped up via a new, multithreaded implementation. Dose verification was implemented by comparing planned with reconstructed 3D dose distributions delivered to two regions in a patient: the target volume and the nontarget volume receiving at least 10 cGy. In both volumes, the mean dose is compared, while in the nontarget volume, the near-maximum dose (D2) is compared as well. The real-time dosimetry system was tested by irradiating an anthropomorphic phantom with three VMAT plans: a 6 MV head-and-neck treatment plan, a 10 MV rectum treatment plan, and a 10 MV prostate treatment plan. In all plans, two types of serious delivery errors were introduced. The functionality of automatically halting the linac was also implemented and tested. The precomputation time per treatment was ∼180 s/treatment arc, depending on gantry angle resolution. The complete processing of a single portal frame, including dose verification, took 266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5-10 s irradiation time. A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

Assessing the Online Social Environment for Surveillance of Obesity Prevalence

PubMed Central

Chunara, Rumi; Bouton, Lindsay; Ayers, John W.; Brownstein, John S.

2013-01-01

Background Understanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data. Purpose This article explores the relationship between online social environment via web-based social networks and population obesity prevalence. Methods We performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and/or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook. Results Higher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0% (95% Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and/or overweight people across USA metros and 7.2% (95% CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and/or overweight people of 3.9% (95% CI: 3.7 to 4.0) (USA) and 27.5% (95% CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set. Conclusions Activity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions. PMID:23637820

VizieR Online Data Catalog: R136 JKs photometry from VLT/SPHERE EAO (Khorrami+, 2017)

NASA Astrophysics Data System (ADS)

Khorrami, Z.; Vakili, F.; Lanz, T.; Langlois, M.; Lagadec, E.; Meyer, M. R.; Robbe-Dubois, S.; Abe, L.; Avenhaus, H.; Beuzit, J. L.; Gratton, R.; Mouillet, D.; Origne, A.; Petit, C.; Ramos, J.

2017-03-01

The SPHERE/IRDIS catalog of the common sources between J and Ks-band data on R136. The ID, Xpix and Ypix are the identification and pixel position in the IRDIS K and J image. σK and σJ are the total error (combination of PSF-fitting error, residual errors and the calibration error) in Ks and J images. CK and CJ are the Correlation coefficients between the input PSF and the star, in Ks and J data. (1 data file).

Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

NASA Astrophysics Data System (ADS)

Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

2018-02-01

This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

Convergence and objective functions of some fault/noise-injection-based online learning algorithms for RBF networks.

PubMed

Ho, Kevin I-J; Leung, Chi-Sing; Sum, John

2010-06-01

In the last two decades, many online fault/noise injection algorithms have been developed to attain a fault tolerant neural network. However, not much theoretical works related to their convergence and objective functions have been reported. This paper studies six common fault/noise-injection-based online learning algorithms for radial basis function (RBF) networks, namely 1) injecting additive input noise, 2) injecting additive/multiplicative weight noise, 3) injecting multiplicative node noise, 4) injecting multiweight fault (random disconnection of weights), 5) injecting multinode fault during training, and 6) weight decay with injecting multinode fault. Based on the Gladyshev theorem, we show that the convergence of these six online algorithms is almost sure. Moreover, their true objective functions being minimized are derived. For injecting additive input noise during training, the objective function is identical to that of the Tikhonov regularizer approach. For injecting additive/multiplicative weight noise during training, the objective function is the simple mean square training error. Thus, injecting additive/multiplicative weight noise during training cannot improve the fault tolerance of an RBF network. Similar to injective additive input noise, the objective functions of other fault/noise-injection-based online algorithms contain a mean square error term and a specialized regularization term.

Correction to Cantor et al. (2005)

ERIC Educational Resources Information Center

Cantor, James M.; Blanchard, Ray; Robichaud, Lori K.; Christensen, Bruce K.

2005-01-01

This paper reports an error in the original article by James M. Cantor, Ray Blanchard, Lori K. Robichaud, and Bruce K. Christensen ("Psychological Bulletin," 2005, Vol. 131, No. 4, pp. 555-568). As a result of an editorial error the article listed the link to online supplemental data incorrectly. The correct URL is provided here. (The following…

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Adaptive Trajectory Tracking of Nonholonomic Mobile Robots Using Vision-Based Position and Velocity Estimation.

PubMed

Li, Luyang; Liu, Yun-Hui; Jiang, Tianjiao; Wang, Kai; Fang, Mu

2018-02-01

Despite tremendous efforts made for years, trajectory tracking control (TC) of a nonholonomic mobile robot (NMR) without global positioning system remains an open problem. The major reason is the difficulty to localize the robot by using its onboard sensors only. In this paper, a newly designed adaptive trajectory TC method is proposed for the NMR without its position, orientation, and velocity measurements. The controller is designed on the basis of a novel algorithm to estimate position and velocity of the robot online from visual feedback of an omnidirectional camera. It is theoretically proved that the proposed algorithm yields the TC errors to asymptotically converge to zero. Real-world experiments are conducted on a wheeled NMR to validate the feasibility of the control system.

Improved setup and positioning accuracy using a three‐point customized cushion/mask/bite‐block immobilization system for stereotactic reirradiation of head and neck cancer

PubMed Central

Wang, He; Wang, Congjun; Tung, Samuel; Dimmitt, Andrew Wilson; Wong, Pei Fong; Edson, Mark A.; Garden, Adam S.; Rosenthal, David I.; Fuller, Clifton D.; Gunn, Gary B.; Takiar, Vinita; Wang, Xin A.; Luo, Dershan; Yang, James N.; Wong, Jennifer

2016-01-01

The purpose of this study was to investigate the setup and positioning uncertainty of a custom cushion/mask/bite‐block (CMB) immobilization system and determine PTV margin for image‐guided head and neck stereotactic ablative radiotherapy (HN‐SABR). We analyzed 105 treatment sessions among 21 patients treated with HN‐SABR for recurrent head and neck cancers using a custom CMB immobilization system. Initial patient setup was performed using the ExacTrac infrared (IR) tracking system and initial setup errors were based on comparison of ExacTrac IR tracking system to corrected online ExacTrac X‐rays images registered to treatment plans. Residual setup errors were determined using repeat verification X‐ray. The online ExacTrac corrections were compared to cone‐beam CT (CBCT) before treatment to assess agreement. Intrafractional positioning errors were determined using prebeam X‐rays. The systematic and random errors were analyzed. The initial translational setup errors were −0.8±1.3 mm, −0.8±1.6 mm, and 0.3±1.9 mm in AP, CC, and LR directions, respectively, with a three‐dimensional (3D) vector of 2.7±1.4 mm. The initial rotational errors were up to 2.4° if 6D couch is not available. CBCT agreed with ExacTrac X‐ray images to within 2 mm and 2.5°. The intrafractional uncertainties were 0.1±0.6 mm, 0.1±0.6 mm, and 0.2±0.5 mm in AP, CC, and LR directions, respectively, and 0.0∘±0.5°, 0.0∘±0.6°, and −0.1∘±0.4∘ in yaw, roll, and pitch direction, respectively. The translational vector was 0.9±0.6 mm. The calculated PTV margins mPTV(90,95) were within 1.6 mm when using image guidance for online setup correction. The use of image guidance for online setup correction, in combination with our customized CMB device, highly restricted target motion during treatments and provided robust immobilization to ensure minimum dose of 95% to target volume with 2.0 mm PTV margin for HN‐SABR. PACS number(s): 87.55.ne PMID:27167275

Principal Candidates Create Decision-Making Simulations to Prepare for the JOB

ERIC Educational Resources Information Center

Staub, Nancy A.; Bravender, Marlena

2014-01-01

Online simulations offer opportunities for trial and error decision-making. What better tool for a principal than to make decisions when the consequences will not have real-world ramifications. In this study, two groups of graduate students in a principal preparation program taking the same course in the same semester use online simulations…

Understanding statements now a virtual cinch.

PubMed

Weber, Danielle B; Talaga, John

2005-04-01

With a click of the mouse, some patients are accessing and paying their hospital bills online. Novant Health revamped its patient billing process so it's easier to understand and use. Developing a clear, concise billing statement and then implementing an online bill presentment and payment system resulted in improved customer relations, fewer payment processing errors, and faster receipt of payment.

Comparing Elicited Imitation and Word Monitoring as Measures of Implicit Knowledge

ERIC Educational Resources Information Center

Suzuki, Yuichi; DeKeyser, Robert

2015-01-01

The present study challenges the validity of elicited imitation (EI) as a measure for implicit knowledge, investigating to what extent online error detection and subsequent sentence repetition draw on implicit knowledge. To assess online detection during listening, a word monitoring component was built into an EI task. Advanced-level Japanese L2…

Help! Active Student Learning and Error Remediation in an Online Calculus e-Help Community

ERIC Educational Resources Information Center

van de Sande, Carla; Leinhardt, Gaea

2007-01-01

Free, open, online homework help sites appear to be extremely popular and exist for many school subjects. Students can anonymously post problems at their convenience and receive responses from forum members. This mode of tutoring may be especially critical for school subjects such as calculus that are intrinsically challenging and have high…

Increasing Students' Awareness of Their Behavior in Online Learning Environments with Visualizations and Achievement Badges

ERIC Educational Resources Information Center

Auvinen, Tapio; Hakulinen, Lasse; Malmi, Lauri

2015-01-01

In online learning environments where automatic assessment is used, students often resort to harmful study practices such as procrastination and trial-and-error. In this paper, we study two teaching interventions that were designed to address these issues in a university-level computer science course. In the first intervention, we used achievement…

Telerobotic control of a mobile coordinated robotic server, executive summary

NASA Technical Reports Server (NTRS)

Lee, Gordon

1993-01-01

This interim report continues with the research effort on advanced adaptive controls for space robotics systems. In particular, previous results developed by the principle investigator and his research team centered around fuzzy logic control (FLC) in which the lack of knowledge of the robotic system as well as the uncertainties of the environment are compensated for by a rule base structure which interacts with varying degrees of belief of control action using system measurements. An on-line adaptive algorithm was developed using a single parameter tuning scheme. In the effort presented, the methodology is further developed to include on-line scaling factor tuning and self-learning control as well as extended to the multi-input, multi-output (MIMO) case. Classical fuzzy logic control requires tuning input scale factors off-line through trial and error techniques. This is time-consuming and cannot adapt to new changes in the process. The new adaptive FLC includes a self-tuning scheme for choosing the scaling factors on-line. Further the rule base in classical FLC is usually produced by soliciting knowledge from human operators as to what is good control action for given circumstances. This usually requires full knowledge and experience of the process and operating conditions, which limits applicability. A self-learning scheme is developed which adaptively forms the rule base with very limited knowledge of the process. Finally, a MIMO method is presented employing optimization techniques. This is required for application to space robotics in which several degrees-of-freedom links are commonly used. Simulation examples are presented for terminal control - typical of robotic problems in which a desired terminal point is to be reached for each link. Future activities will be to implement the MIMO adaptive FLC on an INTEL microcontroller-based circuit and to test the algorithm on a robotic system at the Mars Mission Research Center at North Carolina State University.

Finite-horizon differential games for missile-target interception system using adaptive dynamic programming with input constraints

NASA Astrophysics Data System (ADS)

Sun, Jingliang; Liu, Chunsheng

2018-01-01

In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.

Investigating Perceptual Biases, Data Reliability, and Data Discovery in a Methodology for Collecting Speech Errors From Audio Recordings.

PubMed

Alderete, John; Davies, Monica

2018-04-01

This work describes a methodology of collecting speech errors from audio recordings and investigates how some of its assumptions affect data quality and composition. Speech errors of all types (sound, lexical, syntactic, etc.) were collected by eight data collectors from audio recordings of unscripted English speech. Analysis of these errors showed that: (i) different listeners find different errors in the same audio recordings, but (ii) the frequencies of error patterns are similar across listeners; (iii) errors collected "online" using on the spot observational techniques are more likely to be affected by perceptual biases than "offline" errors collected from audio recordings; and (iv) datasets built from audio recordings can be explored and extended in a number of ways that traditional corpus studies cannot be.

Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety.

PubMed

Kang, Hao-Bo; Wang, Jian-Hui

2013-11-01

This paper studies an adaptive control strategy for a class of 5 DOF upper-limb exoskeleton robot with a special safety consideration. The safety requirement plays a critical role in the clinical treatment when assisting patients with shoulder, elbow and wrist joint movements. With the objective of assuring the tracking performance of the pre-specified operations, the proposed adaptive controller is firstly designed to be robust to the model uncertainties. To further improve the safety and fault-tolerance in the presence of unknown large parameter variances or even actuator faults, the adaptive controller is on-line updated according to the information provided by an adaptive observer without additional sensors. An output tracking performance is well achieved with a tunable error bound. The experimental example also verifies the effectiveness of the proposed control scheme. © 2013 ISA. Published by ISA. All rights reserved.

Recurrent neural network control for LCC-resonant ultrasonic motor drive.

PubMed

Lin, F J; Wai, R J; Hong, C M

2000-01-01

A newly designed driving circuit for the traveling wave-type ultrasonic motor (USM), which consists of a push-pull DC-DC power converter and a two-phase voltage source inverter using one inductance and two capacitances (LCC) resonant technique, is presented in this study. Moreover, because the dynamic characteristics of the USM are difficult to obtain and the motor parameters are time varying, a recurrent neural network (RNN) controller is proposed to control the USM drive system. In the proposed controller, the dynamic backpropagation algorithm is adopted to train the RNN on-line using the proposed delta adaptation law. Furthermore, to guarantee the convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates for the training of the RNN. Finally, the effectiveness of the RNN-controlled USM drive system is demonstrated by some experimental results.

A Bayesian Measurment Error Model for Misaligned Radiographic Data

DOE PAGES

Lennox, Kristin P.; Glascoe, Lee G.

2013-09-06

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error inmore » addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.« less

Adaptive critic autopilot design of bank-to-turn missiles using fuzzy basis function networks.

PubMed

Lin, Chuan-Kai

2005-04-01

A new adaptive critic autopilot design for bank-to-turn missiles is presented. In this paper, the architecture of adaptive critic learning scheme contains a fuzzy-basis-function-network based associative search element (ASE), which is employed to approximate nonlinear and complex functions of bank-to-turn missiles, and an adaptive critic element (ACE) generating the reinforcement signal to tune the associative search element. In the design of the adaptive critic autopilot, the control law receives signals from a fixed gain controller, an ASE and an adaptive robust element, which can eliminate approximation errors and disturbances. Traditional adaptive critic reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment, however, the proposed tuning algorithm can significantly shorten the learning time by online tuning all parameters of fuzzy basis functions and weights of ASE and ACE. Moreover, the weight updating law derived from the Lyapunov stability theory is capable of guaranteeing both tracking performance and stability. Computer simulation results confirm the effectiveness of the proposed adaptive critic autopilot.

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

2014-07-01

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.

Multiple Motor Learning Strategies in Visuomotor Rotation

PubMed Central

Saijo, Naoki; Gomi, Hiroaki

2010-01-01

Background When exposed to a continuous directional discrepancy between movements of a visible hand cursor and the actual hand (visuomotor rotation), subjects adapt their reaching movements so that the cursor is brought to the target. Abrupt removal of the discrepancy after training induces reaching error in the direction opposite to the original discrepancy, which is called an aftereffect. Previous studies have shown that training with gradually increasing visuomotor rotation results in a larger aftereffect than with a suddenly increasing one. Although the aftereffect difference implies a difference in the learning process, it is still unclear whether the learned visuomotor transformations are qualitatively different between the training conditions. Methodology/Principal Findings We examined the qualitative changes in the visuomotor transformation after the learning of the sudden and gradual visuomotor rotations. The learning of the sudden rotation led to a significant increase of the reaction time for arm movement initiation and then the reaching error decreased, indicating that the learning is associated with an increase of computational load in motor preparation (planning). In contrast, the learning of the gradual rotation did not change the reaction time but resulted in an increase of the gain of feedback control, suggesting that the online adjustment of the reaching contributes to the learning of the gradual rotation. When the online cursor feedback was eliminated during the learning of the gradual rotation, the reaction time increased, indicating that additional computations are involved in the learning of the gradual rotation. Conclusions/Significance The results suggest that the change in the motor planning and online feedback adjustment of the movement are involved in the learning of the visuomotor rotation. The contributions of those computations to the learning are flexibly modulated according to the visual environment. Such multiple learning strategies would be required for reaching adaptation within a short training period. PMID:20195373

Competitive action video game players display rightward error bias during on-line video game play.

PubMed

Roebuck, Andrew J; Dubnyk, Aurora J B; Cochran, David; Mandryk, Regan L; Howland, John G; Harms, Victoria

2017-09-12

Research in asymmetrical visuospatial attention has identified a leftward bias in the general population across a variety of measures including visual attention and line-bisection tasks. In addition, increases in rightward collisions, or bumping, during visuospatial navigation tasks have been demonstrated in real world and virtual environments. However, little research has investigated these biases beyond the laboratory. The present study uses a semi-naturalistic approach and the online video game streaming service Twitch to examine navigational errors and assaults as skilled action video game players (n = 60) compete in Counter Strike: Global Offensive. This study showed a significant rightward bias in both fatal assaults and navigational errors. Analysis using the in-game ranking system as a measure of skill failed to show a relationship between bias and skill. These results suggest that a leftward visuospatial bias may exist in skilled players during online video game play. However, the present study was unable to account for some factors such as environmental symmetry and player handedness. In conclusion, video game streaming is a promising method for behavioural research in the future, however further study is required before one can determine whether these results are an artefact of the method applied, or representative of a genuine rightward bias.

Persistent aerial video registration and fast multi-view mosaicing.

PubMed

Molina, Edgardo; Zhu, Zhigang

2014-05-01

Capturing aerial imagery at high resolutions often leads to very low frame rate video streams, well under full motion video standards, due to bandwidth, storage, and cost constraints. Low frame rates make registration difficult when an aircraft is moving at high speeds or when global positioning system (GPS) contains large errors or it fails. We present a method that takes advantage of persistent cyclic video data collections to perform an online registration with drift correction. We split the persistent aerial imagery collection into individual cycles of the scene, identify and correct the registration errors on the first cycle in a batch operation, and then use the corrected base cycle as a reference pass to register and correct subsequent passes online. A set of multi-view panoramic mosaics is then constructed for each aerial pass for representation, presentation and exploitation of the 3D dynamic scene. These sets of mosaics are all in alignment to the reference cycle allowing their direct use in change detection, tracking, and 3D reconstruction/visualization algorithms. Stereo viewing with adaptive baselines and varying view angles is realized by choosing a pair of mosaics from a set of multi-view mosaics. Further, the mosaics for the second pass and later can be generated and visualized online as their is no further batch error correction.

Patients' online access to their electronic health records and linked online services: a systematic review in primary care.

PubMed

Mold, Freda; de Lusignan, Simon; Sheikh, Aziz; Majeed, Azeem; Wyatt, Jeremy C; Quinn, Tom; Cavill, Mary; Franco, Christina; Chauhan, Umesh; Blakey, Hannah; Kataria, Neha; Arvanitis, Theodoros N; Ellis, Beverley

2015-03-01

Online access to medical records by patients can potentially enhance provision of patient-centred care and improve satisfaction. However, online access and services may also prove to be an additional burden for the healthcare provider. To assess the impact of providing patients with access to their general practice electronic health records (EHR) and other EHR-linked online services on the provision, quality, and safety of health care. A systematic review was conducted that focused on all studies about online record access and transactional services in primary care. Data sources included MEDLINE, Embase, CINAHL, Cochrane Library, EPOC, DARE, King's Fund, Nuffield Health, PsycINFO, OpenGrey (1999-2012). The literature was independently screened against detailed inclusion and exclusion criteria; independent dual data extraction was conducted, the risk of bias (RoB) assessed, and a narrative synthesis of the evidence conducted. A total of 176 studies were identified, 17 of which were randomised controlled trials, cohort, or cluster studies. Patients reported improved satisfaction with online access and services compared with standard provision, improved self-care, and better communication and engagement with clinicians. Safety improvements were patient-led through identifying medication errors and facilitating more use of preventive services. Provision of online record access and services resulted in a moderate increase of e-mail, no change on telephone contact, but there were variable effects on face-to-face contact. However, other tasks were necessary to sustain these services, which impacted on clinician time. There were no reports of harm or breaches in privacy. While the RoB scores suggest many of the studies were of low quality, patients using online services reported increased convenience and satisfaction. These services positively impacted on patient safety, although there were variations of record access and use by specific ethnic and socioeconomic groups. Professional concerns about privacy were unrealised and those about workload were only partly so. © British Journal of General Practice 2015.

Patients’ online access to their electronic health records and linked online services: a systematic review in primary care

PubMed Central

Mold, Freda; de Lusignan, Simon; Sheikh, Aziz; Majeed, Azeem; Wyatt, Jeremy C; Quinn, Tom; Cavill, Mary; Franco, Christina; Chauhan, Umesh; Blakey, Hannah; Kataria, Neha; Arvanitis, Theodoros N; Ellis, Beverley

2015-01-01

Background Online access to medical records by patients can potentially enhance provision of patient-centred care and improve satisfaction. However, online access and services may also prove to be an additional burden for the healthcare provider. Aim To assess the impact of providing patients with access to their general practice electronic health records (EHR) and other EHR-linked online services on the provision, quality, and safety of health care. Design and setting A systematic review was conducted that focused on all studies about online record access and transactional services in primary care. Method Data sources included MEDLINE, Embase, CINAHL, Cochrane Library, EPOC, DARE, King’s Fund, Nuffield Health, PsycINFO, OpenGrey (1999–2012). The literature was independently screened against detailed inclusion and exclusion criteria; independent dual data extraction was conducted, the risk of bias (RoB) assessed, and a narrative synthesis of the evidence conducted. Results A total of 176 studies were identified, 17 of which were randomised controlled trials, cohort, or cluster studies. Patients reported improved satisfaction with online access and services compared with standard provision, improved self-care, and better communication and engagement with clinicians. Safety improvements were patient-led through identifying medication errors and facilitating more use of preventive services. Provision of online record access and services resulted in a moderate increase of e-mail, no change on telephone contact, but there were variable effects on face-to-face contact. However, other tasks were necessary to sustain these services, which impacted on clinician time. There were no reports of harm or breaches in privacy. Conclusion While the RoB scores suggest many of the studies were of low quality, patients using online services reported increased convenience and satisfaction. These services positively impacted on patient safety, although there were variations of record access and use by specific ethnic and socioeconomic groups. Professional concerns about privacy were unrealised and those about workload were only partly so. PMID:25733435

Experimental investigation of false positive errors in auditory species occurrence surveys

USGS Publications Warehouse

Miller, David A.W.; Weir, Linda A.; McClintock, Brett T.; Grant, Evan H. Campbell; Bailey, Larissa L.; Simons, Theodore R.

2012-01-01

False positive errors are a significant component of many ecological data sets, which in combination with false negative errors, can lead to severe biases in conclusions about ecological systems. We present results of a field experiment where observers recorded observations for known combinations of electronically broadcast calling anurans under conditions mimicking field surveys to determine species occurrence. Our objectives were to characterize false positive error probabilities for auditory methods based on a large number of observers, to determine if targeted instruction could be used to reduce false positive error rates, and to establish useful predictors of among-observer and among-species differences in error rates. We recruited 31 observers, ranging in abilities from novice to expert, that recorded detections for 12 species during 180 calling trials (66,960 total observations). All observers made multiple false positive errors and on average 8.1% of recorded detections in the experiment were false positive errors. Additional instruction had only minor effects on error rates. After instruction, false positive error probabilities decreased by 16% for treatment individuals compared to controls with broad confidence interval overlap of 0 (95% CI: -46 to 30%). This coincided with an increase in false negative errors due to the treatment (26%; -3 to 61%). Differences among observers in false positive and in false negative error rates were best predicted by scores from an online test and a self-assessment of observer ability completed prior to the field experiment. In contrast, years of experience conducting call surveys was a weak predictor of error rates. False positive errors were also more common for species that were played more frequently, but were not related to the dominant spectral frequency of the call. Our results corroborate other work that demonstrates false positives are a significant component of species occurrence data collected by auditory methods. Instructing observers to only report detections they are completely certain are correct is not sufficient to eliminate errors. As a result, analytical methods that account for false positive errors will be needed, and independent testing of observer ability is a useful predictor for among-observer variation in observation error rates.

Medial prefrontal cortex and the adaptive regulation of reinforcement learning parameters.

PubMed

Khamassi, Mehdi; Enel, Pierre; Dominey, Peter Ford; Procyk, Emmanuel

2013-01-01

Converging evidence suggest that the medial prefrontal cortex (MPFC) is involved in feedback categorization, performance monitoring, and task monitoring, and may contribute to the online regulation of reinforcement learning (RL) parameters that would affect decision-making processes in the lateral prefrontal cortex (LPFC). Previous neurophysiological experiments have shown MPFC activities encoding error likelihood, uncertainty, reward volatility, as well as neural responses categorizing different types of feedback, for instance, distinguishing between choice errors and execution errors. Rushworth and colleagues have proposed that the involvement of MPFC in tracking the volatility of the task could contribute to the regulation of one of RL parameters called the learning rate. We extend this hypothesis by proposing that MPFC could contribute to the regulation of other RL parameters such as the exploration rate and default action values in case of task shifts. Here, we analyze the sensitivity to RL parameters of behavioral performance in two monkey decision-making tasks, one with a deterministic reward schedule and the other with a stochastic one. We show that there exist optimal parameter values specific to each of these tasks, that need to be found for optimal performance and that are usually hand-tuned in computational models. In contrast, automatic online regulation of these parameters using some heuristics can help producing a good, although non-optimal, behavioral performance in each task. We finally describe our computational model of MPFC-LPFC interaction used for online regulation of the exploration rate and its application to a human-robot interaction scenario. There, unexpected uncertainties are produced by the human introducing cued task changes or by cheating. The model enables the robot to autonomously learn to reset exploration in response to such uncertain cues and events. The combined results provide concrete evidence specifying how prefrontal cortical subregions may cooperate to regulate RL parameters. It also shows how such neurophysiologically inspired mechanisms can control advanced robots in the real world. Finally, the model's learning mechanisms that were challenged in the last robotic scenario provide testable predictions on the way monkeys may learn the structure of the task during the pretraining phase of the previous laboratory experiments. Copyright © 2013 Elsevier B.V. All rights reserved.

Detection and control of combustion instability based on the concept of dynamical system theory.

PubMed

Gotoda, Hiroshi; Shinoda, Yuta; Kobayashi, Masaki; Okuno, Yuta; Tachibana, Shigeru

2014-02-01

We propose an online method of detecting combustion instability based on the concept of dynamical system theory, including the characterization of the dynamic behavior of combustion instability. As an important case study relevant to combustion instability encountered in fundamental and practical combustion systems, we deal with the combustion dynamics close to lean blowout (LBO) in a premixed gas-turbine model combustor. The relatively regular pressure fluctuations generated by thermoacoustic oscillations transit to low-dimensional intermittent chaos owing to the intermittent appearance of burst with decreasing equivalence ratio. The translation error, which is characterized by quantifying the degree of parallelism of trajectories in the phase space, can be used as a control variable to prevent LBO.

Detection and control of combustion instability based on the concept of dynamical system theory

NASA Astrophysics Data System (ADS)

Gotoda, Hiroshi; Shinoda, Yuta; Kobayashi, Masaki; Okuno, Yuta; Tachibana, Shigeru

2014-02-01

We propose an online method of detecting combustion instability based on the concept of dynamical system theory, including the characterization of the dynamic behavior of combustion instability. As an important case study relevant to combustion instability encountered in fundamental and practical combustion systems, we deal with the combustion dynamics close to lean blowout (LBO) in a premixed gas-turbine model combustor. The relatively regular pressure fluctuations generated by thermoacoustic oscillations transit to low-dimensional intermittent chaos owing to the intermittent appearance of burst with decreasing equivalence ratio. The translation error, which is characterized by quantifying the degree of parallelism of trajectories in the phase space, can be used as a control variable to prevent LBO.

Erratum to "Combustion oscillation study in a kerosene fueled rocket-based combined-cycle engine combustor" [Acta Astronaut. 129 (2016) 260-270

NASA Astrophysics Data System (ADS)

Huang, Zhi-Wei; He, Guo-Qiang; Qin, Fei; Xue, Rui; Wei, Xiang-Geng; Shi, Lei

2017-03-01

The publisher regrets that in the above article we found that Table 1 is present online, in the html version in ScienceDirect, but has been omitted in error from the final version of the PDF online and in the print version. The table can be found below:

Online benefits solutions--a new trend in managing employee benefits programs.

PubMed

Ala, Mohammad; Brunaczki, Bernadette

2003-01-01

This article focuses on the array of online benefits solutions offered by technology companies and reports the benefits to both employers and employees. Some of the benefits include reduced paperwork, reduced errors, and reduced administration costs. Companies that can deliver these benefits will be in great demand to help manage benefits programs and streamline the administrative processes.

Time-critical Database Condition Data Handling in the CMS Experiment During the First Data Taking Period

NASA Astrophysics Data System (ADS)

Cavallari, Francesca; de Gruttola, Michele; Di Guida, Salvatore; Govi, Giacomo; Innocente, Vincenzo; Pfeiffer, Andreas; Pierro, Antonio

2011-12-01

Automatic, synchronous and reliable population of the condition databases is critical for the correct operation of the online selection as well as of the offline reconstruction and analysis of data. In this complex infrastructure, monitoring and fast detection of errors is a very challenging task. In this paper, we describe the CMS experiment system to process and populate the Condition Databases and make condition data promptly available both online for the high-level trigger and offline for reconstruction. The data are automatically collected using centralized jobs or are "dropped" by the users in dedicated services (offline and online drop-box), which synchronize them and take care of writing them into the online database. Then they are automatically streamed to the offline database, and thus are immediately accessible offline worldwide. The condition data are managed by different users using a wide range of applications.In normal operation the database monitor is used to provide simple timing information and the history of all transactions for all database accounts, and in the case of faults it is used to return simple error messages and more complete debugging information.

Disparity between online and offline tests in accelerated aging tests of LED lamps under electric stress.

PubMed

Wang, Yao; Jing, Lei; Ke, Hong-Liang; Hao, Jian; Gao, Qun; Wang, Xiao-Xun; Sun, Qiang; Xu, Zhi-Jun

2016-09-20

The accelerated aging tests under electric stress for one type of LED lamp are conducted, and the differences between online and offline tests of the degradation of luminous flux are studied in this paper. The transformation of the two test modes is achieved with an adjustable AC voltage stabilized power source. Experimental results show that the exponential fitting of the luminous flux degradation in online tests possesses a higher fitting degree for most lamps, and the degradation rate of the luminous flux by online tests is always lower than that by offline tests. Bayes estimation and Weibull distribution are used to calculate the failure probabilities under the accelerated voltages, and then the reliability of the lamps under rated voltage of 220 V is estimated by use of the inverse power law model. Results show that the relative error of the lifetime estimation by offline tests increases as the failure probability decreases, and it cannot be neglected when the failure probability is less than 1%. The relative errors of lifetime estimation are 7.9%, 5.8%, 4.2%, and 3.5%, at the failure probabilities of 0.1%, 1%, 5%, and 10%, respectively.

Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

PubMed

Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

2006-04-01

This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control system. Performance of the control system is successfully tested by performing several six-degrees-of-freedom nonlinear simulations.

Online Coregularization for Multiview Semisupervised Learning

PubMed Central

Li, Guohui; Huang, Kuihua

2013-01-01

We propose a novel online coregularization framework for multiview semisupervised learning based on the notion of duality in constrained optimization. Using the weak duality theorem, we reduce the online coregularization to the task of increasing the dual function. We demonstrate that the existing online coregularization algorithms in previous work can be viewed as an approximation of our dual ascending process using gradient ascent. New algorithms are derived based on the idea of ascending the dual function more aggressively. For practical purpose, we also propose two sparse approximation approaches for kernel representation to reduce the computational complexity. Experiments show that our derived online coregularization algorithms achieve risk and accuracy comparable to offline algorithms while consuming less time and memory. Specially, our online coregularization algorithms are able to deal with concept drift and maintain a much smaller error rate. This paper paves a way to the design and analysis of online coregularization algorithms. PMID:24194680

Managing the Pre- and Post-analytical Phases of the Total Testing Process

PubMed Central

2012-01-01

For many years, the clinical laboratory's focus on analytical quality has resulted in an error rate of 4-5 sigma, which surpasses most other areas in healthcare. However, greater appreciation of the prevalence of errors in the pre- and post-analytical phases and their potential for patient harm has led to increasing requirements for laboratories to take greater responsibility for activities outside their immediate control. Accreditation bodies such as the Joint Commission International (JCI) and the College of American Pathologists (CAP) now require clear and effective procedures for patient/sample identification and communication of critical results. There are a variety of free on-line resources available to aid in managing the extra-analytical phase and the recent publication of quality indicators and proposed performance levels by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) working group on laboratory errors and patient safety provides particularly useful benchmarking data. Managing the extra-laboratory phase of the total testing cycle is the next challenge for laboratory medicine. By building on its existing quality management expertise, quantitative scientific background and familiarity with information technology, the clinical laboratory is well suited to play a greater role in reducing errors and improving patient safety outside the confines of the laboratory. PMID:22259773

Control control control: a reassessment and comparison of GenBank and chromatogram mtDNA sequence variation in Baltic grey seals (Halichoerus grypus).

PubMed

Fietz, Katharina; Graves, Jeff A; Olsen, Morten Tange

2013-01-01

Genetic data can provide a powerful tool for those interested in the biology, management and conservation of wildlife, but also lead to erroneous conclusions if appropriate controls are not taken at all steps of the analytical process. This particularly applies to data deposited in public repositories such as GenBank, whose utility relies heavily on the assumption of high data quality. Here we report on an in-depth reassessment and comparison of GenBank and chromatogram mtDNA sequence data generated in a previous study of Baltic grey seals. By re-editing the original chromatogram data we found that approximately 40% of the grey seal mtDNA haplotype sequences posted in GenBank contained errors. The re-analysis of the edited chromatogram data yielded overall similar results and conclusions as the original study. However, a significantly different outcome was observed when using the uncorrected dataset based on the GenBank haplotypes. We therefore suggest disregarding the existing GenBank data and instead using the correct haplotypes reported here. Our study serves as an illustrative example reiterating the importance of quality control through every step of a research project, from data generation to interpretation and submission to an online repository. Errors conducted in any step may lead to biased results and conclusions, and could impact management decisions.

Control Control Control: A Reassessment and Comparison of GenBank and Chromatogram mtDNA Sequence Variation in Baltic Grey Seals (Halichoerus grypus)

PubMed Central

Fietz, Katharina; Graves, Jeff A.; Olsen, Morten Tange

2013-01-01

Genetic data can provide a powerful tool for those interested in the biology, management and conservation of wildlife, but also lead to erroneous conclusions if appropriate controls are not taken at all steps of the analytical process. This particularly applies to data deposited in public repositories such as GenBank, whose utility relies heavily on the assumption of high data quality. Here we report on an in-depth reassessment and comparison of GenBank and chromatogram mtDNA sequence data generated in a previous study of Baltic grey seals. By re-editing the original chromatogram data we found that approximately 40% of the grey seal mtDNA haplotype sequences posted in GenBank contained errors. The re-analysis of the edited chromatogram data yielded overall similar results and conclusions as the original study. However, a significantly different outcome was observed when using the uncorrected dataset based on the GenBank haplotypes. We therefore suggest disregarding the existing GenBank data and instead using the correct haplotypes reported here. Our study serves as an illustrative example reiterating the importance of quality control through every step of a research project, from data generation to interpretation and submission to an online repository. Errors conducted in any step may lead to biased results and conclusions, and could impact management decisions. PMID:23977362

Active impulsive noise control using maximum correntropy with adaptive kernel size

NASA Astrophysics Data System (ADS)

Lu, Lu; Zhao, Haiquan

2017-03-01

The active noise control (ANC) based on the principle of superposition is an attractive method to attenuate the noise signals. However, the impulsive noise in the ANC systems will degrade the performance of the controller. In this paper, a filtered-x recursive maximum correntropy (FxRMC) algorithm is proposed based on the maximum correntropy criterion (MCC) to reduce the effect of outliers. The proposed FxRMC algorithm does not requires any priori information of the noise characteristics and outperforms the filtered-x least mean square (FxLMS) algorithm for impulsive noise. Meanwhile, in order to adjust the kernel size of FxRMC algorithm online, a recursive approach is proposed through taking into account the past estimates of error signals over a sliding window. Simulation and experimental results in the context of active impulsive noise control demonstrate that the proposed algorithms achieve much better performance than the existing algorithms in various noise environments.

Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives.

PubMed

Salguero-Chaparro, Lourdes; Baeten, Vincent; Fernández-Pierna, Juan A; Peña-Rodríguez, Francisco

2013-08-15

The acidity, moisture and fat content in intact olive fruits were determined on-line using a NIR diode array instrument, operating on a conveyor belt. Four sets of calibrations models were obtained by means of different combinations from samples collected during 2009-2010 and 2010-2011, using full-cross and external validation. Several preprocessing treatments such as derivatives and scatter correction were investigated by using the root mean square error of cross-validation (RMSECV) and prediction (RMSEP), as control parameters. The results obtained showed RMSECV values of 2.54-3.26 for moisture, 2.35-2.71 for fat content and 2.50-3.26 for acidity parameters, depending on the calibration model developed. Calibrations for moisture, fat content and acidity gave residual predictive deviation (RPD) values of 2.76, 2.37 and 1.60, respectively. Although, it is concluded that the on-line NIRS prediction results were acceptable for the three parameters measured in intact olive samples in movement, the models developed must be improved in order to increase their accuracy before final NIRS implementation at mills. Copyright © 2013 Elsevier Ltd. All rights reserved.

Efficient Online Learning Algorithms Based on LSTM Neural Networks.

PubMed

Ergen, Tolga; Kozat, Suleyman Serdar

2017-09-13

We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

DOE PAGES

McNair, Katelyn; Edwards, Robert A.

2015-06-16

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping errormore » rates low, as well as offering unique data visualization options.« less

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

PubMed

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

PubMed Central

Gerstner, Wulfram

2017-01-01

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280

Patients' online access to their electronic health records and linked online services: a systematic interpretative review.

PubMed

de Lusignan, Simon; Mold, Freda; Sheikh, Aziz; Majeed, Azeem; Wyatt, Jeremy C; Quinn, Tom; Cavill, Mary; Gronlund, Toto Anne; Franco, Christina; Chauhan, Umesh; Blakey, Hannah; Kataria, Neha; Barker, Fiona; Ellis, Beverley; Koczan, Phil; Arvanitis, Theodoros N; McCarthy, Mary; Jones, Simon; Rafi, Imran

2014-09-08

To investigate the effect of providing patients online access to their electronic health record (EHR) and linked transactional services on the provision, quality and safety of healthcare. The objectives are also to identify and understand: barriers and facilitators for providing online access to their records and services for primary care workers; and their association with organisational/IT system issues. Primary care. A total of 143 studies were included. 17 were experimental in design and subject to risk of bias assessment, which is reported in a separate paper. Detailed inclusion and exclusion criteria have also been published elsewhere in the protocol. Our primary outcome measure was change in quality or safety as a result of implementation or utilisation of online records/transactional services. No studies reported changes in health outcomes; though eight detected medication errors and seven reported improved uptake of preventative care. Professional concerns over privacy were reported in 14 studies. 18 studies reported concern over potential increased workload; with some showing an increase workload in email or online messaging; telephone contact remaining unchanged, and face-to face contact staying the same or falling. Owing to heterogeneity in reporting overall workload change was hard to predict. 10 studies reported how online access offered convenience, primarily for more advantaged patients, who were largely highly satisfied with the process when clinician responses were prompt. Patient online access and services offer increased convenience and satisfaction. However, professionals were concerned about impact on workload and risk to privacy. Studies correcting medication errors may improve patient safety. There may need to be a redesign of the business process to engage health professionals in online access and of the EHR to make it friendlier and provide equity of access to a wider group of patients. A1 SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42012003091. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Patients’ online access to their electronic health records and linked online services: a systematic interpretative review

PubMed Central

de Lusignan, Simon; Mold, Freda; Sheikh, Aziz; Majeed, Azeem; Wyatt, Jeremy C; Quinn, Tom; Cavill, Mary; Gronlund, Toto Anne; Franco, Christina; Chauhan, Umesh; Blakey, Hannah; Kataria, Neha; Barker, Fiona; Ellis, Beverley; Koczan, Phil; Arvanitis, Theodoros N; McCarthy, Mary; Jones, Simon; Rafi, Imran

2014-01-01

Objectives To investigate the effect of providing patients online access to their electronic health record (EHR) and linked transactional services on the provision, quality and safety of healthcare. The objectives are also to identify and understand: barriers and facilitators for providing online access to their records and services for primary care workers; and their association with organisational/IT system issues. Setting Primary care. Participants A total of 143 studies were included. 17 were experimental in design and subject to risk of bias assessment, which is reported in a separate paper. Detailed inclusion and exclusion criteria have also been published elsewhere in the protocol. Primary and secondary outcome measures Our primary outcome measure was change in quality or safety as a result of implementation or utilisation of online records/transactional services. Results No studies reported changes in health outcomes; though eight detected medication errors and seven reported improved uptake of preventative care. Professional concerns over privacy were reported in 14 studies. 18 studies reported concern over potential increased workload; with some showing an increase workload in email or online messaging; telephone contact remaining unchanged, and face-to face contact staying the same or falling. Owing to heterogeneity in reporting overall workload change was hard to predict. 10 studies reported how online access offered convenience, primarily for more advantaged patients, who were largely highly satisfied with the process when clinician responses were prompt. Conclusions Patient online access and services offer increased convenience and satisfaction. However, professionals were concerned about impact on workload and risk to privacy. Studies correcting medication errors may improve patient safety. There may need to be a redesign of the business process to engage health professionals in online access and of the EHR to make it friendlier and provide equity of access to a wider group of patients. A1. Systematic review registration number PROSPERO CRD42012003091. PMID:25200561

Online 3D EPID-based dose verification: Proof of concept

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spreeuw, Hanno; Rozendaal, Roel, E-mail: r.rozenda

Purpose: Delivery errors during radiotherapy may lead to medical harm and reduced life expectancy for patients. Such serious incidents can be avoided by performing dose verification online, i.e., while the patient is being irradiated, creating the possibility of halting the linac in case of a large overdosage or underdosage. The offline EPID-based 3D in vivo dosimetry system clinically employed at our institute is in principle suited for online treatment verification, provided the system is able to complete 3D dose reconstruction and verification within 420 ms, the present acquisition time of a single EPID frame. It is the aim of thismore » study to show that our EPID-based dosimetry system can be made fast enough to achieve online 3D in vivo dose verification. Methods: The current dose verification system was sped up in two ways. First, a new software package was developed to perform all computations that are not dependent on portal image acquisition separately, thus removing the need for doing these calculations in real time. Second, the 3D dose reconstruction algorithm was sped up via a new, multithreaded implementation. Dose verification was implemented by comparing planned with reconstructed 3D dose distributions delivered to two regions in a patient: the target volume and the nontarget volume receiving at least 10 cGy. In both volumes, the mean dose is compared, while in the nontarget volume, the near-maximum dose (D2) is compared as well. The real-time dosimetry system was tested by irradiating an anthropomorphic phantom with three VMAT plans: a 6 MV head-and-neck treatment plan, a 10 MV rectum treatment plan, and a 10 MV prostate treatment plan. In all plans, two types of serious delivery errors were introduced. The functionality of automatically halting the linac was also implemented and tested. Results: The precomputation time per treatment was ∼180 s/treatment arc, depending on gantry angle resolution. The complete processing of a single portal frame, including dose verification, took 266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5–10 s irradiation time. Conclusions: A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.« less

VizieR Online Data Catalog: 2014-2017 photometry for ASASSN-13db (Sicilia-Aguilar+, 2017)

NASA Astrophysics Data System (ADS)

Sicilia-Aguilar, A.; Oprandi, A.; Froebrich, D.; Fang, M.; Prieto, J. L.; Stanek, K.; Scholz, A.; Kochanek, C. S.; Henning, T.; Gredel, R.; Holoien, T. S. W.; Rabus, M.; Shappee, B. J.; Billington, S. J.; Campbell-White, J.; Zegmott, T. J.

2017-08-01

Table 1 contains the full photometry from the All Sky Automated Survey for Supernovae (ASAS-SN) for the variable star ASASSN-13db. Detections with their errors and 5-sigma upper limits are given. Upper limits are marked by the "<" sign and have the error column set to 99.99. (1 data file).

The current role of on-line extraction approaches in clinical and forensic toxicology.

PubMed

Mueller, Daniel M

2014-08-01

In today's clinical and forensic toxicological laboratories, automation is of interest because of its ability to optimize processes, to reduce manual workload and handling errors and to minimize exposition to potentially infectious samples. Extraction is usually the most time-consuming step; therefore, automation of this step is reasonable. Currently, from the field of clinical and forensic toxicology, methods using the following on-line extraction techniques have been published: on-line solid-phase extraction, turbulent flow chromatography, solid-phase microextraction, microextraction by packed sorbent, single-drop microextraction and on-line desorption of dried blood spots. Most of these published methods are either single-analyte or multicomponent procedures; methods intended for systematic toxicological analysis are relatively scarce. However, the use of on-line extraction will certainly increase in the near future.

Adaptive Critic-based Neurofuzzy Controller for the Steam Generator Water Level

NASA Astrophysics Data System (ADS)

Fakhrazari, Amin; Boroushaki, Mehrdad

2008-06-01

In this paper, an adaptive critic-based neurofuzzy controller is presented for water level regulation of nuclear steam generators. The problem has been of great concern for many years as the steam generator is a highly nonlinear system showing inverse response dynamics especially at low operating power levels. Fuzzy critic-based learning is a reinforcement learning method based on dynamic programming. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the backpropagation of error algorithm to tune online conclusion parts of the fuzzy inference rules. The critic agent here has a proportional-derivative structure and the fuzzy rule base has nine rules. The proposed controller shows satisfactory transient responses, disturbance rejection and robustness to model uncertainty. Its simple design procedure and structure, nominates it as one of the suitable controller designs for the steam generator water level control in nuclear power plant industry.

Virtual sensors for on-line wheel wear and part roughness measurement in the grinding process.

PubMed

Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A; Cabanes, Itziar; Pombo, Iñigo

2014-05-19

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations.

Permanent-File-Validation Utility Computer Program

NASA Technical Reports Server (NTRS)

Derry, Stephen D.

1988-01-01

Errors in files detected and corrected during operation. Permanent File Validation (PFVAL) utility computer program provides CDC CYBER NOS sites with mechanism to verify integrity of permanent file base. Locates and identifies permanent file errors in Mass Storage Table (MST) and Track Reservation Table (TRT), in permanent file catalog entries (PFC's) in permit sectors, and in disk sector linkage. All detected errors written to listing file and system and job day files. Program operates by reading system tables , catalog track, permit sectors, and disk linkage bytes to vaidate expected and actual file linkages. Used extensively to identify and locate errors in permanent files and enable online correction, reducing computer-system downtime.

RECKONER: read error corrector based on KMC.

PubMed

Dlugosz, Maciej; Deorowicz, Sebastian

2017-04-01

Presence of sequencing errors in data produced by next-generation sequencers affects quality of downstream analyzes. Accuracy of them can be improved by performing error correction of sequencing reads. We introduce a new correction algorithm capable of processing eukaryotic close to 500 Mbp-genome-size, high error-rated data using less than 4 GB of RAM in about 35 min on 16-core computer. Program is freely available at http://sun.aei.polsl.pl/REFRESH/reckoner . sebastian.deorowicz@polsl.pl. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

After the Medication Error: Recent Nursing Graduates' Reflections on Adequacy of Education.

PubMed

Treiber, Linda A; Jones, Jackie H

2018-05-01

The purpose of this study was to better understand individual- and system-level factors surrounding making a medication error from the perspective of recent Bachelor of Science in Nursing graduates. Online survey mixed-methods items included perceptions of adequacy of preparatory nursing education, contributory variables, emotional responses, and treatment by employer following the error. Of the 168 respondents, 55% had made a medication error. Errors resulted from inexperience, rushing, technology, staffing, and patient acuity. Twenty-four percent did not report their errors. Key themes for improving education included more practice in varied clinical areas, intensive pharmacological preparation, practical instruction in functioning within the health care environment, and coping after making medication errors. Errors generally caused emotional distress in the error maker. Overall, perceived treatment after the error reflected supportive environments, where nurses were generally treated with respect, fair treatment, and understanding. Opportunities for nursing education include second victim awareness and reinforcing professional practice standards. [J Nurs Educ. 2018;57(5):275-280.]. Copyright 2018, SLACK Incorporated.

Self-awareness assessment during cognitive rehabilitation in children with acquired brain injury: a feasibility study and proposed model of child anosognosia.

PubMed

Krasny-Pacini, Agata; Limond, Jennifer; Evans, Jonathan; Hiebel, Jean; Bendjelida, Karim; Chevignard, Mathilde

2015-01-01

To compare three ways of assessing self-awareness in children with traumatic brain injury (TBI) and to propose a model of child anosognosia. Five single cases of children with severe TBI, aged 8-14, undergoing metacognitive training. Awareness was assessed using three different measures: two measures of metacognitive knowledge/intellectual awareness (a questionnaire and illustrated stories where child characters have everyday problems related to their executive dysfunction) and one measure of on-line/emergent awareness (post-task appraisal of task difficulty). All three measures showed good feasibility. Analysis of awareness deficit scores indicated large variability (1-100%). Three children showed dissociated scores. Based on these results, we propose a model of child self-awareness and anosognosia and a framework for awareness assessment for rehabilitation purposes. The model emphasizes (1) the role of on-line error detection in the construction of autobiographical memories that allow a child to build a self-knowledge of his/her strengths and difficulties; (2) the multiple components of awareness that need to be assessed separately; (3) the implications for rehabilitation: errorless versus error-based learning, rehabilitation approaches based on metacognition, rationale for rehabilitation intervention based on child's age and impaired awareness component, ethical and developmental consideration of confrontational methods. Self-awareness has multiple components that need to be assessed separately, to better adapt cognitive rehabilitation. Using questionnaires and discrepancy scores are not sufficient to assess awareness, because it does not include on-line error detection, which can be massively impaired in children, especially those with impaired executive functions. On-line error detection is important to promote and error-based learning is useful to allow a child to build a self-knowledge of his/her strengths and difficulties, in the absence of severe episodic memory problems. Metacognitive trainings may not be appropriate for younger children who have age appropriate developmentally immature self-awareness, nor for patients with brain injury if they suffer anosognosia because of their brain injury.

Performance of an online translation tool when applied to patient educational material.

PubMed

Khanna, Raman R; Karliner, Leah S; Eck, Matthias; Vittinghoff, Eric; Koenig, Christopher J; Fang, Margaret C

2011-11-01

Language barriers may prevent clinicians from tailoring patient educational material to the needs of individuals with limited English proficiency. Online translation tools could fill this gap, but their accuracy is unknown. We evaluated the accuracy of an online translation tool for patient educational material. We selected 45 sentences from a pamphlet available in both English and Spanish, and translated it into Spanish using GoogleTranslate™ (GT). Three bilingual Spanish speakers then performed a blinded evaluation on these 45 sentences, comparing GT-translated sentences to those translated professionally, along four domains: fluency (grammatical correctness), adequacy (information preservation), meaning (connotation maintenance), and severity (perceived dangerousness of an error if present). In addition, evaluators indicated whether they had a preference for either the GT-translated or professionally translated sentences. The GT-translated sentences had significantly lower fluency scores compared to the professional translation (3.4 vs. 4.7, P < 0.001), but similar adequacy (4.2 vs. 4.5, P = 0.19) and meaning (4.5 vs. 4.8, P = 0.29) scores. The GT-translated sentences were more likely to have any error (39% vs. 22%, P = 0.05), but not statistically more likely to have a severe error (4% vs. 2%, P = 0.61). Evaluators preferred the professional translation for complex sentences, but not for simple ones. When applied to patient educational material, GT performed comparably to professional human translation in terms of preserving information and meaning, though it was slightly worse in preserving grammar. In situations where professional human translations are unavailable or impractical, online translation may someday fill an important niche. Copyright © 2011 Society of Hospital Medicine.

Online, efficient and precision laser profiling of bronze-bonded diamond grinding wheels based on a single-layer deep-cutting intermittent feeding method

NASA Astrophysics Data System (ADS)

Deng, Hui; Chen, Genyu; He, Jie; Zhou, Cong; Du, Han; Wang, Yanyi

2016-06-01

In this study, an online, efficient and precision laser profiling approach that is based on a single-layer deep-cutting intermittent feeding method is described. The effects of the laser cutting depth and the track-overlap ratio of the laser cutting on the efficiency, precision and quality of laser profiling were investigated. Experiments on the online profiling of bronze-bonded diamond grinding wheels were performed using a pulsed fiber laser. The results demonstrate that an increase in the laser cutting depth caused an increase in the material removal efficiency during the laser profiling process. However, the maximum laser profiling efficiency was only achieved when the laser cutting depth was equivalent to the initial surface contour error of the grinding wheel. In addition, the selection of relatively high track-overlap ratios of laser cutting for the profiling of grinding wheels was beneficial with respect to the increase in the precision of laser profiling, whereas the efficiency and quality of the laser profiling were not affected by the change in the track-overlap ratio. After optimized process parameters were employed for online laser profiling, the circular run-out error and the parallelism error of the grinding wheel surface decreased from 83.1 μm and 324.6 μm to 11.3 μm and 3.5 μm, respectively. The surface contour precision of the grinding wheel significantly improved. The highest surface contour precision for grinding wheels of the same type that can be theoretically achieved after laser profiling is completely dependent on the peak power density of the laser. The higher the laser peak power density is, the higher the surface contour precision of the grinding wheel after profiling.

Orientation estimation algorithm applied to high-spin projectiles

NASA Astrophysics Data System (ADS)

Long, D. F.; Lin, J.; Zhang, X. M.; Li, J.

2014-06-01

High-spin projectiles are low cost military weapons. Accurate orientation information is critical to the performance of the high-spin projectiles control system. However, orientation estimators have not been well translated from flight vehicles since they are too expensive, lack launch robustness, do not fit within the allotted space, or are too application specific. This paper presents an orientation estimation algorithm specific for these projectiles. The orientation estimator uses an integrated filter to combine feedback from a three-axis magnetometer, two single-axis gyros and a GPS receiver. As a new feature of this algorithm, the magnetometer feedback estimates roll angular rate of projectile. The algorithm also incorporates online sensor error parameter estimation performed simultaneously with the projectile attitude estimation. The second part of the paper deals with the verification of the proposed orientation algorithm through numerical simulation and experimental tests. Simulations and experiments demonstrate that the orientation estimator can effectively estimate the attitude of high-spin projectiles. Moreover, online sensor calibration significantly enhances the estimation performance of the algorithm.

Support patient search on pathology reports with interactive online learning based data extraction.

PubMed

Zheng, Shuai; Lu, James J; Appin, Christina; Brat, Daniel; Wang, Fusheng

2015-01-01

Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user's interaction with minimal human effort. We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system's data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users' corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of tests. Extracting data from pathology reports could enable more accurate knowledge to support biomedical research and clinical diagnosis. IDEAL-X provides a bridge that takes advantage of online machine learning based data extraction and the knowledge from human's feedback. By combining iterative online learning and adaptive controlled vocabularies, IDEAL-X can deliver highly adaptive and accurate data extraction to support patient search.

Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

PubMed

Heydari, Ali; Balakrishnan, Sivasubramanya N

2013-01-01

To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.

Online intelligent controllers for an enzyme recovery plant: design methodology and performance.

PubMed

Leite, M S; Fujiki, T L; Silva, F V; Fileti, A M F

2010-12-27

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity.

Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

PubMed Central

Leite, M. S.; Fujiki, T. L.; Silva, F. V.; Fileti, A. M. F.

2010-01-01

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity. PMID:21234106

Predictive monitoring of actions, EEG recordings in virtual reality.

PubMed

Ozkan, Duru G; Pezzetta, Rachele

2018-04-01

Error-related negativity (ERN) is a signal that is associated with error detection. Joch and colleagues (Joch M, Hegele M, Maurer H, Müller H, Maurer LK. J Neurophysiol 118: 486-495, 2017) successfully separated the ERN as a response to online prediction error from feedback updates. We discuss the role of ERN in action and suggest insights from virtual reality techniques; we consider the potential benefit of self-evaluation in determining the mechanisms of ERN amplitude; finally, we review the oscillatory activity that has been claimed to accompany ERN.

Realization of BP neural network modeling based on NOXof CFB boiler in DCS

NASA Astrophysics Data System (ADS)

Bai, Jianyun; Zhu, Zhujun; Wang, Qi; Ying, Jiang

2018-02-01

In the CFB boiler installed with SNCR denitrification system, the mass concentration of NO X is difficult to be predicted by the conventional mathematical model, and the step response mathematical model, obtained by using the step disturbance test of ammonia injection,is inaccurate. this paper presents two kinds of BP neural network model, according to the relationship between the generated mass concentration of NO X and the load, the ratio of air to coal without using the SNCR system, as well as the relationship between the tested mass concentration of NO X and the load, the ratio of air to coal and the amount of ammonia using the SNCR system. then itrealized the on-line prediction of the mass concentration of NO X and the remaining mass concentration of NO X after reductionreaction in DCS system. the practical results show that the average error per hour between generation and the prediction of the amount of NO X mass concentration is within 10 mg/Nm3,the reducing reaction of measured and predicted hourly average error is within 2 mg/Nm3, all in error range, which provides a more accurate model for solvingthe problem on NO X automatic control of SNCR system.

Field Validation of Food Service Listings: A Comparison of Commercial and Online Geographic Information System Databases

PubMed Central

Seliske, Laura; Pickett, William; Bates, Rebecca; Janssen, Ian

2012-01-01

Many studies examining the food retail environment rely on geographic information system (GIS) databases for location information. The purpose of this study was to validate information provided by two GIS databases, comparing the positional accuracy of food service places within a 1 km circular buffer surrounding 34 schools in Ontario, Canada. A commercial database (InfoCanada) and an online database (Yellow Pages) provided the addresses of food service places. Actual locations were measured using a global positioning system (GPS) device. The InfoCanada and Yellow Pages GIS databases provided the locations for 973 and 675 food service places, respectively. Overall, 749 (77.1%) and 595 (88.2%) of these were located in the field. The online database had a higher proportion of food service places found in the field. The GIS locations of 25% of the food service places were located within approximately 15 m of their actual location, 50% were within 25 m, and 75% were within 50 m. This validation study provided a detailed assessment of errors in the measurement of the location of food service places in the two databases. The location information was more accurate for the online database, however, when matching criteria were more conservative, there were no observed differences in error between the databases. PMID:23066385

Field validation of food service listings: a comparison of commercial and online geographic information system databases.

PubMed

Seliske, Laura; Pickett, William; Bates, Rebecca; Janssen, Ian

2012-08-01

Many studies examining the food retail environment rely on geographic information system (GIS) databases for location information. The purpose of this study was to validate information provided by two GIS databases, comparing the positional accuracy of food service places within a 1 km circular buffer surrounding 34 schools in Ontario, Canada. A commercial database (InfoCanada) and an online database (Yellow Pages) provided the addresses of food service places. Actual locations were measured using a global positioning system (GPS) device. The InfoCanada and Yellow Pages GIS databases provided the locations for 973 and 675 food service places, respectively. Overall, 749 (77.1%) and 595 (88.2%) of these were located in the field. The online database had a higher proportion of food service places found in the field. The GIS locations of 25% of the food service places were located within approximately 15 m of their actual location, 50% were within 25 m, and 75% were within 50 m. This validation study provided a detailed assessment of errors in the measurement of the location of food service places in the two databases. The location information was more accurate for the online database, however, when matching criteria were more conservative, there were no observed differences in error between the databases.

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model

PubMed Central

Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo

2017-01-01

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554

A particle swarm model for estimating reliability and scheduling system maintenance

NASA Astrophysics Data System (ADS)

Puzis, Rami; Shirtz, Dov; Elovici, Yuval

2016-05-01

Modifying data and information system components may introduce new errors and deteriorate the reliability of the system. Reliability can be efficiently regained with reliability centred maintenance, which requires reliability estimation for maintenance scheduling. A variant of the particle swarm model is used to estimate reliability of systems implemented according to the model view controller paradigm. Simulations based on data collected from an online system of a large financial institute are used to compare three component-level maintenance policies. Results show that appropriately scheduled component-level maintenance greatly reduces the cost of upholding an acceptable level of reliability by reducing the need in system-wide maintenance.

Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of offline modeling errors

NASA Astrophysics Data System (ADS)

Marti, Alejandro; Folch, Arnau

2018-03-01

Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated with the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems in which meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated with the offline modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the offline coupling strategy are compared against those from an online forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors due to the offline modeling are of the same order of magnitude as those associated with the source term uncertainties. In particular, traditional offline forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45-70 % of the ash cloud of an online forecast. These inconsistencies are anticipated to be even more relevant in scenarios in which the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real-time advisories for aviation to consider employing computationally efficient online dispersal models.

Error detection capability of a novel transmission detector: a validation study for online VMAT monitoring.

PubMed

Pasler, Marlies; Michel, Kilian; Marrazzo, Livia; Obenland, Michael; Pallotta, Stefania; Björnsgard, Mari; Lutterbach, Johannes

2017-09-01

The purpose of this study was to characterize a new single large-area ionization chamber, the integral quality monitor system (iRT, Germany), for online and real-time beam monitoring. Signal stability, monitor unit (MU) linearity and dose rate dependence were investigated for static and arc deliveries and compared to independent ionization chamber measurements. The dose verification capability of the transmission detector system was evaluated by comparing calculated and measured detector signals for 15 volumetric modulated arc therapy plans. The error detection sensitivity was tested by introducing MLC position and linac output errors. Deviations in dose distributions between the original and error-induced plans were compared in terms of detector signal deviation, dose-volume histogram (DVH) metrics and 2D γ-evaluation (2%/2 mm and 3%/3 mm). The detector signal is linearly dependent on linac output and shows negligible (<0.4%) dose rate dependence up to 460 MU min -1 . Signal stability is within 1% for cumulative detector output; substantial variations were observed for the segment-by-segment signal. Calculated versus measured cumulative signal deviations ranged from  -0.16%-2.25%. DVH, mean 2D γ-value and detector signal evaluations showed increasing deviations with regard to the respective reference with growing MLC and dose output errors; good correlation between DVH metrics and detector signal deviation was found (e.g. PTV D mean : R 2   =  0.97). Positional MLC errors of 1 mm and errors in linac output of 2% were identified with the transmission detector system. The extensive tests performed in this investigation show that the new transmission detector provides a stable and sensitive cumulative signal output and is suitable for beam monitoring during patient treatment.

Error detection capability of a novel transmission detector: a validation study for online VMAT monitoring

NASA Astrophysics Data System (ADS)

Pasler, Marlies; Michel, Kilian; Marrazzo, Livia; Obenland, Michael; Pallotta, Stefania; Björnsgard, Mari; Lutterbach, Johannes

2017-09-01

The purpose of this study was to characterize a new single large-area ionization chamber, the integral quality monitor system (iRT, Germany), for online and real-time beam monitoring. Signal stability, monitor unit (MU) linearity and dose rate dependence were investigated for static and arc deliveries and compared to independent ionization chamber measurements. The dose verification capability of the transmission detector system was evaluated by comparing calculated and measured detector signals for 15 volumetric modulated arc therapy plans. The error detection sensitivity was tested by introducing MLC position and linac output errors. Deviations in dose distributions between the original and error-induced plans were compared in terms of detector signal deviation, dose-volume histogram (DVH) metrics and 2D γ-evaluation (2%/2 mm and 3%/3 mm). The detector signal is linearly dependent on linac output and shows negligible (<0.4%) dose rate dependence up to 460 MU min-1. Signal stability is within 1% for cumulative detector output; substantial variations were observed for the segment-by-segment signal. Calculated versus measured cumulative signal deviations ranged from  -0.16%-2.25%. DVH, mean 2D γ-value and detector signal evaluations showed increasing deviations with regard to the respective reference with growing MLC and dose output errors; good correlation between DVH metrics and detector signal deviation was found (e.g. PTV D mean: R 2  =  0.97). Positional MLC errors of 1 mm and errors in linac output of 2% were identified with the transmission detector system. The extensive tests performed in this investigation show that the new transmission detector provides a stable and sensitive cumulative signal output and is suitable for beam monitoring during patient treatment.

Causal Evidence from Humans for the Role of Mediodorsal Nucleus of the Thalamus in Working Memory.

PubMed

Peräkylä, Jari; Sun, Lihua; Lehtimäki, Kai; Peltola, Jukka; Öhman, Juha; Möttönen, Timo; Ogawa, Keith H; Hartikainen, Kaisa M

2017-12-01

The mediodorsal nucleus of the thalamus (MD), with its extensive connections to the lateral pFC, has been implicated in human working memory and executive functions. However, this understanding is based solely on indirect evidence from human lesion and imaging studies and animal studies. Direct, causal evidence from humans is missing. To obtain direct evidence for MD's role in humans, we studied patients treated with deep brain stimulation (DBS) for refractory epilepsy. This treatment is thought to prevent the generalization of a seizure by disrupting the functioning of the patient's anterior nuclei of the thalamus (ANT) with high-frequency electric stimulation. This structure is located superior and anterior to MD, and when the DBS lead is implanted in ANT, tip contacts of the lead typically penetrate through ANT into the adjoining MD. To study the role of MD in human executive functions and working memory, we periodically disrupted and recovered MD's function with high-frequency electric stimulation using DBS contacts reaching MD while participants performed a cognitive task engaging several aspects of executive functions. We hypothesized that the efficacy of executive functions, specifically working memory, is impaired when the functioning of MD is perturbed by high-frequency stimulation. Eight participants treated with ANT-DBS for refractory epilepsy performed a computer-based test of executive functions while DBS was repeatedly switched ON and OFF at MD and at the control location (ANT). In comparison to stimulation of the control location, when MD was stimulated, participants committed 2.26 times more errors in general (total errors; OR = 2.26, 95% CI [1.69, 3.01]) and 2.86 times more working memory-related errors specifically (incorrect button presses; OR = 2.88, CI [1.95, 4.24]). Similarly, participants committed 1.81 more errors in general ( OR = 1.81, CI [1.45, 2.24]) and 2.08 times more working memory-related errors ( OR = 2.08, CI [1.57, 2.75]) in comparison to no stimulation condition. "Total errors" is a composite score consisting of basic error types and was mostly driven by working memory-related errors. The facts that MD and a control location, ANT, are only few millimeters away from each other and that their stimulation produces very different results highlight the location-specific effect of DBS rather than regionally unspecific general effect. In conclusion, disrupting and recovering MD's function with high-frequency electric stimulation modulated participants' online working memory performance providing causal, in vivo evidence from humans for the role of MD in human working memory.

What has fMRI told us about the Development of Cognitive Control through Adolescence?

PubMed Central

Luna, Beatriz; Padmanabhan, Aarthi; O’Hearn, Kirsten

2009-01-01

Cognitive control, the ability to voluntarily guide our behavior, continues to improve throughout adolescence. Below we review the literature on age-related changes in brain function related to response inhibition and working memory, which support cognitive control. Findings from studies using functional magnetic imaging (fMRI) indicate that processing errors, sustaining a cognitive control state, and reaching adult levels of precision, persist through adolescence. Developmental changes in patterns of brain function suggest that core regions of the circuitry underlying cognitive control are on-line early in development. However, age-related changes in localized processes across the brain and in establishing long range connections that support top-down modulation of behavior may support more effective neural processing for optimal mature executive function. While great progress has been made in understanding the age-related changes in brain processes underlying cognitive development, there are still important challenges in developmental neuroimaging methods and the interpretation of data that need to be addressed. PMID:19765880

MIMO H∞ control of three-axis ship-mounted mobile antenna systems

NASA Astrophysics Data System (ADS)

Kuseyri, İ. Sina

2018-02-01

The need for on-line information in any environment has led to the development of mobile satellite communication terminals. These high data-rate terminals require inertial antenna pointing error tolerance within fractions of a degree. However, the base motion of the antenna platform in mobile applications complicates this pointing problem and must be accounted for. Gimbaled motorised pedestals are used to eliminate the effect of disturbance and maintain uninterrupted communication. In this paper, a three-axis ship-mounted antenna on a pedestal gimbal system is studied. Based on the derived dynamic model of the antenna pedestal multi input-multi output PID and H∞ linear controllers are designed to stabilise the antenna to keep its orientation unaltered towards the satellite while the sea waves disturb the antenna. Simulation results are presented to show the stabilisation performance of the system with the synthesised controllers. It is shown through performance comparison and analysis that the proposed H∞ control structure is preferable over PID controlled system in terms of system stability and the disturbance rejection.

An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

NASA Technical Reports Server (NTRS)

Sliwa, S. M.

1984-01-01

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

DOE PAGES

Carlberg, Kevin T.

2014-11-05

Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operationsmore » or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.« less

Quasi-model free control for the post-capture operation of a non-cooperative target

NASA Astrophysics Data System (ADS)

She, Yuchen; Sun, Jun; Li, Shuang; Li, Wendan; Song, Ting

2018-06-01

This paper investigates a quasi-model free control (QMFC) approach for the post-capture control of a non-cooperative space object. The innovation of this paper lies in the following three aspects, which correspond to the three challenges presented in the mission scenario. First, an excitation-response mapping search strategy is developed based on the linearization of the system in terms of a set of parameters, which is efficient in handling the combined spacecraft with a high coupling effect on the inertia matrix. Second, a virtual coordinate system is proposed to efficiently compute the center of mass (COM) of the combined system, which improves the COM tracking efficiency for time-varying COM positions. Third, a linear online corrector is built to reduce the control error to further improve the control accuracy, which helps control the tracking mode within the combined system's time-varying inertia matrix. Finally, simulation analyses show that the proposed control framework is able to realize combined spacecraft post-capture control in extremely unfavorable conditions with high control accuracy.

Analysis of measured data of human body based on error correcting frequency

NASA Astrophysics Data System (ADS)

Jin, Aiyan; Peipei, Gao; Shang, Xiaomei

2014-04-01

Anthropometry is to measure all parts of human body surface, and the measured data is the basis of analysis and study of the human body, establishment and modification of garment size and formulation and implementation of online clothing store. In this paper, several groups of the measured data are gained, and analysis of data error is gotten by analyzing the error frequency and using analysis of variance method in mathematical statistics method. Determination of the measured data accuracy and the difficulty of measured parts of human body, further studies of the causes of data errors, and summarization of the key points to minimize errors possibly are also mentioned in the paper. This paper analyses the measured data based on error frequency, and in a way , it provides certain reference elements to promote the garment industry development.

Clutch pressure estimation for a power-split hybrid transmission using nonlinear robust observer

NASA Astrophysics Data System (ADS)

Zhou, Bin; Zhang, Jianwu; Gao, Ji; Yu, Haisheng; Liu, Dong

2018-06-01

For a power-split hybrid transmission, using the brake clutch to realize the transition from electric drive mode to hybrid drive mode is an available strategy. Since the pressure information of the brake clutch is essential for the mode transition control, this research designs a nonlinear robust reduced-order observer to estimate the brake clutch pressure. Model uncertainties or disturbances are considered as additional inputs, thus the observer is designed in order that the error dynamics is input-to-state stable. The nonlinear characteristics of the system are expressed as the lookup tables in the observer. Moreover, the gain matrix of the observer is solved by two optimization procedures under the constraints of the linear matrix inequalities. The proposed observer is validated by offline simulation and online test, the results have shown that the observer achieves significant performance during the mode transition, as the estimation error is within a reasonable range, more importantly, it is asymptotically stable.

Automatic lung segmentation using control feedback system: morphology and texture paradigm.

PubMed

Noor, Norliza M; Than, Joel C M; Rijal, Omar M; Kassim, Rosminah M; Yunus, Ashari; Zeki, Amir A; Anzidei, Michele; Saba, Luca; Suri, Jasjit S

2015-03-01

Interstitial Lung Disease (ILD) encompasses a wide array of diseases that share some common radiologic characteristics. When diagnosing such diseases, radiologists can be affected by heavy workload and fatigue thus decreasing diagnostic accuracy. Automatic segmentation is the first step in implementing a Computer Aided Diagnosis (CAD) that will help radiologists to improve diagnostic accuracy thereby reducing manual interpretation. Automatic segmentation proposed uses an initial thresholding and morphology based segmentation coupled with feedback that detects large deviations with a corrective segmentation. This feedback is analogous to a control system which allows detection of abnormal or severe lung disease and provides a feedback to an online segmentation improving the overall performance of the system. This feedback system encompasses a texture paradigm. In this study we studied 48 males and 48 female patients consisting of 15 normal and 81 abnormal patients. A senior radiologist chose the five levels needed for ILD diagnosis. The results of segmentation were displayed by showing the comparison of the automated and ground truth boundaries (courtesy of ImgTracer™ 1.0, AtheroPoint™ LLC, Roseville, CA, USA). The left lung's performance of segmentation was 96.52% for Jaccard Index and 98.21% for Dice Similarity, 0.61 mm for Polyline Distance Metric (PDM), -1.15% for Relative Area Error and 4.09% Area Overlap Error. The right lung's performance of segmentation was 97.24% for Jaccard Index, 98.58% for Dice Similarity, 0.61 mm for PDM, -0.03% for Relative Area Error and 3.53% for Area Overlap Error. The segmentation overall has an overall similarity of 98.4%. The segmentation proposed is an accurate and fully automated system.

Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

PubMed

Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

2017-03-01

A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs. Biotechnol. Bioeng. 2017;114: 589-599. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Calibration of a flexible measurement system based on industrial articulated robot and structured light sensor

NASA Astrophysics Data System (ADS)

Mu, Nan; Wang, Kun; Xie, Zexiao; Ren, Ping

2017-05-01

To realize online rapid measurement for complex workpieces, a flexible measurement system based on an articulated industrial robot with a structured light sensor mounted on the end-effector is developed. A method for calibrating the system parameters is proposed in which the hand-eye transformation parameters and the robot kinematic parameters are synthesized in the calibration process. An initial hand-eye calibration is first performed using a standard sphere as the calibration target. By applying the modified complete and parametrically continuous method, we establish a synthesized kinematic model that combines the initial hand-eye transformation and distal link parameters as a whole with the sensor coordinate system as the tool frame. According to the synthesized kinematic model, an error model is constructed based on spheres' center-to-center distance errors. Consequently, the error model parameters can be identified in a calibration experiment using a three-standard-sphere target. Furthermore, the redundancy of error model parameters is eliminated to ensure the accuracy and robustness of the parameter identification. Calibration and measurement experiments are carried out based on an ER3A-C60 robot. The experimental results show that the proposed calibration method enjoys high measurement accuracy, and this efficient and flexible system is suitable for online measurement in industrial scenes.

Discrete-Time Zhang Neural Network for Online Time-Varying Nonlinear Optimization With Application to Manipulator Motion Generation.

PubMed

Jin, Long; Zhang, Yunong

2015-07-01

In this brief, a discrete-time Zhang neural network (DTZNN) model is first proposed, developed, and investigated for online time-varying nonlinear optimization (OTVNO). Then, Newton iteration is shown to be derived from the proposed DTZNN model. In addition, to eliminate the explicit matrix-inversion operation, the quasi-Newton Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is introduced, which can effectively approximate the inverse of Hessian matrix. A DTZNN-BFGS model is thus proposed and investigated for OTVNO, which is the combination of the DTZNN model and the quasi-Newton BFGS method. In addition, theoretical analyses show that, with step-size h=1 and/or with zero initial error, the maximal residual error of the DTZNN model has an O(τ(2)) pattern, whereas the maximal residual error of the Newton iteration has an O(τ) pattern, with τ denoting the sampling gap. Besides, when h ≠ 1 and h ∈ (0,2) , the maximal steady-state residual error of the DTZNN model has an O(τ(2)) pattern. Finally, an illustrative numerical experiment and an application example to manipulator motion generation are provided and analyzed to substantiate the efficacy of the proposed DTZNN and DTZNN-BFGS models for OTVNO.

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

NASA Astrophysics Data System (ADS)

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.

Ultrasound fusion image error correction using subject-specific liver motion model and automatic image registration.

PubMed

Yang, Minglei; Ding, Hui; Zhu, Lei; Wang, Guangzhi

2016-12-01

Ultrasound fusion imaging is an emerging tool and benefits a variety of clinical applications, such as image-guided diagnosis and treatment of hepatocellular carcinoma and unresectable liver metastases. However, respiratory liver motion-induced misalignment of multimodal images (i.e., fusion error) compromises the effectiveness and practicability of this method. The purpose of this paper is to develop a subject-specific liver motion model and automatic registration-based method to correct the fusion error. An online-built subject-specific motion model and automatic image registration method for 2D ultrasound-3D magnetic resonance (MR) images were combined to compensate for the respiratory liver motion. The key steps included: 1) Build a subject-specific liver motion model for current subject online and perform the initial registration of pre-acquired 3D MR and intra-operative ultrasound images; 2) During fusion imaging, compensate for liver motion first using the motion model, and then using an automatic registration method to further correct the respiratory fusion error. Evaluation experiments were conducted on liver phantom and five subjects. In the phantom study, the fusion error (superior-inferior axis) was reduced from 13.90±2.38mm to 4.26±0.78mm by using the motion model only. The fusion error further decreased to 0.63±0.53mm by using the registration method. The registration method also decreased the rotation error from 7.06±0.21° to 1.18±0.66°. In the clinical study, the fusion error was reduced from 12.90±9.58mm to 6.12±2.90mm by using the motion model alone. Moreover, the fusion error decreased to 1.96±0.33mm by using the registration method. The proposed method can effectively correct the respiration-induced fusion error to improve the fusion image quality. This method can also reduce the error correction dependency on the initial registration of ultrasound and MR images. Overall, the proposed method can improve the clinical practicability of ultrasound fusion imaging. Copyright © 2016 Elsevier Ltd. All rights reserved.

Online damage detection using recursive principal component analysis and recursive condition indicators

NASA Astrophysics Data System (ADS)

Krishnan, M.; Bhowmik, B.; Tiwari, A. K.; Hazra, B.

2017-08-01

In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using recursive principal component analysis (RPCA) in conjunction with online damage indicators is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal modes in online using the rank-one perturbation method, and subsequently utilized to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/nonlinear-states that indicate damage. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. An online condition indicator (CI) based on the L2 norm of the error between actual response and the response projected using recursive eigenvector matrix updates over successive iterations is proposed. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data. The proposed CI, named recursive residual error, is also adopted for simultaneous spatio-temporal damage detection. Numerical simulations performed on five-degree of freedom nonlinear system under white noise and El Centro excitations, with different levels of nonlinearity simulating the damage scenarios, demonstrate the robustness of the proposed algorithm. Successful results obtained from practical case studies involving experiments performed on a cantilever beam subjected to earthquake excitation, for full sensors and underdetermined cases; and data from recorded responses of the UCLA Factor building (full data and its subset) demonstrate the efficacy of the proposed methodology as an ideal candidate for real-time, reference free structural health monitoring.

Self-Tuning Adaptive-Controller Using Online Frequency Identification

NASA Technical Reports Server (NTRS)

Chiang, W. W.; Cannon, R. H., Jr.

1985-01-01

A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

Model predictive controller design for boost DC-DC converter using T-S fuzzy cost function

NASA Astrophysics Data System (ADS)

Seo, Sang-Wha; Kim, Yong; Choi, Han Ho

2017-11-01

This paper proposes a Takagi-Sugeno (T-S) fuzzy method to select cost function weights of finite control set model predictive DC-DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T-S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T-S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.

Accessibility assessment of assistive technology for the hearing impaired.

PubMed

Áfio, Aline Cruz Esmeraldo; Carvalho, Aline Tomaz de; Caravalho, Luciana Vieira de; Silva, Andréa Soares Rocha da; Pagliuca, Lorita Marlena Freitag

2016-01-01

to assess the automatic accessibility of assistive technology in online courses for the hearing impaired. evaluation study guided by the Assessment and Maintenance step proposed in the Model of Development of Digital Educational Material. The software Assessor and Simulator for the Accessibility of Sites (ASES) was used to analyze the online course "Education on Sexual and Reproductive Health: the use of condoms" according to the accessibility standards of national and international websites. an error report generated by the program identified, in each didactic module, one error and two warnings related to two international principles and six warnings involved with six national recommendations. The warnings relevant to hearing-impaired people were corrected, and the course was considered accessible by automatic assessment. we concluded that the pages of the course were considered, by the software used, appropriate to the standards of web accessibility.

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

PubMed Central

Arriandiaga, Ander; Portillo, Eva; Sánchez, Jose A.; Cabanes, Itziar; Pombo, Iñigo

2014-01-01

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 μm). In the case of surface finish, the absolute error is well below Ra 1 μm (average value 0.32 μm). The present approach can be easily generalized to other grinding operations. PMID:24854055

Accurate Heart Rate Monitoring During Physical Exercises Using PPG.

PubMed

Temko, Andriy

2017-09-01

The challenging task of heart rate (HR) estimation from the photoplethysmographic (PPG) signal, during intensive physical exercises, is tackled in this paper. The study presents a detailed analysis of a novel algorithm (WFPV) that exploits a Wiener filter to attenuate the motion artifacts, a phase vocoder to refine the HR estimate and user-adaptive post-processing to track the subject physiology. Additionally, an offline version of the HR estimation algorithm that uses Viterbi decoding is designed for scenarios that do not require online HR monitoring (WFPV+VD). The performance of the HR estimation systems is rigorously compared with existing algorithms on the publically available database of 23 PPG recordings. On the whole dataset of 23 PPG recordings, the algorithms result in average absolute errors of 1.97 and 1.37 BPM in the online and offline modes, respectively. On the test dataset of 10 PPG recordings which were most corrupted with motion artifacts, WFPV has an error of 2.95 BPM on its own and 2.32 BPM in an ensemble with two existing algorithms. The error rate is significantly reduced when compared with the state-of-the art PPG-based HR estimation methods. The proposed system is shown to be accurate in the presence of strong motion artifacts and in contrast to existing alternatives has very few free parameters to tune. The algorithm has a low computational cost and can be used for fitness tracking and health monitoring in wearable devices. The MATLAB implementation of the algorithm is provided online.

High-performance object tracking and fixation with an online neural estimator.

PubMed

Kumarawadu, Sisil; Watanabe, Keigo; Lee, Tsu-Tian

2007-02-01

Vision-based target tracking and fixation to keep objects that move in three dimensions in view is important for many tasks in several fields including intelligent transportation systems and robotics. Much of the visual control literature has focused on the kinematics of visual control and ignored a number of significant dynamic control issues that limit performance. In line with this, this paper presents a neural network (NN)-based binocular tracking scheme for high-performance target tracking and fixation with minimum sensory information. The procedure allows the designer to take into account the physical (Lagrangian dynamics) properties of the vision system in the control law. The design objective is to synthesize a binocular tracking controller that explicitly takes the systems dynamics into account, yet needs no knowledge of dynamic nonlinearities and joint velocity sensory information. The combined neurocontroller-observer scheme can guarantee the uniform ultimate bounds of the tracking, observer, and NN weight estimation errors under fairly general conditions on the controller-observer gains. The controller is tested and verified via simulation tests in the presence of severe target motion changes.

Competitive learning with pairwise constraints.

PubMed

Covões, Thiago F; Hruschka, Eduardo R; Ghosh, Joydeep

2013-01-01

Constrained clustering has been an active research topic since the last decade. Most studies focus on batch-mode algorithms. This brief introduces two algorithms for on-line constrained learning, named on-line linear constrained vector quantization error (O-LCVQE) and constrained rival penalized competitive learning (C-RPCL). The former is a variant of the LCVQE algorithm for on-line settings, whereas the latter is an adaptation of the (on-line) RPCL algorithm to deal with constrained clustering. The accuracy results--in terms of the normalized mutual information (NMI)--from experiments with nine datasets show that the partitions induced by O-LCVQE are competitive with those found by the (batch-mode) LCVQE. Compared with this formidable baseline algorithm, it is surprising that C-RPCL can provide better partitions (in terms of the NMI) for most of the datasets. Also, experiments on a large dataset show that on-line algorithms for constrained clustering can significantly reduce the computational time.

Adaptive filter design using recurrent cerebellar model articulation controller.

PubMed

Lin, Chih-Min; Chen, Li-Yang; Yeung, Daniel S

2010-07-01

A novel adaptive filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so the stability of the filtering error can be guaranteed. To demonstrate the performance of the proposed adaptive RCMAC filter, it is applied to a nonlinear channel equalization system and an adaptive noise cancelation system. The advantages of the proposed filter over other adaptive filters are verified through simulations.

A Novel Image Steganography Technique for Secured Online Transaction Using DWT and Visual Cryptography

NASA Astrophysics Data System (ADS)

Anitha Devi, M. D.; ShivaKumar, K. B.

2017-08-01

Online payment eco system is the main target especially for cyber frauds. Therefore end to end encryption is very much needed in order to maintain the integrity of secret information related to transactions carried online. With access to payment related sensitive information, which enables lot of money transactions every day, the payment infrastructure is a major target for hackers. The proposed system highlights, an ideal approach for secure online transaction for fund transfer with a unique combination of visual cryptography and Haar based discrete wavelet transform steganography technique. This combination of data hiding technique reduces the amount of information shared between consumer and online merchant needed for successful online transaction along with providing enhanced security to customer’s account details and thereby increasing customer’s confidence preventing “Identity theft” and “Phishing”. To evaluate the effectiveness of proposed algorithm Root mean square error, Peak signal to noise ratio have been used as evaluation parameters

On-line vs off-line electrical conductivity characterization. Polycarbonate composites developed with multiwalled carbon nanotubes by compounding technology

NASA Astrophysics Data System (ADS)

Llorens-Chiralt, R.; Weiss, P.; Mikonsaari, I.

2014-05-01

Material characterization is one of the key steps when conductive polymers are developed. The dispersion of carbon nanotubes (CNTs) in a polymeric matrix using melt mixing influence final composite properties. The compounding becomes trial and error using a huge amount of materials, spending time and money to obtain competitive composites. Traditional methods to carry out electrical conductivity characterization include compression and injection molding. Both methods need extra equipments and moulds to obtain standard bars. This study aims to investigate the accuracy of the data obtained from absolute resistance recorded during the melt compounding, using an on-line setup developed by our group, and to correlate these values with off-line characterization and processing parameters (screw/barrel configuration, throughput, screw speed, temperature profile and CNTs percentage). Compounds developed with different percentages of multi walled carbon nanotubes (MWCNTs) and polycarbonate has been characterized during and after extrusion. Measurements, on-line resistance and off-line resistivity, showed parallel response and reproducibility, confirming method validity. The significance of the results obtained stems from the fact that we are able to measure on-line resistance and to change compounding parameters during production to achieve reference values reducing production/testing cost and ensuring material quality. Also, this method removes errors which can be found in test bars development, showing better correlation with compounding parameters.

TH-E-BRE-04: An Online Replanning Algorithm for VMAT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahunbay, E; Li, X; Moreau, M

2014-06-15

Purpose: To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filtered (FF) and flattening filter free (FFF) beams. Methods: A software tool was developed to interface with a VMAT planning system ((Monaco, Elekta), enabling the output of detailed beam/machine parameters of original VMAT plans generated based on planning CTs for FF or FFF beams. A SAM algorithm, previously developed for fixed-beam IMRT, was modified to allow the algorithm to correct for interfractional variations (e.g., setup error, organ motion and deformation) by morphing apertures based on themore » geometric relationship between the beam's eye view of the anatomy from the planning CT and that from the daily CT for each control point. The algorithm was tested using daily CTs acquired using an in-room CT during daily IGRT for representative prostate cancer cases along with their planning CTs. The algorithm allows for restricted MLC leaf travel distance between control points of the VMAT delivery to prevent SAM from increasing leaf travel, and therefore treatment delivery time. Results: The VMAT plans adapted to the daily CT by SAM were found to improve the dosimetry relative to the IGRT repositioning plans for both FF and FFF beams. For the adaptive plans, the changes in leaf travel distance between control points were < 1cm for 80% of the control points with no restriction. When restricted to the original plans' maximum travel distance, the dosimetric effect was minimal. The adaptive plans were delivered successfully with similar delivery times as the original plans. The execution of the SAM algorithm was < 10 seconds. Conclusion: The SAM algorithm can quickly generate deliverable online-adaptive VMAT plans based on the anatomy of the day for both FF and FFF beams.« less

Help prevent hospital errors

MedlinePlus

... A.D.A.M. follows rigorous standards of quality and accountability. A.D.A.M. is among the first to achieve this important distinction for online health information and services. Learn more about A.D.A.M.'s editorial ...

Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

PubMed

Steinwandter, Valentin; Zahel, Thomas; Sagmeister, Patrick; Herwig, Christoph

2017-01-01

In biopharmaceutical process development and manufacturing, the online measurement of biomass and derived specific turnover rates is a central task to physiologically monitor and control the process. However, hard-type sensors such as dielectric spectroscopy, broth fluorescence, or permittivity measurement harbor various disadvantages. Therefore, soft-sensors, which use measurements of the off-gas stream and substrate feed to reconcile turnover rates and provide an online estimate of the biomass formation, are smart alternatives. For the reconciliation procedure, mass and energy balances are used together with accuracy estimations of measured conversion rates, which were so far arbitrarily chosen and static over the entire process. In this contribution, we present a novel strategy within the soft-sensor framework (named adaptive soft-sensor) to propagate uncertainties from measurements to conversion rates and demonstrate the benefits: For industrially relevant conditions, hereby the error of the resulting estimated biomass formation rate and specific substrate consumption rate could be decreased by 43 and 64 %, respectively, compared to traditional soft-sensor approaches. Moreover, we present a generic workflow to determine the required raw signal accuracy to obtain predefined accuracies of soft-sensor estimations. Thereby, appropriate measurement devices and maintenance intervals can be selected. Furthermore, using this workflow, we demonstrate that the estimation accuracy of the soft-sensor can be additionally and substantially increased.

Application Of A Potentiometric Electronic Tongue For The Determination Of Free SO2 And Other Analytical Parameters In White Wines From New Zealand

NASA Astrophysics Data System (ADS)

Mednova, Olga; Kirsanov, Dmitry; Rudnitskaya, Alisa; Kilmartin, Paul; Legin, Andrey

2009-05-01

The present study deals with a potentiometric electronic tongue (ET) multisensor system applied for the simultaneous determination of several chemical parameters for white wines produced in New Zealand. Methods in use for wine quality control are often expensive and require considerable time and skilled operation. The ET approach usually offers a simple and fast measurement protocol and allows automation for on-line analysis under industrial conditions. The ET device developed in this research is capable of quantifying the free and total SO2 content, total acids and some polyphenolic compounds in white wines with acceptable analytical errors.

Crowd-sourcing Meteorological Data for Student Field Projects

NASA Astrophysics Data System (ADS)

Bullard, J. E.

2016-12-01

This paper explains how students can rapidly collect large datasets to characterise wind speed and direction under different meteorological conditions. The tools used include a mobile device (tablet or phone), low cost wind speed/direction meters that are plugged in to the mobile device, and an app with online web support for uploading, collating and georeferencing data. Electronic customised data input forms downloaded to the mobile device are used to ensure students collect data using specified protocols which streamlines data management and reduces the likelihood of data entry errors. A key benefit is the rapid collection and quality control of field data that can be promptly disseminated to students for subsequent analysis.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

TH-AB-202-04: Auto-Adaptive Margin Generation for MLC-Tracked Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glitzner, M; Lagendijk, J; Raaymakers, B

Purpose: To develop an auto-adaptive margin generator for MLC tracking. The generator is able to estimate errors arising in image guided radiotherapy, particularly on an MR-Linac, which depend on the latencies of machine and image processing, as well as on patient motion characteristics. From the estimated error distribution, a segment margin is generated, able to compensate errors up to a user-defined confidence. Method: In every tracking control cycle (TCC, 40ms), the desired aperture D(t) is compared to the actual aperture A(t), a delayed and imperfect representation of D(t). Thus an error e(t)=A(T)-D(T) is measured every TCC. Applying kernel-density-estimation (KDE), themore » cumulative distribution (CDF) of e(t) is estimated. With CDF-confidence limits, upper and lower error limits are extracted for motion axes along and perpendicular leaf-travel direction and applied as margins. To test the dosimetric impact, two representative motion traces were extracted from fast liver-MRI (10Hz). The traces were applied onto a 4D-motion platform and continuously tracked by an Elekta Agility 160 MLC using an artificially imposed tracking delay. Gafchromic film was used to detect dose exposition for static, tracked, and error-compensated tracking cases. The margin generator was parameterized to cover 90% of all tracking errors. Dosimetric impact was rated by calculating the ratio between underexposed points (>5% underdosage) to the total number of points inside FWHM of static exposure. Results: Without imposing adaptive margins, tracking experiments showed a ratio of underexposed points of 17.5% and 14.3% for two motion cases with imaging delays of 200ms and 300ms, respectively. Activating the margin generated yielded total suppression (<1%) of underdosed points. Conclusion: We showed that auto-adaptive error compensation using machine error statistics is possible for MLC tracking. The error compensation margins are calculated on-line, without the need of assuming motion or machine models. Further strategies to reduce consequential overdosages are currently under investigation. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution.« less

Identification and control of plasma vertical position using neural network in Damavand tokamak.

PubMed

Rasouli, H; Rasouli, C; Koohi, A

2013-02-01

In this work, a nonlinear model is introduced to determine the vertical position of the plasma column in Damavand tokamak. Using this model as a simulator, a nonlinear neural network controller has been designed. In the first stage, the electronic drive and sensory circuits of Damavand tokamak are modified. These circuits can control the vertical position of the plasma column inside the vacuum vessel. Since the vertical position of plasma is an unstable parameter, a direct closed loop system identification algorithm is performed. In the second stage, a nonlinear model is identified for plasma vertical position, based on the multilayer perceptron (MLP) neural network (NN) structure. Estimation of simulator parameters has been performed by back-propagation error algorithm using Levenberg-Marquardt gradient descent optimization technique. The model is verified through simulation of the whole closed loop system using both simulator and actual plant in similar conditions. As the final stage, a MLP neural network controller is designed for simulator model. In the last step, online training is performed to tune the controller parameters. Simulation results justify using of the NN controller for the actual plant.

Structural analysis of online handwritten mathematical symbols based on support vector machines

NASA Astrophysics Data System (ADS)

Simistira, Foteini; Papavassiliou, Vassilis; Katsouros, Vassilis; Carayannis, George

2013-01-01

Mathematical expression recognition is still a very challenging task for the research community mainly because of the two-dimensional (2d) structure of mathematical expressions (MEs). In this paper, we present a novel approach for the structural analysis between two on-line handwritten mathematical symbols of a ME, based on spatial features of the symbols. We introduce six features to represent the spatial affinity of the symbols and compare two multi-class classification methods that employ support vector machines (SVMs): one based on the "one-against-one" technique and one based on the "one-against-all", in identifying the relation between a pair of symbols (i.e. subscript, numerator, etc). A dataset containing 1906 spatial relations derived from the Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) 2012 training dataset is constructed to evaluate the classifiers and compare them with the rule-based classifier of the ILSP-1 system participated in the contest. The experimental results give an overall mean error rate of 2.61% for the "one-against-one" SVM approach, 6.57% for the "one-against-all" SVM technique and 12.31% error rate for the ILSP-1 classifier.

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Time pressure in scenario-based online construction safety quizzes and its effect on students' performance

NASA Astrophysics Data System (ADS)

Jaeger, Martin; Adair, Desmond

2017-05-01

Online quizzes have been shown to be effective learning and assessment approaches. However, if scenario-based online construction safety quizzes do not include time pressure similar to real-world situations, they reflect situations too ideally. The purpose of this paper is to compare engineering students' performance when carrying out an online construction safety quiz with time pressure versus an online construction safety quiz without time pressure. Two versions of an online construction safety quiz are developed and administered to randomly assigned engineering students based on a quasi-experimental post-test design. The findings contribute to scenario-based learning and assessment of construction safety in four ways. First, the results confirm earlier findings that 'intrinsic stress' does not seem to impair students' performance. Second, students who carry out the online construction safety quiz with time pressure are less likely to 'learn by trial and error'. Third, students exposed to time pressure appreciate that they become better prepared for real life. Finally, preparing students to work under time pressure is an important industry requirement. The results of this study should encourage engineering educators to explore and implement ways to include time pressure in scenario-based online quizzes and learning.

On-line near infrared spectroscopy as a Process Analytical Technology (PAT) tool to control an industrial seeded API crystallization.

PubMed

Schaefer, C; Lecomte, C; Clicq, D; Merschaert, A; Norrant, E; Fotiadu, F

2013-09-01

The final step of an active pharmaceutical ingredient (API) manufacturing synthesis process consists of a crystallization during which the API and residual solvent contents have to be quantified precisely in order to reach a predefined seeding point. A feasibility study was conducted to demonstrate the suitability of on-line NIR spectroscopy to control this step in line with new version of the European Medicines Agency (EMA) guideline [1]. A quantitative method was developed at laboratory scale using statistical design of experiments (DOE) and multivariate data analysis such as principal component analysis (PCA) and partial least squares (PLS) regression. NIR models were built to quantify the API in the range of 9-12% (w/w) and to quantify the residual methanol in the range of 0-3% (w/w). To improve the predictive ability of the models, the development procedure encompassed: outliers elimination, optimum model rank definition, spectral range and spectral pre-treatment selection. Conventional criteria such as, number of PLS factors, R(2), root mean square errors of calibration, cross-validation and prediction (RMSEC, RMSECV, RMSEP) enabled the selection of three model candidates. These models were tested in the industrial pilot plant during three technical campaigns. Results of the most suitable models were evaluated against to the chromatographic reference methods. Maximum relative bias of 2.88% was obtained about API target content. Absolute bias of 0.01 and 0.02% (w/w) respectively were achieved at methanol content levels of 0.10 and 0.13% (w/w). The repeatability was assessed as sufficient for the on-line monitoring of the 2 analytes. The present feasibility study confirmed the possibility to use on-line NIR spectroscopy as a PAT tool to monitor in real-time both the API and the residual methanol contents, in order to control the seeding of an API crystallization at industrial scale. Furthermore, the successful scale-up of the method proved its capability to be implemented in the manufacturing plant with the launch of the new API process. Copyright © 2013 Elsevier B.V. All rights reserved.

On-line evaluation of multiloop digital controller performance

NASA Technical Reports Server (NTRS)

Wieseman, Carol D.

1993-01-01

The purpose of this presentation is to inform the Guidance and Control community of capabilities which were developed by the Aeroservoelasticity Branch to evaluate the performance of multivariable control laws, on-line, during wind-tunnel testing. The capabilities are generic enough to be useful for all kinds of on-line analyses involving multivariable control in experimental testing. Consequently, it was decided to present this material at this workshop even though it has been presented elsewhere. Topics covered include: essential on-line analysis requirements; on-line analysis capabilities; on-line analysis software; frequency domain procedures; controller performance evaluation frequency-domain flutter suppression; and plant determination.

An approach to multivariable control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

Computer-Aided Systems Engineering for Flight Research Projects Using a Workgroup Database

NASA Technical Reports Server (NTRS)

Mizukami, Masahi

2004-01-01

An online systems engineering tool for flight research projects has been developed through the use of a workgroup database. Capabilities are implemented for typical flight research systems engineering needs in document library, configuration control, hazard analysis, hardware database, requirements management, action item tracking, project team information, and technical performance metrics. Repetitive tasks are automated to reduce workload and errors. Current data and documents are instantly available online and can be worked on collaboratively. Existing forms and conventional processes are used, rather than inventing or changing processes to fit the tool. An integrated tool set offers advantages by automatically cross-referencing data, minimizing redundant data entry, and reducing the number of programs that must be learned. With a simplified approach, significant improvements are attained over existing capabilities for minimal cost. By using a workgroup-level database platform, personnel most directly involved in the project can develop, modify, and maintain the system, thereby saving time and money. As a pilot project, the system has been used to support an in-house flight experiment. Options are proposed for developing and deploying this type of tool on a more extensive basis.

An adaptive reentry guidance method considering the influence of blackout zone

NASA Astrophysics Data System (ADS)

Wu, Yu; Yao, Jianyao; Qu, Xiangju

2018-01-01

Reentry guidance has been researched as a popular topic because it is critical for a successful flight. In view that the existing guidance methods do not take into account the accumulated navigation error of Inertial Navigation System (INS) in the blackout zone, in this paper, an adaptive reentry guidance method is proposed to obtain the optimal reentry trajectory quickly with the target of minimum aerodynamic heating rate. The terminal error in position and attitude can be also reduced with the proposed method. In this method, the whole reentry guidance task is divided into two phases, i.e., the trajectory updating phase and the trajectory planning phase. In the first phase, the idea of model predictive control (MPC) is used, and the receding optimization procedure ensures the optimal trajectory in the next few seconds. In the trajectory planning phase, after the vehicle has flown out of the blackout zone, the optimal reentry trajectory is obtained by online planning to adapt to the navigation information. An effective swarm intelligence algorithm, i.e. pigeon inspired optimization (PIO) algorithm, is applied to obtain the optimal reentry trajectory in both of the two phases. Compared to the trajectory updating method, the proposed method can reduce the terminal error by about 30% considering both the position and attitude, especially, the terminal error of height has almost been eliminated. Besides, the PIO algorithm performs better than the particle swarm optimization (PSO) algorithm both in the trajectory updating phase and the trajectory planning phases.

Optimal estimation of suspended-sediment concentrations in streams

USGS Publications Warehouse

Holtschlag, D.J.

2001-01-01

Optimal estimators are developed for computation of suspended-sediment concentrations in streams. The estimators are a function of parameters, computed by use of generalized least squares, which simultaneously account for effects of streamflow, seasonal variations in average sediment concentrations, a dynamic error component, and the uncertainty in concentration measurements. The parameters are used in a Kalman filter for on-line estimation and an associated smoother for off-line estimation of suspended-sediment concentrations. The accuracies of the optimal estimators are compared with alternative time-averaging interpolators and flow-weighting regression estimators by use of long-term daily-mean suspended-sediment concentration and streamflow data from 10 sites within the United States. For sampling intervals from 3 to 48 days, the standard errors of on-line and off-line optimal estimators ranged from 52.7 to 107%, and from 39.5 to 93.0%, respectively. The corresponding standard errors of linear and cubic-spline interpolators ranged from 48.8 to 158%, and from 50.6 to 176%, respectively. The standard errors of simple and multiple regression estimators, which did not vary with the sampling interval, were 124 and 105%, respectively. Thus, the optimal off-line estimator (Kalman smoother) had the lowest error characteristics of those evaluated. Because suspended-sediment concentrations are typically measured at less than 3-day intervals, use of optimal estimators will likely result in significant improvements in the accuracy of continuous suspended-sediment concentration records. Additional research on the integration of direct suspended-sediment concentration measurements and optimal estimators applied at hourly or shorter intervals is needed.

SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting

NASA Astrophysics Data System (ADS)

Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

2014-12-01

Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

Design and Calibration of an RF Actuator for Low-Level RF Systems

NASA Astrophysics Data System (ADS)

Geng, Zheqiao; Hong, Bo

2016-02-01

X-ray free electron laser (FEL) machines like the Linac Coherent Light Source (LCLS) at SLAC require high-quality electron beams to generate X-ray lasers for various experiments. Digital low-level RF (LLRF) systems are widely used to control the high-power RF klystrons to provide a highly stable RF field in accelerator structures for beam acceleration. Feedback and feedforward controllers are implemented in LLRF systems to stabilize or adjust the phase and amplitude of the RF field. To achieve the RF stability and the accuracy of the phase and amplitude adjustment, low-noise and highly linear RF actuators are required. Aiming for the upgrade of the S-band Linac at SLAC, an RF actuator is designed with an I/Qmodulator driven by two digital-to-analog converters (DAC) for the digital LLRF systems. A direct upconversion scheme is selected for RF actuation, and an on-line calibration algorithm is developed to compensate the RF reference leakage and the imbalance errors in the I/Q modulator, which may cause significant phase and amplitude actuation errors. This paper presents the requirements on the RF actuator, the design of the hardware, the calibration algorithm, and the implementation in firmware and software and the test results at LCLS.

EEG-based decoding of error-related brain activity in a real-world driving task

NASA Astrophysics Data System (ADS)

Zhang, H.; Chavarriaga, R.; Khaliliardali, Z.; Gheorghe, L.; Iturrate, I.; Millán, J. d. R.

2015-12-01

Objectives. Recent studies have started to explore the implementation of brain-computer interfaces (BCI) as part of driving assistant systems. The current study presents an EEG-based BCI that decodes error-related brain activity. Such information can be used, e.g., to predict driver’s intended turning direction before reaching road intersections. Approach. We executed experiments in a car simulator (N = 22) and a real car (N = 8). While subject was driving, a directional cue was shown before reaching an intersection, and we classified the presence or not of an error-related potentials from EEG to infer whether the cued direction coincided with the subject’s intention. In this protocol, the directional cue can correspond to an estimation of the driving direction provided by a driving assistance system. We analyzed ERPs elicited during normal driving and evaluated the classification performance in both offline and online tests. Results. An average classification accuracy of 0.698 ± 0.065 was obtained in offline experiments in the car simulator, while tests in the real car yielded a performance of 0.682 ± 0.059. The results were significantly higher than chance level for all cases. Online experiments led to equivalent performances in both simulated and real car driving experiments. These results support the feasibility of decoding these signals to help estimating whether the driver’s intention coincides with the advice provided by the driving assistant in a real car. Significance. The study demonstrates a BCI system in real-world driving, extending the work from previous simulated studies. As far as we know, this is the first online study in real car decoding driver’s error-related brain activity. Given the encouraging results, the paradigm could be further improved by using more sophisticated machine learning approaches and possibly be combined with applications in intelligent vehicles.

Simple robust control laws for robot manipulators. Part 1: Non-adaptive case

NASA Technical Reports Server (NTRS)

Wen, J. T.; Bayard, D. S.

1987-01-01

A new class of exponentially stabilizing control laws for joint level control of robot arms is introduced. It has been recently recognized that the nonlinear dynamics associated with robotic manipulators have certain inherent passivity properties. More specifically, the derivation of the robotic dynamic equations from the Hamilton's principle gives rise to natural Lyapunov functions for control design based on total energy considerations. Through a slight modification of the energy Lyapunov function and the use of a convenient lemma to handle third order terms in the Lyapunov function derivatives, closed loop exponential stability for both the set point and tracking control problem is demonstrated. The exponential convergence property also leads to robustness with respect to frictions, bounded modeling errors and instrument noise. In one new design, the nonlinear terms are decoupled from real-time measurements which completely removes the requirement for on-line computation of nonlinear terms in the controller implementation. In general, the new class of control laws offers alternatives to the more conventional computed torque method, providing tradeoffs between robustness, computation and convergence properties. Furthermore, these control laws have the unique feature that they can be adapted in a very simple fashion to achieve asymptotically stable adaptive control.

Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation.

PubMed

Deng, Wenxiang; Yao, Jianyong; Ma, Dawei

2017-09-01

This paper addresses the high performance motion control of hydraulic actuators with parametric uncertainties, unmodeled disturbances and unknown valve dead-zone. By constructing a smooth dead-zone inverse, a robust adaptive controller is proposed via backstepping method, in which adaptive law is synthesized to deal with parametric uncertainties and a continuous nonlinear robust control law to suppress unmodeled disturbances. Since the unknown dead-zone parameters can be estimated by adaptive law and then the effect of dead-zone can be compensated effectively via inverse operation, improved tracking performance can be expected. In addition, the disturbance upper bounds can also be updated online by adaptive laws, which increases the controller operability in practice. The Lyapunov based stability analysis shows that excellent asymptotic output tracking with zero steady-state error can be achieved by the developed controller even in the presence of unmodeled disturbance and unknown valve dead-zone. Finally, the proposed control strategy is experimentally tested on a servovalve controlled hydraulic actuation system subjected to an artificial valve dead-zone. Comparative experimental results are obtained to illustrate the effectiveness of the proposed control scheme. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A Review of System Identification Methods Applied to Aircraft

NASA Technical Reports Server (NTRS)

Klein, V.

1983-01-01

Airplane identification, equation error method, maximum likelihood method, parameter estimation in frequency domain, extended Kalman filter, aircraft equations of motion, aerodynamic model equations, criteria for the selection of a parsimonious model, and online aircraft identification are addressed.

Design of barrier bucket kicker control system

NASA Astrophysics Data System (ADS)

Ni, Fa-Fu; Wang, Yan-Yu; Yin, Jun; Zhou, De-Tai; Shen, Guo-Dong; Zheng, Yang-De.; Zhang, Jian-Chuan; Yin, Jia; Bai, Xiao; Ma, Xiao-Li

2018-05-01

The Heavy-Ion Research Facility in Lanzhou (HIRFL) contains two synchrotrons: the main cooler storage ring (CSRm) and the experimental cooler storage ring (CSRe). Beams are extracted from CSRm, and injected into CSRe. To apply the Barrier Bucket (BB) method on the CSRe beam accumulation, a new BB technology based kicker control system was designed and implemented. The controller of the system is implemented using an Advanced Reduced Instruction Set Computer (RISC) Machine (ARM) chip and a field-programmable gate array (FPGA) chip. Within the architecture, ARM is responsible for data presetting and floating number arithmetic processing. The FPGA computes the RF phase point of the two rings and offers more accurate control of the time delay. An online preliminary experiment on HIRFL was also designed to verify the functionalities of the control system. The result shows that the reference trigger point of two different sinusoidal RF signals for an arbitrary phase point was acquired with a matched phase error below 1° (approximately 2.1 ns), and the step delay time better than 2 ns were realized.

Observer-based distributed adaptive fault-tolerant containment control of multi-agent systems with general linear dynamics.

PubMed

Ye, Dan; Chen, Mengmeng; Li, Kui

2017-11-01

In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Online Deviation Detection for Medical Processes

PubMed Central

Christov, Stefan C.; Avrunin, George S.; Clarke, Lori A.

2014-01-01

Human errors are a major concern in many medical processes. To help address this problem, we are investigating an approach for automatically detecting when performers of a medical process deviate from the acceptable ways of performing that process as specified by a detailed process model. Such deviations could represent errors and, thus, detecting and reporting deviations as they occur could help catch errors before harm is done. In this paper, we identify important issues related to the feasibility of the proposed approach and empirically evaluate the approach for two medical procedures, chemotherapy and blood transfusion. For the evaluation, we use the process models to generate sample process executions that we then seed with synthetic errors. The process models describe the coordination of activities of different process performers in normal, as well as in exceptional situations. The evaluation results suggest that the proposed approach could be applied in clinical settings to help catch errors before harm is done. PMID:25954343

Effects of vibration on inertial wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Young, Clarence P., Jr.; Buehrle, Ralph D.; Balakrishna, S.; Kilgore, W. Allen

1994-01-01

Results of an experimental study of a wind tunnel model inertial angle-of-attack sensor response to a simulated dynamic environment are presented. The inertial device cannot distinguish between the gravity vector and the centrifugal accelerations associated with wind tunnel model vibration, this situation results in a model attitude measurement bias error. Significant bias error in model attitude measurement was found for the model system tested. The model attitude bias error was found to be vibration mode and amplitude dependent. A first order correction model was developed and used for estimating attitude measurement bias error due to dynamic motion. A method for correcting the output of the model attitude inertial sensor in the presence of model dynamics during on-line wind tunnel operation is proposed.

Brands and Inhibition: A Go/No-Go Task Reveals the Power of Brand Influence

PubMed Central

Peatfield, Nicholas; Caulfield, Joanne; Parkinson, John; Intriligator, James

2015-01-01

Whether selecting a candy in a shop or picking a digital camera online, there are usually many options from which consumers may choose. With such abundance, consumers must use a variety of cognitive, emotional, and heuristic means to filter out and inhibit some of their responses. Here we use brand logos within a Go/No-Go task to probe inhibitory control during the presentation of familiar and unfamiliar logos. The results showed no differences in response times or in commission errors (CE) between familiar and unfamiliar logos. However, participants demonstrated a generally more cautious attitude of responding to the familiar brands: they were significantly slower and less accurate at responding to these brands in the Go trials. These findings suggest that inhibitory control can be exercised quite effectively for familiar brands, but that when such inhibition fails, the potent appetitive nature of brands is revealed. PMID:26544606

An advanced robust method for speed control of switched reluctance motor

NASA Astrophysics Data System (ADS)

Zhang, Chao; Ming, Zhengfeng; Su, Zhanping; Cai, Zhuang

2018-05-01

This paper presents an advanced robust controller for the speed system of a switched reluctance motor (SRM) in the presence of nonlinearities, speed ripple, and external disturbances. It proposes that the adaptive fuzzy control is applied to regulate the motor speed in the outer loop, and the detector is used to obtain rotor detection in the inner loop. The new fuzzy logic tuning rules are achieved from the experience of the operator and the knowledge of the specialist. The fuzzy parameters are automatically adjusted online according to the error and its change of speed in the transient period. The designed detector can obtain the rotor's position accurately in each phase module. Furthermore, a series of contrastive simulations are completed between the proposed controller and proportion integration differentiation controller including low speed, medium speed, and high speed. Simulations show that the proposed robust controller enables the system reduced by at least 3% in overshoot, 6% in rise time, and 20% in setting time, respectively, and especially under external disturbances. Moreover, an actual SRM control system is constructed at 220 V 370 W. The experiment results further prove that the proposed robust controller has excellent dynamic performance and strong robustness.

Dual fuel injection piggyback controller system

NASA Astrophysics Data System (ADS)

Muji, Siti Zarina Mohd.; Hassanal, Muhammad Amirul Hafeez; Lee, Chua King; Fawzi, Mas; Zulkifli, Fathul Hakim

2017-09-01

Dual-fuel injection is an effort to reduce the dependency on diesel and gasoline fuel. Generally, there are two approaches to implement the dual-fuel injection in car system. The first approach is changing the whole injector of the car engine, the consequence is excessive high cost. Alternatively, it also can be achieved by manipulating the system's control signal especially the Electronic Control Unit (ECU) signal. Hence, the study focuses to develop a dual injection timing controller system that likely adopted to control injection time and quantity of compressed natural gas (CNG) and diesel fuel. In this system, Raspberry Pi 3 reacts as main controller unit to receive ECU signal, analyze it and then manipulate its duty cycle to be fed into the Electronic Driver Unit (EDU). The manipulation has changed the duty cycle to two pulses instead of single pulse. A particular pulse mainly used to control injection of diesel fuel and another pulse controls injection of Compressed Natural Gas (CNG). The test indicated promising results that the system can be implemented in the car as piggyback system. This article, which was originally published online on 14 September 2017, contained an error in the acknowledgment section. The corrected acknowledgment appears in the Corrigendum attached to the pdf.

Examining relations between locus of control, loneliness, subjective well-being, and preference for online social interaction.

PubMed

Ye, Yinghua; Lin, Lin

2015-02-01

The unprecedented popularity of online communication has raised interests and concerns among the public as well as in scholarly circles. Online communications have pushed people farther away from one another. This study is a further examination of the effects of online communications on well-being, in particular: Locus of control, Loneliness, Subjective well-being, and Preference for online social interaction. Chinese undergraduate students (N = 260; 84 men, 176 women; M age = 20.1 yr., SD = 1.2) were questioned about demographic information and use of social media as well as four previously validated questionnaires related to well-being. Most participants used QQ, a popular social networking program, as the major channel for online social interactions. Locus of control was positively related to Loneliness and Preference for online social interaction, but negatively related to Subjective well-being; Loneliness (positively) and Subjective well-being (negatively) were related to Preference for online social interaction; and Loneliness and Subjective well-being had a full mediating effect between the relationships of Locus of control and Preference for online social interaction. The findings of the study showed that more lonely, unhappy, and externally controlled students were more likely to be engaged in online social interaction. Improving students' locus of control, loneliness, and happiness may help reduce problematic Internet use.

Adaptive estimation of nonlinear parameters of a nonholonomic spherical robot using a modified fuzzy-based speed gradient algorithm

NASA Astrophysics Data System (ADS)

Roozegar, Mehdi; Mahjoob, Mohammad J.; Ayati, Moosa

2017-05-01

This paper deals with adaptive estimation of the unknown parameters and states of a pendulum-driven spherical robot (PDSR), which is a nonlinear in parameters (NLP) chaotic system with parametric uncertainties. Firstly, the mathematical model of the robot is deduced by applying the Newton-Euler methodology for a system of rigid bodies. Then, based on the speed gradient (SG) algorithm, the states and unknown parameters of the robot are estimated online for different step length gains and initial conditions. The estimated parameters are updated adaptively according to the error between estimated and true state values. Since the errors of the estimated states and parameters as well as the convergence rates depend significantly on the value of step length gain, this gain should be chosen optimally. Hence, a heuristic fuzzy logic controller is employed to adjust the gain adaptively. Simulation results indicate that the proposed approach is highly encouraging for identification of this NLP chaotic system even if the initial conditions change and the uncertainties increase; therefore, it is reliable to be implemented on a real robot.

Partially supervised P300 speller adaptation for eventual stimulus timing optimization: target confidence is superior to error-related potential score as an uncertain label

NASA Astrophysics Data System (ADS)

Zeyl, Timothy; Yin, Erwei; Keightley, Michelle; Chau, Tom

2016-04-01

Objective. Error-related potentials (ErrPs) have the potential to guide classifier adaptation in BCI spellers, for addressing non-stationary performance as well as for online optimization of system parameters, by providing imperfect or partial labels. However, the usefulness of ErrP-based labels for BCI adaptation has not been established in comparison to other partially supervised methods. Our objective is to make this comparison by retraining a two-step P300 speller on a subset of confident online trials using naïve labels taken from speller output, where confidence is determined either by (i) ErrP scores, (ii) posterior target scores derived from the P300 potential, or (iii) a hybrid of these scores. We further wish to evaluate the ability of partially supervised adaptation and retraining methods to adjust to a new stimulus-onset asynchrony (SOA), a necessary step towards online SOA optimization. Approach. Eleven consenting able-bodied adults attended three online spelling sessions on separate days with feedback in which SOAs were set at 160 ms (sessions 1 and 2) and 80 ms (session 3). A post hoc offline analysis and a simulated online analysis were performed on sessions two and three to compare multiple adaptation methods. Area under the curve (AUC) and symbols spelled per minute (SPM) were the primary outcome measures. Main results. Retraining using supervised labels confirmed improvements of 0.9 percentage points (session 2, p < 0.01) and 1.9 percentage points (session 3, p < 0.05) in AUC using same-day training data over using data from a previous day, which supports classifier adaptation in general. Significance. Using posterior target score alone as a confidence measure resulted in the highest SPM of the partially supervised methods, indicating that ErrPs are not necessary to boost the performance of partially supervised adaptive classification. Partial supervision significantly improved SPM at a novel SOA, showing promise for eventual online SOA optimization.

Disclosure of Medical Errors in Oman

PubMed Central

Norrish, Mark I. K.

2015-01-01

Objectives: This study aimed to provide insight into the preferences for and perceptions of medical error disclosure (MED) by members of the public in Oman. Methods: Between January and June 2012, an online survey was used to collect responses from 205 members of the public across five governorates of Oman. Results: A disclosure gap was revealed between the respondents’ preferences for MED and perceived current MED practices in Oman. This disclosure gap extended to both the type of error and the person most likely to disclose the error. Errors resulting in patient harm were found to have a strong influence on individuals’ perceived quality of care. In addition, full disclosure was found to be highly valued by respondents and able to mitigate for a perceived lack of care in cases where medical errors led to damages. Conclusion: The perceived disclosure gap between respondents’ MED preferences and perceptions of current MED practices in Oman needs to be addressed in order to increase public confidence in the national health care system. PMID:26052463

VizieR Online Data Catalog: V and R CCD photometry of visual binaries (Abad+, 2004)

NASA Astrophysics Data System (ADS)

Abad, C.; Docobo, J. A.; Lanchares, V.; Lahulla, J. F.; Abelleira, P.; Blanco, J.; Alvarez, C.

2003-11-01

Table 1 gives relevant data for the visual binaries observed. Observations were carried out over a short period of time, therefore we assign the mean epoch (1998.58) for the totality of data. Data of individual stars are presented as average data with errors, by parameter, when various observations have been calculated, as well as the number of observations involved. Errors corresponding to astrometric relative positions between components are always present. For single observations, parameter fitting errors, specially for dx and dy parameters, have been calculated analysing the chi2 test around the minimum. Following the rules for error propagation, theta and rho errors can be estimated. Then, Table 1 shows single observation errors with an additional significant digit. When a star does not have known references, we include it in Table 2, where J2000 position and magnitudes are from the USNO-A2.0 catalogue (Monet et al., 1998, Cat. ). (2 data files).