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Sample records for adaptive robust motion

  1. Adaptive robust motion/force control of holonomic-constrained nonholonomic mobile manipulators.

    PubMed

    Li, Zhijun; Ge, Shuzhi Sam; Ming, Aiguo

    2007-06-01

    In this paper, adaptive robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The proposed control is robust not only to parameter uncertainties such as mass variations but also to external ones such as disturbances. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance and the bounded constraint force. Simulation results validate that the motion of the system converges to the desired trajectory, and the constraint force converges to the desired force.

  2. Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

    PubMed

    Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

    2015-11-01

    Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

  3. Robust Adaptive Control

    NASA Technical Reports Server (NTRS)

    Narendra, K. S.; Annaswamy, A. M.

    1985-01-01

    Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.

  4. Robust, Adaptive Radar Detection and Estimation

    DTIC Science & Technology

    2015-07-21

    AFRL-OSR-VA-TR-2015-0208 Robust, Adaptive Radar Detection and Estimation Vishal Monga PENNSYLVANIA STATE UNIVERSITY THE Final Report 07/21/2015...Robust, Adaptive Radar Detection and Estimation 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1-0333 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Monga...we develop robust estimators that can adapt to imperfect knowledge of physical constraints using an expected likelihood (EL) approach. We analyze

  5. Motion-Adaptive Depth Superresolution.

    PubMed

    Kamilov, Ulugbek S; Boufounos, Petros T

    2017-04-01

    Multi-modal sensing is increasingly becoming important in a number of applications, providing new capabilities and processing challenges. In this paper, we explore the benefit of combining a low-resolution depth sensor with a high-resolution optical video sensor, in order to provide a high-resolution depth map of the scene. We propose a new formulation that is able to incorporate temporal information and exploit the motion of objects in the video to significantly improve the results over existing methods. In particular, our approach exploits the space-time redundancy in the depth and intensity using motion-adaptive low-rank regularization. We provide experiments to validate our approach and confirm that the quality of the estimated high-resolution depth is improved substantially. Our approach can be a first component in systems using vision techniques that rely on high-resolution depth information.

  6. Robust adaptive beamforming for MIMO monopulse radar

    NASA Astrophysics Data System (ADS)

    Rowe, William; Ström, Marie; Li, Jian; Stoica, Petre

    2013-05-01

    Researchers have recently proposed a widely separated multiple-input multiple-output (MIMO) radar using monopulse angle estimation techniques for target tracking. The widely separated antennas provide improved tracking performance by mitigating complex target radar cross-section fades and angle scintillation. An adaptive array is necessary in this paradigm because the direct path from any transmitter could act as a jammer at a receiver. When the target-free covariance matrix is not available, it is critical to include robustness into the adaptive beamformer weights. This work explores methods of robust adaptive monopulse beamforming techniques for MIMO tracking radar.

  7. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  8. Robust, multidimensional mesh motion based on Monge-Kantorovich equidistribution

    SciTech Connect

    Chacon De La Rosa, Luis; Delzanno, Gian Luca; Finn, John M.

    2011-01-01

    Mesh-motion (r-refinement) grid adaptivity schemes are attractive due to their potential to minimize the numerical error for a prescribed number of degrees of freedom. However, a key roadblock to a widespread deployment of this class of techniques has been the formulation of robust, reliable mesh-motion governing principles, which (1) guarantee a solution in multiple dimensions (2D and 3D), (2) avoid grid tangling (or folding of the mesh, whereby edges of a grid cell cross somewhere in the domain), and (3) can be solved effectively and efficiently. In this study, we formulate such a mesh-motion governing principle, based on volume equidistribution via Monge-Kantorovich optimization (MK). In earlier publications [1] and [2], the advantages of this approach with regard to these points have been demonstrated for the time-independent case. In this study, we demonstrate that Monge-Kantorovich equidistribution can in fact be used effectively in a time-stepping context, and delivers an elegant solution to the otherwise pervasive problem of grid tangling in mesh-motion approaches, without resorting to ad hoc time-dependent terms (as in moving-mesh PDEs, or MMPDEs [3] and [4]). We explore two distinct r-refinement implementations of MK: the direct method, where the current mesh relates to an initial, unchanging mesh, and the sequential method, where the current mesh is related to the previous one in time. We demonstrate that the direct approach is superior with regard to mesh distortion and robustness. The properties of the approach are illustrated with a hyperbolic PDE, the advection of a passive scalar, in 2D and 3D. Velocity flow fields with and without flow shear are considered. Three-dimensional grid, time-step, and nonlinear tolerance convergence studies are presented which demonstrate the optimality of the approach.

  9. Robust, multidimensional mesh motion based on Monge-Kantorovich equidistribution

    SciTech Connect

    Delzanno, G L; Finn, J M

    2009-01-01

    Mesh-motion (r-refinement) grid adaptivity schemes are attractive due to their potential to minimize the numerical error for a prescribed number of degrees of freedom. However, a key roadblock to a widespread deployment of the technique has been the formulation of robust, reliable mesh motion governing principles, which (1) guarantee a solution in multiple dimensions (2D and 3D), (2) avoid grid tangling (or folding of the mesh, whereby edges of a grid cell cross somewhere in the domain), and (3) can be solved effectively and efficiently. In this study, we formulate such a mesh-motion governing principle, based on volume equidistribution via Monge-Kantorovich optimization (MK). In earlier publications [1, 2], the advantages of this approach in regards to these points have been demonstrated for the time-independent case. In this study, demonstrate that Monge-Kantorovich equidistribution can in fact be used effectively in a time stepping context, and delivers an elegant solution to the otherwise pervasive problem of grid tangling in mesh motion approaches, without resorting to ad-hoc time-dependent terms (as in moving-mesh PDEs, or MMPDEs [3, 4]). We explore two distinct r-refinement implementations of MK: direct, where the current mesh relates to an initial, unchanging mesh, and sequential, where the current mesh is related to the previous one in time. We demonstrate that the direct approach is superior in regards to mesh distortion and robustness. The properties of the approach are illustrated with a paradigmatic hyperbolic PDE, the advection of a passive scalar. Imposed velocity flow fields or varying vorticity levels and flow shears are considered.

  10. A decentralized adaptive robust method for chaos control.

    PubMed

    Kobravi, Hamid-Reza; Erfanian, Abbas

    2009-09-01

    This paper presents a control strategy, which is based on sliding mode control, adaptive control, and fuzzy logic system for controlling the chaotic dynamics. We consider this control paradigm in chaotic systems where the equations of motion are not known. The proposed control strategy is robust against the external noise disturbance and system parameter variations and can be used to convert the chaotic orbits not only to the desired periodic ones but also to any desired chaotic motions. Simulation results of controlling some typical higher order chaotic systems demonstrate the effectiveness of the proposed control method.

  11. Robust Adaptive Control of Hypnosis During Anesthesia

    DTIC Science & Technology

    2007-11-02

    1 of 4 ROBUST ADAPTIVE CONTROL OF HYPNOSIS DURING ANESTHESIA Pascal Grieder1, Andrea Gentilini1, Manfred Morari1, Thomas W. Schnider2 1ETH Zentrum...A closed-loop controller for hypnosis was designed and validated on humans at our laboratory. The controller aims at regulat- ing the Bispectral Index...BIS) - a surro- gate measure of hypnosis derived from the electroencephalogram of the patient - with the volatile anesthetic isoflurane administered

  12. Robust adaptive control of HVDC systems

    SciTech Connect

    Reeve, J.; Sultan, M. )

    1994-07-01

    The transient performance of an HVDC power system is highly dependent on the parameters of the current/voltage regulators of the converter controls. In order to better accommodate changes in system structure or dc operating conditions, this paper introduces a new adaptive control strategy. The advantages of automatic tuning for continuous fine tuning are combined with predetermined gain scheduling in order to achieve robustness for large disturbances. Examples are provided for a digitally simulated back-to-back dc system.

  13. Real Time & Power Efficient Adaptive - Robust Control

    NASA Astrophysics Data System (ADS)

    Ioan Gliga, Lavinius; Constantin Mihai, Cosmin; Lupu, Ciprian; Popescu, Dumitru

    2017-01-01

    A design procedure for a control system suited for dynamic variable processes is presented in this paper. The proposed adaptive - robust control strategy considers both adaptive control advantages and robust control benefits. It estimates the degradation of the system’s performances due to the dynamic variation in the process and it then utilizes it to determine when the system must be adapted with a redesign of the robust controller. A single integral criterion is used for the identification of the process, and for the design of the control algorithm, which is expressed in direct form, through a cost function defined in the space of the parameters of both the process and the controller. For the minimization of this nonlinear function, an adequate mathematical programming minimization method is used. The theoretical approach presented in this paper was validated for a closed loop control system, simulated in an application developed in C. Because of the reduced number of operations, this method is suitable for implementation on fast processes. Due to its effectiveness, it increases the idle time of the CPU, thereby saving electrical energy.

  14. Adaptive Force Control in Compliant Motion

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1994-01-01

    This paper addresses the problem of controlling a manipulator in compliant motion while in contact with an environment having an unknown stiffness. Two classes of solutions are discussed: adaptive admittance control and adaptive compliance control. In both admittance and compliance control schemes, compensator adaptation is used to ensure a stable and uniform system performance.

  15. Complex principal components for robust motion estimation.

    PubMed

    Mauldin, F William; Viola, Francesco; Walker, William F

    2010-11-01

    Bias and variance errors in motion estimation result from electronic noise, decorrelation, aliasing, and inherent algorithm limitations. Unlike most error sources, decorrelation is coherent over time and has the same power spectrum as the signal. Thus, reducing decorrelation is impossible through frequency domain filtering or simple averaging and must be achieved through other methods. In this paper, we present a novel motion estimator, termed the principal component displacement estimator (PCDE), which takes advantage of the signal separation capabilities of principal component analysis (PCA) to reject decorrelation and noise. Furthermore, PCDE only requires the computation of a single principal component, enabling computational speed that is on the same order of magnitude or faster than the commonly used Loupas algorithm. Unlike prior PCA strategies, PCDE uses complex data to generate motion estimates using only a single principal component. The use of complex echo data is critical because it allows for separation of signal components based on motion, which is revealed through phase changes of the complex principal components. PCDE operates on the assumption that the signal component of interest is also the most energetic component in an ensemble of echo data. This assumption holds in most clinical ultrasound environments. However, in environments where electronic noise SNR is less than 0 dB or in blood flow data for which the wall signal dominates the signal from blood flow, the calculation of more than one PC is required to obtain the signal of interest. We simulated synthetic ultrasound data to assess the performance of PCDE over a wide range of imaging conditions and in the presence of decorrelation and additive noise. Under typical ultrasonic elasticity imaging conditions (0.98 signal correlation, 25 dB SNR, 1 sample shift), PCDE decreased estimation bias by more than 10% and standard deviation by more than 30% compared with the Loupas method and normalized

  16. Robust adaptive kinematic control of redundant robots

    NASA Technical Reports Server (NTRS)

    Tarokh, M.; Zuck, D. D.

    1992-01-01

    The paper presents a general method for the resolution of redundancy that combines the Jacobian pseudoinverse and augmentation approaches. A direct adaptive control scheme is developed to generate joint angle trajectories for achieving desired end-effector motion as well as additional user defined tasks. The scheme ensures arbitrarily small errors between the desired and the actual motion of the manipulator. Explicit bounds on the errors are established that are directly related to the mismatch between actual and estimated pseudoinverse Jacobian matrix, motion velocity and the controller gain. It is shown that the scheme is tolerant of the mismatch and consequently only infrequent pseudoinverse computations are needed during a typical robot motion. As a result, the scheme is computationally fast, and can be implemented for real-time control of redundant robots. A method is incorporated to cope with the robot singularities allowing the manipulator to get very close or even pass through a singularity while maintaining a good tracking performance and acceptable joint velocities. Computer simulations and experimental results are provided in support of the theoretical developments.

  17. Robust, Practical Adaptive Control for Launch Vehicles

    NASA Technical Reports Server (NTRS)

    Orr, Jeb. S.; VanZwieten, Tannen S.

    2012-01-01

    A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

  18. Coordinated adaptive filters for motion simulators.

    NASA Technical Reports Server (NTRS)

    Parrish, R. V.; Dieudonne, J. E.; Bowles, R. L.; Martin, D. J.

    1973-01-01

    A new approach to providing motion drive signals to a flight simulator utilizing coordinated adaptive filters is presented. Some motivation for the use of coordinated washout is discussed, along with conditions that determine the burden of coordination. The coordinated adaptive filters are derived, based on continuous steepest descent, and the application of the filters to simulated flight data is demonstrated.

  19. Coordinated adaptive washout for motion simulators.

    NASA Technical Reports Server (NTRS)

    Parrish, R. V.; Dieudonne, J. E.; Bowles, R. L.; Martin, D. J., Jr.

    1973-01-01

    This paper introduces a new method of providing motion cues to a moving base six-degree-of-freedom flight simulator utilizing nonlinear filters. Coordinated adaptive filters, used to coordinate translational and rotational motion, are derived based on the method of continuous steepest descent, and the basic concept of the digital controllers used for the uncoordinated heave and yaw cues is also presented. The coordinated adaptive washout method is illustrated by an application in a six-degree-of-freedom fixed-base environment.

  20. On adaptive robustness approach to Anti-Jam signal processing

    NASA Astrophysics Data System (ADS)

    Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

    An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

  1. Optimal robust motion controller design using multiobjective genetic algorithm.

    PubMed

    Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor

    2014-01-01

    This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm-differential evolution.

  2. Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm

    PubMed Central

    Svečko, Rajko

    2014-01-01

    This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749

  3. Motion management with phase-adapted 4D-optimization

    NASA Astrophysics Data System (ADS)

    Nohadani, Omid; Seco, Joao; Bortfeld, Thomas

    2010-09-01

    Cancer treatment with ionizing radiation is often compromised by organ motion, in particular for lung cases. Motion uncertainties can significantly degrade an otherwise optimized treatment plan. We present a spatiotemporal optimization method, which takes into account all phases of breathing via the corresponding 4D-CTs and provides a 4D-optimal plan that can be delivered throughout all breathing phases. Monte Carlo dose calculations are employed to warrant for highest dosimetric accuracy, as pertinent to study motion effects in lung. We demonstrate the performance of this optimization method with clinical lung cancer cases and compare the outcomes to conventional gating techniques. We report significant improvements in target coverage and in healthy tissue sparing at a comparable computational expense. Furthermore, we show that the phase-adapted 4D-optimized plans are robust against irregular breathing, as opposed to gating. This technique has the potential to yield a higher delivery efficiency and a decisively shorter delivery time.

  4. Robust, Flexible Motion Control for the Mars Explorer Rovers

    NASA Technical Reports Server (NTRS)

    Maimone, Mark; Biesiadecki, Jeffrey

    2007-01-01

    The Mobility Flight Software, running on computers aboard the Mars Explorer Rover (MER) robotic vehicles Spirit and Opportunity, affords the robustness and flexibility of control to enable safe and effective operation of these vehicles in traversing natural terrain. It can make the vehicles perform specific maneuvers commanded from Earth, and/or can autonomously administer multiple aspects of mobility, including choice of motion, measurement of actual motion, and even selection of targets to be approached. Motion of a vehicle can be commanded by use of multiple layers of control, ranging from motor control at a low level, direct drive operations (e.g., motion along a circular arc, motion along a straight line, or turn in place) at an intermediate level to goal-position driving (that is, driving to a specified location) at a high level. The software can also perform high-level assessment of terrain and selection of safe paths across the terrain: this involves processing of the digital equivalent of a local traversability map generated from images acquired by stereoscopic pairs of cameras aboard the vehicles. Other functions of the software include interacting with the rest of the MER flight software and performing safety checks.

  5. Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters

    PubMed Central

    Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

    2016-01-01

    Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers. PMID:27618046

  6. Robust and sensitive video motion detection for sleep analysis.

    PubMed

    Heinrich, Adrienne; Geng, Di; Znamenskiy, Dmitry; Vink, Jelte Peter; de Haan, Gerard

    2014-05-01

    In this paper, we propose a camera-based system combining video motion detection, motion estimation, and texture analysis with machine learning for sleep analysis. The system is robust to time-varying illumination conditions while using standard camera and infrared illumination hardware. We tested the system for periodic limb movement (PLM) detection during sleep, using EMG signals as a reference. We evaluated the motion detection performance both per frame and with respect to movement event classification relevant for PLM detection. The Matthews correlation coefficient improved by a factor of 2, compared to a state-of-the-art motion detection method, while sensitivity and specificity increased with 45% and 15%, respectively. Movement event classification improved by a factor of 6 and 3 in constant and highly varying lighting conditions, respectively. On 11 PLM patient test sequences, the proposed system achieved a 100% accurate PLM index (PLMI) score with a slight temporal misalignment of the starting time (<1 s) regarding one movement. We conclude that camera-based PLM detection during sleep is feasible and can give an indication of the PLMI score.

  7. Adaptive motion artifact reducing algorithm for wrist photoplethysmography application

    NASA Astrophysics Data System (ADS)

    Zhao, Jingwei; Wang, Guijin; Shi, Chenbo

    2016-04-01

    Photoplethysmography (PPG) technology is widely used in wearable heart pulse rate monitoring. It might reveal the potential risks of heart condition and cardiopulmonary function by detecting the cardiac rhythms in physical exercise. However the quality of wrist photoelectric signal is very sensitive to motion artifact since the thicker tissues and the fewer amount of capillaries. Therefore, motion artifact is the major factor that impede the heart rate measurement in the high intensity exercising. One accelerometer and three channels of light with different wavelengths are used in this research to analyze the coupled form of motion artifact. A novel approach is proposed to separate the pulse signal from motion artifact by exploiting their mixing ratio in different optical paths. There are four major steps of our method: preprocessing, motion artifact estimation, adaptive filtering and heart rate calculation. Five healthy young men are participated in the experiment. The speeder in the treadmill is configured as 12km/h, and all subjects would run for 3-10 minutes by swinging the arms naturally. The final result is compared with chest strap. The average of mean square error (MSE) is less than 3 beats per minute (BPM/min). Proposed method performed well in intense physical exercise and shows the great robustness to individuals with different running style and posture.

  8. An improved robust blind motion de-blurring algorithm for remote sensing images

    NASA Astrophysics Data System (ADS)

    He, Yulong; Liu, Jin; Liang, Yonghui

    2016-10-01

    Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

  9. Estimating nonrigid motion from inconsistent intensity with robust shape features

    SciTech Connect

    Liu, Wenyang; Ruan, Dan

    2013-12-15

    Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided

  10. Robustness of Adaptive Testing to Multidimensionality.

    ERIC Educational Resources Information Center

    Weiss, David J.; Suhadolnik, Debra

    The present monte carlo simulation study was designed to examine the effects of multidimensionality during the administration of computerized adaptive testing (CAT). It was assumed that multidimensionality existed in the individuals to whom test items were being administered, i.e., that the correct or incorrect responses given by an individual…

  11. Robust adaptive control of MEMS triaxial gyroscope using fuzzy compensator.

    PubMed

    Fei, Juntao; Zhou, Jian

    2012-12-01

    In this paper, a robust adaptive control strategy using a fuzzy compensator for MEMS triaxial gyroscope, which has system nonlinearities, including model uncertainties and external disturbances, is proposed. A fuzzy logic controller that could compensate for the model uncertainties and external disturbances is incorporated into the adaptive control scheme in the Lyapunov framework. The proposed adaptive fuzzy controller can guarantee the convergence and asymptotical stability of the closed-loop system. The proposed adaptive fuzzy control strategy does not depend on accurate mathematical models, which simplifies the design procedure. The innovative development of intelligent control methods incorporated with conventional control for the MEMS gyroscope is derived with the strict theoretical proof of the Lyapunov stability. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control scheme and demonstrate the satisfactory tracking performance and robustness against model uncertainties and external disturbances compared with conventional adaptive control method.

  12. Robust adaptive regulation without persistent excitation

    NASA Technical Reports Server (NTRS)

    Lozano-Leal, Rogelio

    1989-01-01

    A globally convergent adaptive regulator for minimum- or nonminimum-phase systems subject to bounded disturbances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least-Squares identification algorithm a with dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given.

  13. Robust Wiener filtering for Adaptive Optics

    SciTech Connect

    Poyneer, L A

    2004-06-17

    In many applications of optical systems, the observed field in the pupil plane has a non-uniform phase component. This deviation of the phase of the field from uniform is called a phase aberration. In imaging systems this aberration will degrade the quality of the images. In the case of a large astronomical telescope, random fluctuations in the atmosphere lead to significant distortion. These time-varying distortions can be corrected using an Adaptive Optics (AO) system, which is a real-time control system composed of optical, mechanical and computational parts. Adaptive optics is also applicable to problems in vision science, laser propagation and communication. For a high-level overview, consult this web site. For an in-depth treatment of the astronomical case, consult these books.

  14. Robust adaptive regulation without persistent excitation

    NASA Technical Reports Server (NTRS)

    Lozano-Leal, Rogelio

    1988-01-01

    A globally convergent adaptive regulator for minimum or nonminimum phase systems subject to bounded distrubances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the new representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least Squares identification algorithm with a dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given.

  15. 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.

  16. Robust Adaptive Data Encoding and Restoration

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.; Rahman, Zia-ur; Halyo, Nesim

    2000-01-01

    This is the final report for NASA cooperative agreement and covers the period from 01 October, 1997 to 11 April, 2000. The research during this period was performed in three primary, but related, areas. 1. Evaluation of integrated information adaptive imaging. 2. Improvements in memory utilization and performance of the multiscale retinex with color restoration (MSRCR). 3. Commencement of a theoretical study to evaluate the non-linear retinex image enhancement technique. The research resulted in several publications, and an intellectual property disclosure to the NASA patent council in May, 1999.

  17. Robust cascade control for the horizontal motion of a vehicle with single-wheel actuators

    NASA Astrophysics Data System (ADS)

    Moseberg, Jan-Erik; Roppenecker, Günter

    2015-12-01

    The article presents a cascade control for the horizontal motion of a vehicle with single-wheel actuators. The outer control loop for the longitudinal and lateral accelerations and the yaw rate ensures a desired vehicle motion. By a combination of state feedback control and observer-based disturbance feedforward the inner control loop robustly stabilises the rotating and steering motions of the wheels in spite of unknown frictions between tyres and ground. Since the three degrees of freedom of the horizontal motion are affected by eight tyre forces, the vehicle considered is an over-actuated system. Thus additional control objectives can be realised besides the desired motion trajectory as, for example, a maximum in driving safety. The corresponding analytical tyre force allocation also guarantees real-time capability because of its relatively low computational effort. Provided suitable fault detection and isolation are available, the proposed cascade control has the potential of fault-tolerance, because the force allocation is adaptable. Another benefit results from the modular control structure, because it allows a stepwise implementation. Besides, it only requires a small number of measurements for control purposes. These measurements are the rotational speeds and steering angles of the wheels, the longitudinal and lateral acceleration and the yaw rate of the vehicle.

  18. Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

    PubMed

    Chen, Tien-Chi; Yu, Chih-Hsien

    2009-07-01

    A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

  19. Differential effect of visual motion adaption upon visual cortical excitability.

    PubMed

    Lubeck, Astrid J A; Van Ombergen, Angelique; Ahmad, Hena; Bos, Jelte E; Wuyts, Floris L; Bronstein, Adolfo M; Arshad, Qadeer

    2017-03-01

    The objectives of this study were 1) to probe the effects of visual motion adaptation on early visual and V5/MT cortical excitability and 2) to investigate whether changes in cortical excitability following visual motion adaptation are related to the degree of visual dependency, i.e., an overreliance on visual cues compared with vestibular or proprioceptive cues. Participants were exposed to a roll motion visual stimulus before, during, and after visual motion adaptation. At these stages, 20 transcranial magnetic stimulation (TMS) pulses at phosphene threshold values were applied over early visual and V5/MT cortical areas from which the probability of eliciting a phosphene was calculated. Before and after adaptation, participants aligned the subjective visual vertical in front of the roll motion stimulus as a marker of visual dependency. During adaptation, early visual cortex excitability decreased whereas V5/MT excitability increased. After adaptation, both early visual and V5/MT excitability were increased. The roll motion-induced tilt of the subjective visual vertical (visual dependence) was not influenced by visual motion adaptation and did not correlate with phosphene threshold or visual cortex excitability. We conclude that early visual and V5/MT cortical excitability is differentially affected by visual motion adaptation. Furthermore, excitability in the early or late visual cortex is not associated with an increase in visual reliance during spatial orientation. Our findings complement earlier studies that have probed visual cortical excitability following motion adaptation and highlight the differential role of the early visual cortex and V5/MT in visual motion processing.NEW & NOTEWORTHY We examined the influence of visual motion adaptation on visual cortex excitability and found a differential effect in V1/V2 compared with V5/MT. Changes in visual excitability following motion adaptation were not related to the degree of an individual's visual dependency.

  20. Guidance and adaptive-robust attitude & orbit control of a small information satellite

    NASA Astrophysics Data System (ADS)

    Somov, Ye.; Butyrin, S.; Somov, S.; Somova, T.; Testoyedov, N.; Rayevsky, V.; Titov, G.; Yakimov, Ye.; Ovchinnikov, A.; Mathylenko, M.

    2017-01-01

    We consider a small information satellite which may be placed on an orbit with altitude from 600 up to 1000 km. The satellite attitude and orbit control system contains a strap-down inertial navigation system, cluster of four reaction wheels, magnetic driver and a correcting engine unit with eight electro-reaction engines. We study problems on design of algorithms for spatial guidance, in-flight identification and adaptive-robust control of the satellite motion on sun-synchronous orbit.

  1. Adaptation to real motion reveals direction-selective interactions between real and implied motion processing.

    PubMed

    Lorteije, Jeannette A M; Kenemans, J Leon; Jellema, Tjeerd; van der Lubbe, Rob H J; Lommers, Marjolein W; van Wezel, Richard J A

    2007-08-01

    Viewing static pictures of running humans evokes neural activity in the dorsal motion-sensitive cortex. To establish whether this response arises from direction-selective neurons that are also involved in real motion processing, we measured the visually evoked potential to implied motion following adaptation to static or moving random dot patterns. The implied motion response was defined as the difference between evoked potentials to pictures with and without implied motion. Interaction between real and implied motion was found as a modulation of this difference response by the preceding motion adaptation. The amplitude of the implied motion response was significantly reduced after adaptation to motion in the same direction as the implied motion, compared to motion in the opposite direction. At 280 msec after stimulus onset, the average difference in amplitude reduction between opposite and same adapted direction was 0.5 muV on an average implied motion amplitude of 2.0 muV. These results indicate that the response to implied motion arises from direction-selective motion-sensitive neurons. This is consistent with interactions between real and implied motion processing at a neuronal level.

  2. Robust design of configurations and parameters of adaptable products

    NASA Astrophysics Data System (ADS)

    Zhang, Jian; Chen, Yongliang; Xue, Deyi; Gu, Peihua

    2014-03-01

    An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

  3. Monocular motion adaptation affects the perceived trajectory of stereomotion

    NASA Technical Reports Server (NTRS)

    Brooks, Kevin R.

    2002-01-01

    Perceived stereomotion trajectory was measured before and after adaptation to lateral motion in the dominant or nondominant eye to assess the relative contributions of 2 cues: changing disparity and interocular velocity difference. Perceived speed for monocular lateral motion and perceived binocular visual direction (BVD) was also assessed. Unlike stereomotion trajectory perception, the BVD of static targets showed an ocular dominance bias, even without adaptation. Adaptation caused equivalent biases in perceived trajectory and monocular motion speed, without significantly affecting perceived BVD. Predictions from monocular motion data closely match trajectory perception data, unlike those from BVD sources. The results suggest that the interocular velocity differences make a significant contribution to stereomotion trajectory perception.

  4. Robust time and frequency domain estimation methods in adaptive control

    NASA Technical Reports Server (NTRS)

    Lamaire, Richard Orville

    1987-01-01

    A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

  5. Robust adaptive dynamic programming and feedback stabilization of nonlinear systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-05-01

    This paper studies the robust optimal control design for a class of uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (RADP). The objective is to fill up a gap in the past literature of adaptive dynamic programming (ADP) where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The proposed RADP methodology can be viewed as an extension of ADP to uncertain nonlinear systems. Practical learning algorithms are developed in this paper, and have been applied to the controller design problems for a jet engine and a one-machine power system.

  6. Robust local search for spacecraft operations using adaptive noise

    NASA Technical Reports Server (NTRS)

    Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve

    2004-01-01

    Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

  7. Robust, multidimensional mesh-motion based on Monge-Kantorovich equidistribution

    NASA Astrophysics Data System (ADS)

    Chacón, L.; Delzanno, G. L.; Finn, J. M.

    2011-01-01

    Mesh-motion (r-refinement) grid adaptivity schemes are attractive due to their potential to minimize the numerical error for a prescribed number of degrees of freedom. However, a key roadblock to a widespread deployment of this class of techniques has been the formulation of robust, reliable mesh-motion governing principles, which (1) guarantee a solution in multiple dimensions (2D and 3D), (2) avoid grid tangling (or folding of the mesh, whereby edges of a grid cell cross somewhere in the domain), and (3) can be solved effectively and efficiently. In this study, we formulate such a mesh-motion governing principle, based on volume equidistribution via Monge-Kantorovich optimization (MK). In earlier publications [1,2], the advantages of this approach with regard to these points have been demonstrated for the time-independent case. In this study, we demonstrate that Monge-Kantorovich equidistribution can in fact be used effectively in a time-stepping context, and delivers an elegant solution to the otherwise pervasive problem of grid tangling in mesh-motion approaches, without resorting to ad hoc time-dependent terms (as in moving-mesh PDEs, or MMPDEs [3,4]). We explore two distinct r-refinement implementations of MK: the direct method, where the current mesh relates to an initial, unchanging mesh, and the sequential method, where the current mesh is related to the previous one in time. We demonstrate that the direct approach is superior with regard to mesh distortion and robustness. The properties of the approach are illustrated with a hyperbolic PDE, the advection of a passive scalar, in 2D and 3D. Velocity flow fields with and without flow shear are considered. Three-dimensional grid, time-step, and nonlinear tolerance convergence studies are presented which demonstrate the optimality of the approach.

  8. Robust, multidimensional mesh-motion based on Monge-Kantorovich equidistribution

    SciTech Connect

    Chacon De La Rosa, Luis; Delzanno, Gian Luca; Finn, John M.

    2011-01-01

    Mesh-motion (r-refinement) grid adaptivity schemes are attractive due to their potential to minimize the numerical error for a prescribed number of degrees of freedom. However, a key roadblock to a widespread deployment of this class of techniques has been the formulation of robust, reliable mesh-motion governing principles, which (1) guarantee a solution in multiple dimensions (2D and 3D), (2) avoid grid tangling (or folding of the mesh, whereby edges of a grid cell cross somewhere in the domain), and (3) can be solved effectively and efficiently. In this study, we formulate such a mesh-motion governing principle, based on volume equidistribution via Monge-Kantorovich optimization (MK). In earlier publications [1,2], the advantages of this approach with regard to these points have been demonstrated for the time-independent case. In this study, we demonstrate that Monge-Kantorovich equidistribution can in fact be used effectively in a time-stepping context, and delivers an elegant solution to the otherwise pervasive problem of grid tangling in mesh-motion approaches, without resorting to ad hoc time-dependent terms (as in moving-mesh PDEs, or MMPDEs [3,4]). We explore two distinct r-refinement implementations of MK: the direct method, where the current mesh relates to an initial, unchanging mesh, and the sequential method, where the current mesh is related to the previous one in time. We demonstrate that the direct approach is superior with regard to mesh distortion and robustness. The properties of the approach are illustrated with a hyperbolic PDE, the advection of a passive scalar, in 20 and 3D. Velocity flow fields with and without flow shear are considered. Three-dimensional grid, time-step, and nonlinear tolerance convergence studies are presented which demonstrate the optimality of the approach.

  9. Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

    PubMed Central

    Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

    2016-01-01

    Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information. PMID:27304526

  10. Adaptive and robust radiation therapy in the presence of drift

    NASA Astrophysics Data System (ADS)

    Mar, Philip Allen; Chan, Timothy C. Y.

    2015-05-01

    Combining adaptive and robust optimization in radiation therapy has the potential to mitigate the negative effects of both intrafraction and interfraction uncertainty over a fractionated treatment course. A previously developed adaptive and robust radiation therapy (ARRT) method for lung cancer was demonstrated to be effective when the sequence of breathing patterns was well-behaved. In this paper, we examine the applicability of the ARRT method to less well-behaved breathing patterns. We develop a novel method to generate sequences of probability mass functions that represent different types of drift in the underlying breathing pattern. Computational results derived from applying the ARRT method to these sequences demonstrate that the ARRT method is effective for a much broader class of breathing patterns than previously demonstrated.

  11. Variable Neural Adaptive Robust Control: A Switched System Approach

    SciTech Connect

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  12. Decentralized adaptive control of robot manipulators with robust stabilization design

    NASA Technical Reports Server (NTRS)

    Yuan, Bau-San; Book, Wayne J.

    1988-01-01

    Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.

  13. Robustness of channel-adapted quantum error correction

    SciTech Connect

    Ballo, Gabor; Gurin, Peter

    2009-07-15

    A quantum channel models the interaction between the system we are interested in and its environment. Such a model can capture the main features of the interaction, but, because of the complexity of the environment, we cannot assume that it is fully accurate. We study the robustness of quantum error correction operations against completely unexpected and subsequently undetermined type of channel uncertainties. We find that a channel-adapted optimal error correction operation does not only give the best possible channel fidelity but it is more robust against channel alterations than any other error correction operation. Our results are valid for Pauli channels and stabilizer codes, but based on some numerical results, we believe that very similar conclusions can be drawn also in the general case.

  14. 6-DOF robust adaptive terminal sliding mode control for spacecraft formation flying

    NASA Astrophysics Data System (ADS)

    Wang, Jianying; Sun, Zhaowei

    2012-04-01

    This paper addresses the tracking control problem of the leader-follower spacecraft formation, by which we mean that the relative motion between the leader and the follower is required to track a desired time-varying trajectory given in advance. Using dual number, the six-degree-of-freedom motion of the follower spacecraft relative to the leader spacecraft is modeled, where the coupling effect between the translational motion and the rotational one is accounted. A robust adaptive terminal sliding mode control law, including the adaptive algorithms, is proposed to ensure the finite time convergence of the relative motion tracking errors despite the presence of model uncertainties and external disturbances, based on which a modified controller is furthermore developed to solve the dual-equilibrium problem caused by dual quaternion representation. In addition, to alleviate the chattering, hyperbolic tangent function is adopted to substitute for the sign function. And by theoretical analysis, it is proved that the tracking error in such case will converge to a neighborhood of the origin in finite time. Finally, numerical simulations are performed to demonstrate the validity of the proposed approaches.

  15. Effects of Crowding and Attention on High-Levels of Motion Processing and Motion Adaptation

    PubMed Central

    Pavan, Andrea; Greenlee, Mark W.

    2015-01-01

    The motion after-effect (MAE) persists in crowding conditions, i.e., when the adaptation direction cannot be reliably perceived. The MAE originating from complex moving patterns spreads into non-adapted sectors of a multi-sector adapting display (i.e., phantom MAE). In the present study we used global rotating patterns to measure the strength of the conventional and phantom MAEs in crowded and non-crowded conditions, and when attention was directed to the adapting stimulus and when it was diverted away from the adapting stimulus. The results show that: (i) the phantom MAE is weaker than the conventional MAE, for both non-crowded and crowded conditions, and when attention was focused on the adapting stimulus and when it was diverted from it, (ii) conventional and phantom MAEs in the crowded condition are weaker than in the non-crowded condition. Analysis conducted to assess the effect of crowding on high-level of motion adaptation suggests that crowding is likely to affect the awareness of the adapting stimulus rather than degrading its sensory representation, (iii) for high-level of motion processing the attentional manipulation does not affect the strength of either conventional or phantom MAEs, neither in the non-crowded nor in the crowded conditions. These results suggest that high-level MAEs do not depend on attention and that at high-level of motion adaptation the effects of crowding are not modulated by attention. PMID:25615577

  16. Adaptive motion mapping in pancreatic SBRT patients using Fourier transforms

    PubMed Central

    Jones, Bernard L.; Schefter, Tracey; Miften, Moyed

    2015-01-01

    Background and Purpose Recent studies suggest that 4DCT is unable to accurately measure respiratory-induced pancreatic tumor motion. In this work, we assessed the daily motion of pancreatic tumors treated with SBRT, and developed adaptive strategies to predict and account for this motion. Materials and Methods The daily motion trajectory of pancreatic tumors during CBCT acquisition was calculated using a model which reconstructs the instantaneous 3D position in each 2D CBCT projection image. We developed a metric (termed “Spectral Coherence,” SC) based on the Fourier frequency spectrum of motion in the SI direction, and analyzed the ability of SC to predict motion-based errors and classify patients according to motion characteristics. Results The amplitude of daily motion exceeded the predictions of pre-treatment 4DCT imaging by an average of 3.0 mm, 2.3 mm, and 3.5 mm in the AP/LR/SI directions. SC was correlated with daily motion differences and tumor dose coverage. In a simulated adaptive protocol, target margins were adjusted based on SC, resulting in significant increases in mean target D95, D99, and minimum dose. Conclusions Our Fourier-based approach differentiates between consistent and inconsistent motion characteristics of respiration and correlates with daily motion deviations from pre-treatment 4DCT. The feasibility of an SC-based adaptive protocol was demonstrated, and this patient-specific respiratory information was used to improve target dosimetry by expanding coverage in inconsistent breathers while shrinking treatment volumes in consistent breathers. PMID:25890573

  17. Robust visual tracking via adaptive kernelized correlation filter

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Wang, Desheng; Liao, Qingmin

    2016-10-01

    Correlation filter based trackers have proved to be very efficient and robust in object tracking with a notable performance competitive with state-of-art trackers. In this paper, we propose a novel object tracking method named Adaptive Kernelized Correlation Filter (AKCF) via incorporating Kernelized Correlation Filter (KCF) with Structured Output Support Vector Machines (SOSVM) learning method in a collaborative and adaptive way, which can effectively handle severe object appearance changes with low computational cost. AKCF works by dynamically adjusting the learning rate of KCF and reversely verifies the intermediate tracking result by adopting online SOSVM classifier. Meanwhile, we bring Color Names in this formulation to effectively boost the performance owing to its rich feature information encoded. Experimental results on several challenging benchmark datasets reveal that our approach outperforms numerous state-of-art trackers.

  18. Robust adaptive backstepping control for piezoelectric nano-manipulating systems

    NASA Astrophysics Data System (ADS)

    Zhang, Yangming; Yan, Peng; Zhang, Zhen

    2017-01-01

    In this paper we present a systematic modeling and control approach for nano-manipulations of a two-dimensional PZT (piezoelectric transducer) actuated servo stage. The major control challenges associated with piezoelectric nano-manipulators typically include the nonlinear dynamics of hysteresis, model uncertainties, and various disturbances. The adverse effects of these complications will result in significant performance loss, unless effectively eliminated. The primary goal of the paper is on the ultra high precision control of such systems by handling various model uncertainties and disturbances simultaneously. To this end, a novel robust adaptive backstepping-like control approach is developed such that parametric uncertainties can be estimated adaptively while the nonlinear dynamics and external disturbances are treated as bounded disturbances for robust elimination. Meanwhile, the L2-gain of the closed-loop system is considered, and an H∞ optimization problem is formulated to improve the tracking accuracy. Numerical simulations and real time experiments are finally conducted, which significantly outperform conventional PID methods and achieve around 1% tracking error for circular contouring tasks.

  19. Robust adaptive backstepping control for reentry reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Wu, Zhong; Du, Yijiang

    2016-09-01

    During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.

  20. Unbiased measures of interocular transfer of motion adaptation.

    PubMed

    Vilidaité, Greta; Baker, Daniel H

    2015-01-01

    Numerous studies have measured the extent to which motion aftereffects transfer interocularly. However, many have done so using bias-prone methods, and studies rarely compare different types of motion directly. Here, we use a technique designed to reduce bias (Morgan, 2013, Journal of Vision, 13(8):26, 1-11) to estimate interocular transfer (IOT) for five types of motion: simple translational motion, expansion/contraction, rotation, spiral, and complex translational motion. We used both static and dynamic targets with subjects making binary judgments of perceived speed. Overall, the average IOT was 65%, consistent with previous studies (mean over 17 studies of 67% transfer). There was a main effect of motion type, with translational motion producing stronger IOT (mean: 86%) overall than any of the more complex varieties of motion (mean: 51%). This is inconsistent with the notion that IOT should be strongest for motion processed in extrastriate regions that are fully binocular. We conclude that adaptation is a complex phenomenon too poorly understood to make firm inferences about the binocular structure of motion systems.

  1. Adaptation to vection-induced symptoms of motion sickness

    NASA Technical Reports Server (NTRS)

    Stern, Robert M.; Hu, Senqi; Vasey, Michael W.; Koch, Kenneth L.

    1989-01-01

    The effects of repeated exposures to a rotating circular vection drum on the symptoms of motion sickness and tachygastria in humans were investigated. Subjects were sitting in a drum and were exposed to 15 min baseline (no rotation), followed by 15 min drum rotation at 60 deg/s, and, then, by 15 min recovery. Gastric myoelectric activity was continuously recorded with the electrogastrogram. Subjects who were exposed to the drum three times with intervals of 4-24 days all showed symptoms of tachygastria and failed to show an amelioration of motion sickness symptoms. On the other hand subjects who had only 48 h between the three sessions of drum exposure, experienced a reduction in motion-sickness symptoms and in tachygastsria upon repeated exposure to the drum, indicating that training effected a symptomatic and physiological adaptation. It is suggested that preflight adaptation to visual-vestibular sensory mismatch may reduce motion sickness in astronauts.

  2. Human motor adaptation in whole body motion

    PubMed Central

    Babič, Jan; Oztop, Erhan; Kawato, Mitsuo

    2016-01-01

    The main role of the sensorimotor system of an organism is to increase the survival of the species. Therefore, to understand the adaptation and optimality mechanisms of motor control, it is necessary to study the sensorimotor system in terms of ecological fitness. We designed an experimental paradigm that exposed sensorimotor system to risk of injury. We studied human subjects performing uncon- strained squat-to-stand movements that were systematically subjected to non-trivial perturbation. We found that subjects adapted by actively compensating the perturbations, converging to movements that were different from their normal unperturbed squat-to-stand movements. Furthermore, the adapted movements had clear intrinsic inter-subject differences which could be explained by different adapta- tion strategies employed by the subjects. These results suggest that classical optimality measures of physical energy and task satisfaction should be seen as part of a hierarchical organization of optimality with safety being at the highest level. Therefore, in addition to physical energy and task fulfillment, the risk of injury and other possible costs such as neural computational overhead have to be considered when analyzing human movement. PMID:27608652

  3. Robust adaptive cruise control of high speed trains.

    PubMed

    Faieghi, Mohammadreza; Jalali, Aliakbar; Mashhadi, Seyed Kamal-e-ddin Mousavi

    2014-03-01

    The cruise control problem of high speed trains in the presence of unknown parameters and external disturbances is considered. In particular a Lyapunov-based robust adaptive controller is presented to achieve asymptotic tracking and disturbance rejection. The system under consideration is nonlinear, MIMO and non-minimum phase. To deal with the limitations arising from the unstable zero-dynamics we do an output redefinition such that the zero-dynamics with respect to new outputs becomes stable. Rigorous stability analyses are presented which establish the boundedness of all the internal states and simultaneously asymptotic stability of the tracking error dynamics. The results are presented for two common configurations of high speed trains, i.e. the DD and PPD designs, based on the multi-body model and are verified by several numerical simulations.

  4. Adaptation-Induced Compression of Event Time Occurs Only for Translational Motion.

    PubMed

    Fornaciai, Michele; Arrighi, Roberto; Burr, David C

    2016-03-22

    Adaptation to fast motion reduces the perceived duration of stimuli displayed at the same location as the adapting stimuli. Here we show that the adaptation-induced compression of time is specific for translational motion. Adaptation to complex motion, either circular or radial, did not affect perceived duration of subsequently viewed stimuli. Adaptation with multiple patches of translating motion caused compression of duration only when the motion of all patches was in the same direction. These results show that adaptation-induced compression of event-time occurs only for uni-directional translational motion, ruling out the possibility that the neural mechanisms of the adaptation occur at early levels of visual processing.

  5. Adaptive Force Control For Compliant Motion Of A Robot

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1995-01-01

    Two adaptive control schemes offer robust solutions to problem of stable control of forces of contact between robotic manipulator and objects in its environment. They are called "adaptive admittance control" and "adaptive compliance control." Both schemes involve use of force-and torque sensors that indicate contact forces. These schemes performed well when tested in computational simulations in which they were used to control seven-degree-of-freedom robot arm in executing contact tasks. Choice between admittance or compliance control is dictated by requirements of the application at hand.

  6. Robust observer-based adaptive fuzzy sliding mode controller

    NASA Astrophysics Data System (ADS)

    Oveisi, Atta; Nestorović, Tamara

    2016-08-01

    In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

  7. Nonlinear mode decomposition: a noise-robust, adaptive decomposition method.

    PubMed

    Iatsenko, Dmytro; McClintock, Peter V E; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool-nonlinear mode decomposition (NMD)-which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques-which, together with the adaptive choice of their parameters, make it extremely noise robust-and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

  8. Robustness via Run-Time Adaptation of Contingent Plans

    NASA Technical Reports Server (NTRS)

    Bresina, John L.; Washington, Richard; Norvig, Peter (Technical Monitor)

    2000-01-01

    In this paper, we discuss our approach to making the behavior of planetary rovers more robust for the purpose of increased productivity. Due to the inherent uncertainty in rover exploration, the traditional approach to rover control is conservative, limiting the autonomous operation of the rover and sacrificing performance for safety. Our objective is to increase the science productivity possible within a single uplink by allowing the rover's behavior to be specified with flexible, contingent plans and by employing dynamic plan adaptation during execution. We have deployed a system exhibiting flexible, contingent execution; this paper concentrates on our ongoing efforts on plan adaptation, Plans can be revised in two ways: plan steps may be deleted, with execution continuing with the plan suffix; and the current plan may be merged with an "alternate plan" from an on-board library. The plan revision action is chosen to maximize the expected utility of the plan. Plan merging and action deletion constitute a more conservative general-purpose planning system; in return, our approach is more efficient and more easily verified, two important criteria for deployed rovers.

  9. Adaptation disrupts motion integration in the primate dorsal stream

    PubMed Central

    Patterson, Carlyn A.; Wissig, Stephanie C.; Kohn, Adam

    2014-01-01

    Summary Sensory systems adjust continuously to the environment. The effects of recent sensory experience—or adaptation—are typically assayed by recording in a relevant subcortical or cortical network. However, adaptation effects cannot be localized to a single, local network. Adjustments in one circuit or area will alter the input provided to others, with unclear consequences for computations implemented in the downstream circuit. Here we show that prolonged adaptation with drifting gratings, which alters responses in the early visual system, impedes the ability of area MT neurons to integrate motion signals in plaid stimuli. Perceptual experiments reveal a corresponding loss of plaid coherence. A simple computational model shows how the altered representation of motion signals in early cortex can derail integration in MT. Our results suggest that the effects of adaptation cascade through the visual system, derailing the downstream representation of distinct stimulus attributes. PMID:24507198

  10. Motion-guided attention promotes adaptive communications during social navigation

    PubMed Central

    Lemasson, B. H.; Anderson, J. J.; Goodwin, R. A.

    2013-01-01

    Animals are capable of enhanced decision making through cooperation, whereby accurate decisions can occur quickly through decentralized consensus. These interactions often depend upon reliable social cues, which can result in highly coordinated activities in uncertain environments. Yet information within a crowd may be lost in translation, generating confusion and enhancing individual risk. As quantitative data detailing animal social interactions accumulate, the mechanisms enabling individuals to rapidly and accurately process competing social cues remain unresolved. Here, we model how motion-guided attention influences the exchange of visual information during social navigation. We also compare the performance of this mechanism to the hypothesis that robust social coordination requires individuals to numerically limit their attention to a set of n-nearest neighbours. While we find that such numerically limited attention does not generate robust social navigation across ecological contexts, several notable qualities arise from selective attention to motion cues. First, individuals can instantly become a local information hub when startled into action, without requiring changes in neighbour attention level. Second, individuals can circumvent speed–accuracy trade-offs by tuning their motion thresholds. In turn, these properties enable groups to collectively dampen or amplify social information. Lastly, the minority required to sway a group's short-term directional decisions can change substantially with social context. Our findings suggest that motion-guided attention is a fundamental and efficient mechanism underlying collaborative decision making during social navigation. PMID:23325772

  11. Robust ego-motion estimation and 3-D model refinement using surface parallax.

    PubMed

    Agrawal, Amit; Chellappa, Rama

    2006-05-01

    We present an iterative algorithm for robustly estimating the ego-motion and refining and updating a coarse depth map using parametric surface parallax models and brightness derivatives extracted from an image pair. Given a coarse depth map acquired by a range-finder or extracted from a digital elevation map (DEM), ego-motion is estimated by combining a global ego-motion constraint and a local brightness constancy constraint. Using the estimated camera motion and the available depth estimate, motion of the three-dimensional (3-D) points is compensated. We utilize the fact that the resulting surface parallax field is an epipolar field, and knowing its direction from the previous motion estimates, estimate its magnitude and use it to refine the depth map estimate. The parallax magnitude is estimated using a constant parallax model (CPM) which assumes a smooth parallax field and a depth based parallax model (DBPM), which models the parallax magnitude using the given depth map. We obtain confidence measures for determining the accuracy of the estimated depth values which are used to remove regions with potentially incorrect depth estimates for robustly estimating ego-motion in subsequent iterations. Experimental results using both synthetic and real data (both indoor and outdoor sequences) illustrate the effectiveness of the proposed algorithm.

  12. Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

    NASA Astrophysics Data System (ADS)

    Kesrarat, Darun; Patanavijit, Vorapoj

    2017-02-01

    In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

  13. A robust adaptive load frequency control for micro-grids.

    PubMed

    Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede; Davari, Pooya; Dragicevic, Tomislav

    2016-11-01

    The goal of this study is to introduce a novel robust load frequency control (LFC) strategy for micro-grid(s) (MG(s)) in islanded mode operation. Admittedly, power generators in MG(s) cannot supply steady electric power output and sometimes cause unbalance between supply and demand. Battery energy storage system (BESS) is one of the effective solutions to these problems. Due to the high cost of the BESS, a new idea of Vehicle-to-Grid (V2G) is that a battery of Electric-Vehicle (EV) can be applied as a tantamount large-scale BESS in MG(s). As a result, a new robust control strategy for an islanded micro-grid (MG) is introduced that can consider electric vehicles׳ (EV(s)) effect. Moreover, in this paper, a new combination of the General Type II Fuzzy Logic Sets (GT2FLS) and the Modified Harmony Search Algorithm (MHSA) technique is applied for adaptive tuning of proportional-integral (PI) controller. Implementing General Type II Fuzzy Systems is computationally expensive. However, using a recently introduced α-plane representation, GT2FLS can be seen as a composition of several Interval Type II Fuzzy Logic Systems (IT2FLS) with a corresponding level of α for each. Real-data from an offshore wind farm in Sweden and solar radiation data in Aberdeen (United Kingdom) was used in order to examine the performance of the proposed novel controller. A comparison is made between the achieved results of Optimal Fuzzy-PI (OFPI) controller and those of Optimal Interval Type II Fuzzy-PI (IT2FPI) controller, which are of most recent advances in the area at hand. The Simulation results prove the successfulness and effectiveness of the proposed controller.

  14. Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems.

    PubMed

    Zhang, Zhengbo; Silva, Ikaro; Wu, Dalei; Zheng, Jiewen; Wu, Hao; Wang, Weidong

    2014-12-01

    Wearable healthcare monitoring systems (WHMSs) have received significant interest from both academia and industry with the advantage of non-intrusive and ambulatory monitoring. The aim of this paper is to investigate the use of an adaptive filter to reduce motion artefact (MA) in physiological signals acquired by WHMSs. In our study, a WHMS is used to acquire ECG, respiration and triaxial accelerometer (ACC) signals during incremental treadmill and cycle ergometry exercises. With these signals, performances of adaptive MA cancellation are evaluated in both respiration and ECG signals. To achieve effective and robust MA cancellation, three axial outputs of the ACC are employed to estimate the MA by a bank of gradient adaptive Laguerre lattice (GALL) filter, and the outputs of the GALL filters are further combined with time-varying weights determined by a Kalman filter. The results show that for the respiratory signals, MA component can be reduced and signal quality can be improved effectively (the power ratio between the MA-corrupted respiratory signal and the adaptive filtered signal was 1.31 in running condition, and the corresponding signal quality was improved from 0.77 to 0.96). Combination of the GALL and Kalman filters can achieve robust MA cancellation without supervised selection of the reference axis from the ACC. For ECG, the MA component can also be reduced by adaptive filtering. The signal quality, however, could not be improved substantially just by the adaptive filter with the ACC outputs as the reference signals.

  15. Motion-compensated wavelet video coding using adaptive mode selection

    NASA Astrophysics Data System (ADS)

    Zhai, Fan; Pappas, Thrasyvoulos N.

    2004-01-01

    A motion-compensated wavelet video coder is presented that uses adaptive mode selection (AMS) for each macroblock (MB). The block-based motion estimation is performed in the spatial domain, and an embedded zerotree wavelet coder (EZW) is employed to encode the residue frame. In contrast to other motion-compensated wavelet video coders, where all the MBs are forced to be in INTER mode, we construct the residue frame by combining the prediction residual of the INTER MBs with the coding residual of the INTRA and INTER_ENCODE MBs. Different from INTER MBs that are not coded, the INTRA and INTER_ENCODE MBs are encoded separately by a DCT coder. By adaptively selecting the quantizers of the INTRA and INTER_ENCODE coded MBs, our goal is to equalize the characteristics of the residue frame in order to improve the overall coding efficiency of the wavelet coder. The mode selection is based on the variance of the MB, the variance of the prediction error, and the variance of the neighboring MBs' residual. Simulations show that the proposed motion-compensated wavelet video coder achieves a gain of around 0.7-0.8dB PSNR over MPEG-2 TM5, and a comparable PSNR to other 2D motion-compensated wavelet-based video codecs. It also provides potential visual quality improvement.

  16. Robust Parallel Motion Estimation and Mapping with Stereo Cameras in Underground Infrastructure

    NASA Astrophysics Data System (ADS)

    Liu, Chun; Li, Zhengning; Zhou, Yuan

    2016-06-01

    Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it's also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.

  17. Use of promethazine to hasten adaptation to provocative motion

    NASA Technical Reports Server (NTRS)

    Lackner, J. R.; Graybiel, A.

    1994-01-01

    In an earlier study, the authors found that severely motion sick individuals could be greatly relieved of their symptoms by intramuscular injections of promethazine (50 mg) or scopolamine (.5 mg). Comparable 50-mg injections of promethazine also have been found effective in alleviating symptoms of space motion sickness. The concern has risen, however, that such drugs may delay or retard the acquisition of adaptation to stressful environments. In the current study, we controlled arousal using a mental arithmetic task and precisely equated the exposure history (number of head movements during rotation) of a placebo, control group and an experimental group who had received promethazine. No differences in total adaptation or in rates of adaptation were present between the two groups. Another experimental group also received promethazine and was allowed to make as many head movements as they could, before reaching nausea, up to 800. This group showed a greater level of adaptation than the placebo group. These results suggest a strategy for dealing with space motion sickness that is described.

  18. Sensorimotor Adaptation Following Exposure to Ambiguous Inertial Motion Cues

    NASA Technical Reports Server (NTRS)

    Wood, S. J.; Clement, G. R.; Rupert, A. H.; Reschke, M. F.; Harm, D. L.; Guedry, F. E.

    2007-01-01

    The central nervous system must resolve the ambiguity of inertial motion sensory cues in order to derive accurate spatial orientation awareness. Adaptive changes in how inertial cues from the otolith system are integrated with other sensory information lead to perceptual and postural disturbances upon return to Earth s gravity. The primary goals of this ground-based research investigation are to explore physiological mechanisms and operational implications of tilt-translation disturbances during and following re-entry, and to evaluate a tactile prosthesis as a countermeasure for improving control of whole-body orientation during tilt and translation motion.

  19. Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate

    NASA Astrophysics Data System (ADS)

    Samaras, C.; Cook, L.

    2015-12-01

    Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.

  20. Investigation of Adaptive Robust Kalman Filtering Algorithms for GPS/DR Navigation System Filters

    NASA Astrophysics Data System (ADS)

    Elzoghby, MOSTAFA; Arif, USMAN; Li, FU; Zhi Yu, XI

    2017-03-01

    The conventional Kalman filter (KF) algorithm is suitable if the characteristic noise covariance for states as well as measurements is readily known but in most cases these are unknown. Similarly robustness is required instead of smoothing if states are changing abruptly. Such an adaptive as well as robust Kalman filter is vital for many real time applications, like target tracking and navigating aerial vehicles. A number of adaptive as well as robust Kalman filtering methods are available in the literature. In order to investigate the performance of some of these methods, we have selected three different Kalman filters, namely Sage Husa KF, Modified Adaptive Robust KF and Adaptively Robust KF, which are easily simulate able as well as implementable for real time applications. These methods are simulated for land based vehicle and the results are compared with conventional Kalman filter. Results show that the Modified Adaptive Robust KF is best amongst the selected methods and can be used for Navigation applications.

  1. Robust image registration using adaptive coherent point drift method

    NASA Astrophysics Data System (ADS)

    Yang, Lijuan; Tian, Zheng; Zhao, Wei; Wen, Jinhuan; Yan, Weidong

    2016-04-01

    Coherent point drift (CPD) method is a powerful registration tool under the framework of the Gaussian mixture model (GMM). However, the global spatial structure of point sets is considered only without other forms of additional attribute information. The equivalent simplification of mixing parameters and the manual setting of the weight parameter in GMM make the CPD method less robust to outlier and have less flexibility. An adaptive CPD method is proposed to automatically determine the mixing parameters by embedding the local attribute information of features into the construction of GMM. In addition, the weight parameter is treated as an unknown parameter and automatically determined in the expectation-maximization algorithm. In image registration applications, the block-divided salient image disk extraction method is designed to detect sparse salient image features and local self-similarity is used as attribute information to describe the local neighborhood structure of each feature. The experimental results on optical images and remote sensing images show that the proposed method can significantly improve the matching performance.

  2. Distributed reinforcement learning for adaptive and robust network intrusion response

    NASA Astrophysics Data System (ADS)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  3. Robust adaptive digital watermark for still images using hybrid modulation

    NASA Astrophysics Data System (ADS)

    Alturki, Faisal T.; Mersereau, Russell M.

    2001-08-01

    A digital watermark is a short sequence of information containing an owner identity or copyright information embedded in a way that is difficult to erase. We present a new oblivious digital watermarking technique for copyright protection of still images. The technique embeds the watermark in a subset of low to mid frequency coefficients. A key is used to randomly select a group of coefficients from that subset for watermark embedding. The original phases of the selected coefficients are removed and the new phases are set in accordance with the embedded watermark. Since the coefficients are selected at random, the powers of the low magnitude coefficients are increased to enhance their immunity against image attacks. To cope with small geometric attacks, a replica of the watermark is embedded by dividing the image into sub-blocks and taking the DCT of these blocks. The watermark is embedded in the DC component of some of these blocks selected in an adaptive way using quantization techniques. A major advantage of this technique is its complete suppression of the noise due to the host image. The robustness of the technique to a number of standard image processing attacks is demonstrated using the criteria of the latest Stirmark benchmark test.

  4. Robust online tracking via adaptive samples selection with saliency detection

    NASA Astrophysics Data System (ADS)

    Yan, Jia; Chen, Xi; Zhu, QiuPing

    2013-12-01

    Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

  5. Robust adaptive control of spacecraft proximity maneuvers under dynamic coupling and uncertainty

    NASA Astrophysics Data System (ADS)

    Sun, Liang; Huo, Wei

    2015-11-01

    This paper provides a solution for the position tracking and attitude synchronization problem of the close proximity phase in spacecraft rendezvous and docking. The chaser spacecraft must be driven to a certain fixed position along the docking port direction of the target spacecraft, while the attitude of the two spacecraft must be synchronized for subsequent docking operations. The kinematics and dynamics for relative position and relative attitude are modeled considering dynamic coupling, parametric uncertainties and external disturbances. The relative motion model has a new form with a novel definition of the unknown parameters. An original robust adaptive control method is developed for the concerned problem, and a proof of the asymptotic stability is given for the six degrees of freedom closed-loop system. A numerical example is displayed in simulation to verify the theoretical results.

  6. An Adaptive Motion Estimation Scheme for Video Coding

    PubMed Central

    Gao, Yuan; Jia, Kebin

    2014-01-01

    The unsymmetrical-cross multihexagon-grid search (UMHexagonS) is one of the best fast Motion Estimation (ME) algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV) distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised. PMID:24672313

  7. Enhanced adaptive loop filter for motion compensated frame.

    PubMed

    Yoo, Young-Joe; Seo, Chan-Won; Han, Jong-Ki; Nguyen, Truong Q

    2011-08-01

    We propose an adaptive loop filter to remove the redundancy between current and motion compensated frames so that the residual signal is minimized, thus coding efficiency increases. The loop filter coefficients and offset are optimized for each frame or a set of blocks to minimize the total energy of the residual signal resulting from motion estimation and compensation. The optimized loop filter with offset is applied for the set of blocks where the filtering process gives coding gain based upon rate-distortion cost. The proposed loop filter is used for the motion compensated frame whereas the conventional adaptive interpolation filter (AIF) is applied to the reference frames to interpolate the subpixel values. Another conventional scheme adaptive loop filter (ALF), is used after deblocking filtering to enhance quality of reconstructed frames, not to minimize energy of residual signal. The proposed loop filter can be used in combination with the AIF and ALF. Experimental results show that proposed algorithm provides the averaged bit reduction of 8% compared to conventional H.264/AVC scheme. When the proposed scheme is combined with AIF and ALF, the coding gain increases even further.

  8. Robust object tracking techniques for vision-based 3D motion analysis applications

    NASA Astrophysics Data System (ADS)

    Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

    2016-04-01

    Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

  9. Robust identification of local adaptation from allele frequencies.

    PubMed

    Günther, Torsten; Coop, Graham

    2013-09-01

    Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of "standardized allele frequencies" that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools-a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.

  10. Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations.

    PubMed

    Egbert, Matthew D; Pérez-Mercader, Juan

    2016-01-08

    Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism's internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving "interoceptively," i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms.

  11. Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations

    PubMed Central

    Egbert, Matthew D.; Pérez-Mercader, Juan

    2016-01-01

    Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism’s internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving “interoceptively,” i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms. PMID:26743579

  12. MR-guided thermotherapy of abdominal organs using a robust PCA-based motion descriptor.

    PubMed

    de Senneville, Baudouin Denis; Ries, Mario; Maclair, Grégory; Moonen, Chrit

    2011-11-01

    Thermotherapies can now be guided in real-time using magnetic resonance imaging (MRI). This technique is rapidly gaining importance in interventional therapies for abdominal organs such as liver and kidney. An accurate online estimation and characterization of organ displacement is mandatory to prevent misregistration and correct for motion related thermometry artifacts. In addition, when the ablation is performed with an extracorporal heating device such as high intensity focused ultrasound (HIFU), the continuous estimation of the organ displacement is the basis for the dynamic adjustment of the focal point position to track the targeted pathological tissue. In this paper, we describe the use of an optimized principal component analysis (PCA)-based motion descriptor to characterize in real-time the complex organ deformation during the therapy. The PCA was used to detect, in a preparative learning step, spatio-temporal coherences in the motion of the targeted organ. During hyperthermia, incoherent motion patterns could be discarded, which enabled improvements in motion estimation robustness, the compensation of motion related errors in thermal maps, and the adjustment of the beam position. The suggested method was evaluated for a moving phantom, and tested in vivo in the kidney and the liver of 12 healthy volunteers under free breathing conditions. The ability to perform a MR-guided thermotherapy in vivo during HIFU intervention was finally demonstrated on a porcine kidney.

  13. Preflight Adaptation Training for Spatial Orientation and Space Motion Sickness

    NASA Technical Reports Server (NTRS)

    Harm, Deborah L.; Parker, Donald E.

    1994-01-01

    Two part-task preflight adaptation trainers (PATs) are being developed at the NASA Johnson Space Center to preadapt astronauts to novel sensory stimulus conditions similar to those present in microgravity to facilitate adaptation to microgravity and readaptation to Earth. This activity is a major component of a general effort to develop countermeasures aimed at minimizing sensory and sensorimotor disturbances and Space Motion Sickness (SMS) associated with adaptation to microgravity and readaptation to Earth. Design principles for the development of the two trainers are discussed, along with a detailed description of both devices. In addition, a summary of four ground-based investigations using one of the trainers to determine the extent to which various novel sensory stimulus conditions produce changes in compensatory eye movement responses, postural equilibrium, motion sickness symptoms, and electrogastric responses are presented. Finally, a brief description of the general concept of dual-adopted states that underly the development of the PATs, and ongoing and future operational and basic research activities are presented.

  14. A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

    PubMed Central

    Ci, Wenyan; Huang, Yingping

    2016-01-01

    Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera’s 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg–Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade–Lucas–Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method. PMID:27763508

  15. Adaptation of vestibular signals for self-motion perception.

    PubMed

    St George, Rebecca J; Day, Brian L; Fitzpatrick, Richard C

    2011-02-15

    appreciable effect, making a specific vestibular behavioural role unlikely. This adaptation appears to be a general property of the internal coding of self-motion that receives information from multiple sensory sources and filters out the unvarying components regardless of their origin. In this instance of a pure vestibular sensation, it defines the afferent signal that represents the stationary or zero-rotation state.

  16. Adaptive robust controller based on integral sliding mode concept

    NASA Astrophysics Data System (ADS)

    Taleb, M.; Plestan, F.

    2016-09-01

    This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.

  17. Coronary DSA: enhancing coronary tree visibility through discriminative learning and robust motion estimation

    NASA Astrophysics Data System (ADS)

    Zhu, Ying; Prummer, Simone; Chen, Terrence; Ostermeier, Martin; Comaniciu, Dorin

    2009-02-01

    Digital subtraction angiography (DSA) is a well-known technique for improving the visibility and perceptibility of blood vessels in the human body. Coronary DSA extends conventional DSA to dynamic 2D fluoroscopic sequences of coronary arteries which are subject to respiratory and cardiac motion. Effective motion compensation is the main challenge for coronary DSA. Without a proper treatment, both breathing and heart motion can cause unpleasant artifacts in coronary subtraction images, jeopardizing the clinical value of coronary DSA. In this paper, we present an effective method to separate the dynamic layer of background structures from a fluoroscopic sequence of the heart, leaving a clean layer of moving coronary arteries. Our method combines the techniques of learning-based vessel detection and robust motion estimation to achieve reliable motion compensation for coronary sequences. Encouraging results have been achieved on clinically acquired coronary sequences, where the proposed method considerably improves the visibility and perceptibility of coronary arteries undergoing breathing and cardiac movement. Perceptibility improvement is significant especially for very thin vessels. The potential clinical benefit is expected in the context of obese patients and deep angulation, as well as in the reduction of contrast dose in normal size patients.

  18. Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

    NASA Astrophysics Data System (ADS)

    Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

    2016-11-01

    For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

  19. Adaptation-Induced Compression of Event Time Occurs Only for Translational Motion

    PubMed Central

    Fornaciai, Michele; Arrighi, Roberto; Burr, David C.

    2016-01-01

    Adaptation to fast motion reduces the perceived duration of stimuli displayed at the same location as the adapting stimuli. Here we show that the adaptation-induced compression of time is specific for translational motion. Adaptation to complex motion, either circular or radial, did not affect perceived duration of subsequently viewed stimuli. Adaptation with multiple patches of translating motion caused compression of duration only when the motion of all patches was in the same direction. These results show that adaptation-induced compression of event-time occurs only for uni-directional translational motion, ruling out the possibility that the neural mechanisms of the adaptation occur at early levels of visual processing. PMID:27003445

  20. Improved motion robustness of remote-PPG by using the blood volume pulse signature.

    PubMed

    de Haan, G; van Leest, A

    2014-08-27

    Remote photoplethysmography (rPPG) enables contact-free monitoring of the blood volume pulse using a color camera. Essentially, it detects the minute optical absorption changes caused by blood volume variations in the skin. In this paper, we show that the different absorption spectra of arterial blood and bloodless skin cause the variations to occur along a very specific vector in a normalized RGB-space. The exact vector can be determined for a given light spectrum and for given transfer characteristics of the optical filters in the camera. We show that this 'signature' can be used to design an rPPG algorithm with a much better motion robustness than the recent methods based on blind source separation, and even better than the chrominance-based methods we published earlier. Using six videos recorded in a gym, with four subjects exercising on a range of fitness devices, we confirm the superior motion robustness of our newly proposed rPPG methods. A simple peak detector in the frequency domain returns the correct pulse-rate for 68% of total measurements compared to 60% for the best previous method, while the SNR of the pulse-signal improves from  - 5 dB to  - 4 dB. For a large population of 117 stationary subjects we prove that the accuracy is comparable to the best previous method, although the SNR of the pulse-signal drops from  + 8.4 dB to  + 7.6 dB. We expect the improved motion robustness to significantly widen the application scope of the rPPG-technique.

  1. A robust real-time structure from motion for situational awareness and RSTA

    NASA Astrophysics Data System (ADS)

    Shim, M.; Yilma, S.; Bonner, K.

    2008-04-01

    Maintaining real-time situational awareness of military combat vehicles (manned/unmanned) with onboard vision sensors for either autonomous mobility or reconnaissance missions such as moving target indication (MTI) and automatic target recognition (ATR) while the vehicle is on the move has been technically and operationally challenging. In this paper, we investigate and present a practical implementation of a robust real-time structure from motion technique that allows moving robotic vehicles to be able to reconstruct 3D models from observed 2D features with dynamically adjusting motion parameters. We also demonstrate applications that locate and track moving targets within the structured environment built by the SFM and recognize the targets such as vehicles and humans through a hierarchical shape model.

  2. Introductory review on `Flying Triangulation': a motion-robust optical 3D measurement principle

    NASA Astrophysics Data System (ADS)

    Ettl, Svenja

    2015-04-01

    'Flying Triangulation' (FlyTri) is a recently developed principle which allows for a motion-robust optical 3D measurement of rough surfaces. It combines a simple sensor with sophisticated algorithms: a single-shot sensor acquires 2D camera images. From each camera image, a 3D profile is generated. The series of 3D profiles generated are aligned to one another by algorithms, without relying on any external tracking device. It delivers real-time feedback of the measurement process which enables an all-around measurement of objects. The principle has great potential for small-space acquisition environments, such as the measurement of the interior of a car, and motion-sensitive measurement tasks, such as the intraoral measurement of teeth. This article gives an overview of the basic ideas and applications of FlyTri. The main challenges and their solutions are discussed. Measurement examples are also given to demonstrate the potential of the measurement principle.

  3. Robust cardiac motion estimation using ultrafast ultrasound data: a low-rank-topology-preserving approach.

    PubMed

    Aviles, Angelica I; Widlak, Thomas; Casals, Alicia; Nillesen, Maartje; Ammari, Habib

    2017-03-24

    Cardiac motion estimation is an important diagnostic tool to detect heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of the complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate the cardiac motion using ultrafast ultrasound data. -- Our solution is based on a variational formulation characterized by the L2-regularized class. The displacement is represented by a lattice of b-splines and we ensure robustness by applying a maximum likelihood type estimator. While this is an important part of our solution, the main highlight of this work is to combine a low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati Matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. While maintaining the accuracy of the solution, the low-rank preprocessing is shown to speed up the convergence of the variational problem. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that experience motion.

  4. Adaptive Introspection and Deployment for Robust Long Duration Autonomy

    DTIC Science & Technology

    2014-09-30

    Duration Autonomy Nathan Michael, Sebastian Scherer Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA, 15213-3890 phone: (412) 268...7816 fax: (412) 268-1338 email: nmichael@cmu.edu, scherer@cmu.edu Award Number: N000141310821 LONG-TERM GOALS Long duration autonomy ...integrative experimental framework toward evaluating the approaches developed through the first two tasks. Task 1: Introspection for Robust Autonomy

  5. Adaptive robust control of longitudinal and transverse electron beam profiles

    NASA Astrophysics Data System (ADS)

    Rezaeizadeh, Amin; Schilcher, Thomas; Smith, Roy S.

    2016-05-01

    Feedback control of the longitudinal and transverse electron beam profiles are considered to be critical for beam control in accelerators. In the feedback scheme, the longitudinal or transverse beam profile is measured and compared to a desired profile to give an error estimate. The error is then used to act on the appropriate actuators to correct the profile. The role of the transverse feedback is to steer the beam in a particular trajectory, known as the "orbit." The common approach for orbit correction is based on approximately inverting the response matrix, and in the best case, involves regulating or filtering the singular values. In the current contribution, a more systematic and structured way of handling orbit correction is introduced giving robustness against uncertainties in the response matrix. Moreover, the input bounds are treated to avoid violating the limits of the corrector currents. The concept of the robust orbit correction has been successfully tested at the SwissFEL injector test facility. In the SwissFEL machine, a photo-injector laser system extracts electrons from a cathode and a similar robust control method is developed for the longitudinal feedback control of the current profile of the electron bunch. The method manipulates the angles of the crystals in the laser system to produce a desired charge distribution over the electron bunch length. This approach paves the way towards automation of laser pulse stacking.

  6. BOLD subjective value signals exhibit robust range adaptation.

    PubMed

    Cox, Karin M; Kable, Joseph W

    2014-12-03

    Many theories of decision making assume that choice options are assessed along a common subjective value (SV) scale. The neural correlates of SV are widespread and reliable, despite the wide variation in the range of values over which decisions are made (e.g., between goods worth a few dollars, in some cases, or hundreds of dollars, in others). According to adaptive coding theories (Barlow, 1961), an efficient value signal should exhibit range adaptation, such that neural activity maintains a fixed dynamic range, and the slope of the value response varies inversely with the range of values within the local context. Although monkey data have demonstrated range adaptation in single-unit correlates of value (Padoa-Schioppa, 2009; Kobayashi et al., 2010), whether BOLD value signals exhibit similar range adaptation is unknown. To test for this possibility, we presented human participants with choices between a fixed immediate and variable delayed payment options. Across two conditions, the delayed options' SVs spanned either a narrow or wide range. SV-tracking activity emerged in the posterior cingulate, ventral striatum, anterior cingulate, and ventromedial prefrontal cortex. Throughout this network, we observed evidence consistent with the predictions of range adaptation: the SV response slope increased in the narrow versus wide range, with statistically significant slope changes confirmed for the posterior cingulate and ventral striatum. No regions exhibited a reliably increased BOLD activity range in the wide versus narrow condition. Our observations of range adaptation present implications for the interpretation of BOLD SV responses that are measured across different contexts or individuals.

  7. Sensorimotor Adaptations Following Exposure to Ambiguous Inertial Motion Cues

    NASA Technical Reports Server (NTRS)

    Wood, S. J.; Harm, D. L.; Reschke, M. F.; Rupert, A. H.; Clement, G. R.

    2009-01-01

    The central nervous system must resolve the ambiguity of inertial motion sensory cues in order to derive accurate spatial orientation awareness. We hypothesize that multi-sensory integration will be adaptively optimized in altered gravity environments based on the dynamics of other sensory information available, with greater changes in otolith-mediated responses in the mid-frequency range where there is a crossover of tilt and translation responses. The primary goals of this ground-based research investigation are to explore physiological mechanisms and operational implications of tilt-translation disturbances during and following re-entry, and to evaluate a tactile prosthesis as a countermeasure for improving control of whole-body orientation.

  8. Sensorimotor Adaptation Following Exposure to Ambiguous Inertial Motion Cues

    NASA Technical Reports Server (NTRS)

    Wood, S. J.; Clement, G. R.; Harm, D. L.; Rupert, A. H.; Guedry, F. E.; Reschke, M. F.

    2005-01-01

    The central nervous system must resolve the ambiguity of inertial motion sensory cues in order to derive accurate spatial orientation awareness. Our general hypothesis is that the central nervous system utilizes both multi-sensory integration and frequency segregation as neural strategies to resolve the ambiguity of tilt and translation stimuli. Movement in an altered gravity environment, such as weightlessness without a stable gravity reference, results in new patterns of sensory cues. For example, the semicircular canals, vision and neck proprioception provide information about head tilt on orbit without the normal otolith head-tilt position that is omnipresent on Earth. Adaptive changes in how inertial cues from the otolith system are integrated with other sensory information lead to perceptual and postural disturbances upon return to Earth's gravity. The primary goals of this ground-based research investigation are to explore physiological mechanisms and operational implications of disorientation and tilt-translation disturbances reported by crewmembers during and following re-entry, and to evaluate a tactile prosthesis as a countermeasure for improving control of whole-body orientation during tilt and translation motion.

  9. Sensorimotor Adaptation Following Exposure to Ambiguous Inertial Motion Cues

    NASA Technical Reports Server (NTRS)

    Wood, S. J.; Clement, G. R.; Harm, D L.; Rupert, A. H.; Guedry, F. E.; Reschke, M. F.

    2005-01-01

    The central nervous system must resolve the ambiguity of inertial motion sensory cues in order to derive accurate spatial orientation awareness. Our general hypothesis is that the central nervous system utilizes both multi-sensory integration and frequency segregation as neural strategies to resolve the ambiguity of tilt and translation stimuli. Movement in an altered gravity environment, such as weightlessness without a stable gravity reference, results in new patterns of sensory cues. For example, the semicircular canals, vision and neck proprioception provide information about head tilt on orbit without the normal otolith head-tilt position that is omnipresent on Earth. Adaptive changes in how inertial cues from the otolith system are integrated with other sensory information lead to perceptual and postural disturbances upon return to Earth s gravity. The primary goals of this ground-based research investigation are to explore physiological mechanisms and operational implications of disorientation and tilt-translation disturbances reported by crewmembers during and following re-entry, and to evaluate a tactile prosthesis as a countermeasure for improving control of whole-body orientation during tilt and translation motion.

  10. A Mixture Model for Robust Point Matching under Multi-Layer Motion

    PubMed Central

    Ma, Jiayi; Chen, Jun; Ming, Delie; Tian, Jinwen

    2014-01-01

    This paper proposes an efficient mixture model for establishing robust point correspondences between two sets of points under multi-layer motion. Our algorithm starts by creating a set of putative correspondences which can contain a number of false correspondences, or outliers, in addition to the true correspondences (inliers). Next we solve for correspondence by interpolating a set of spatial transformations on the putative correspondence set based on a mixture model, which involves estimating a consensus of inlier points whose matching follows a non-parametric geometrical constraint. We formulate this as a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables indicating whether matches in the putative set are outliers or inliers. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS). MAP estimation is performed by the EM algorithm which by also estimating the variance of the prior model (initialized to a large value) is able to obtain good estimates very quickly (e.g., avoiding many of the local minima inherent in this formulation). We further provide a fast implementation based on sparse approximation which can achieve a significant speed-up without much performance degradation. We illustrate the proposed method on 2D and 3D real images for sparse feature correspondence, as well as a public available dataset for shape matching. The quantitative results demonstrate that our method is robust to non-rigid deformation and multi-layer/large discontinuous motion. PMID:24658087

  11. A mixture model for robust point matching under multi-layer motion.

    PubMed

    Ma, Jiayi; Chen, Jun; Ming, Delie; Tian, Jinwen

    2014-01-01

    This paper proposes an efficient mixture model for establishing robust point correspondences between two sets of points under multi-layer motion. Our algorithm starts by creating a set of putative correspondences which can contain a number of false correspondences, or outliers, in addition to the true correspondences (inliers). Next we solve for correspondence by interpolating a set of spatial transformations on the putative correspondence set based on a mixture model, which involves estimating a consensus of inlier points whose matching follows a non-parametric geometrical constraint. We formulate this as a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables indicating whether matches in the putative set are outliers or inliers. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS). MAP estimation is performed by the EM algorithm which by also estimating the variance of the prior model (initialized to a large value) is able to obtain good estimates very quickly (e.g., avoiding many of the local minima inherent in this formulation). We further provide a fast implementation based on sparse approximation which can achieve a significant speed-up without much performance degradation. We illustrate the proposed method on 2D and 3D real images for sparse feature correspondence, as well as a public available dataset for shape matching. The quantitative results demonstrate that our method is robust to non-rigid deformation and multi-layer/large discontinuous motion.

  12. Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

    2009-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

  13. Shape adaptive, robust iris feature extraction from noisy iris images.

    PubMed

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-10-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

  14. Automated 3D motion tracking using Gabor filter bank, robust point matching, and deformable models.

    PubMed

    Chen, Ting; Wang, Xiaoxu; Chung, Sohae; Metaxas, Dimitris; Axel, Leon

    2010-01-01

    Tagged magnetic resonance imaging (tagged MRI or tMRI) provides a means of directly and noninvasively displaying the internal motion of the myocardium. Reconstruction of the motion field is needed to quantify important clinical information, e.g., the myocardial strain, and detect regional heart functional loss. In this paper, we present a three-step method for this task. First, we use a Gabor filter bank to detect and locate tag intersections in the image frames, based on local phase analysis. Next, we use an improved version of the robust point matching (RPM) method to sparsely track the motion of the myocardium, by establishing a transformation function and a one-to-one correspondence between grid tag intersections in different image frames. In particular, the RPM helps to minimize the impact on the motion tracking result of 1) through-plane motion and 2) relatively large deformation and/or relatively small tag spacing. In the final step, a meshless deformable model is initialized using the transformation function computed by RPM. The model refines the motion tracking and generates a dense displacement map, by deforming under the influence of image information, and is constrained by the displacement magnitude to retain its geometric structure. The 2D displacement maps in short and long axis image planes can be combined to drive a 3D deformable model, using the moving least square method, constrained by the minimization of the residual error at tag intersections. The method has been tested on a numerical phantom, as well as on in vivo heart data from normal volunteers and heart disease patients. The experimental results show that the new method has a good performance on both synthetic and real data. Furthermore, the method has been used in an initial clinical study to assess the differences in myocardial strain distributions between heart disease (left ventricular hypertrophy) patients and the normal control group. The final results show that the proposed method

  15. Robust adaptive extended Kalman filtering for real time MR-thermometry guided HIFU interventions.

    PubMed

    Roujol, Sébastien; de Senneville, Baudouin Denis; Hey, Silke; Moonen, Chrit; Ries, Mario

    2012-03-01

    Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.

  16. Robust speech perception: recognize the familiar, generalize to the similar, and adapt to the novel.

    PubMed

    Kleinschmidt, Dave F; Jaeger, T Florian

    2015-04-01

    Successful speech perception requires that listeners map the acoustic signal to linguistic categories. These mappings are not only probabilistic, but change depending on the situation. For example, one talker's /p/ might be physically indistinguishable from another talker's /b/ (cf. lack of invariance). We characterize the computational problem posed by such a subjectively nonstationary world and propose that the speech perception system overcomes this challenge by (a) recognizing previously encountered situations, (b) generalizing to other situations based on previous similar experience, and (c) adapting to novel situations. We formalize this proposal in the ideal adapter framework: (a) to (c) can be understood as inference under uncertainty about the appropriate generative model for the current talker, thereby facilitating robust speech perception despite the lack of invariance. We focus on 2 critical aspects of the ideal adapter. First, in situations that clearly deviate from previous experience, listeners need to adapt. We develop a distributional (belief-updating) learning model of incremental adaptation. The model provides a good fit against known and novel phonetic adaptation data, including perceptual recalibration and selective adaptation. Second, robust speech recognition requires that listeners learn to represent the structured component of cross-situation variability in the speech signal. We discuss how these 2 aspects of the ideal adapter provide a unifying explanation for adaptation, talker-specificity, and generalization across talkers and groups of talkers (e.g., accents and dialects). The ideal adapter provides a guiding framework for future investigations into speech perception and adaptation, and more broadly language comprehension.

  17. Nonlinear mode decomposition: A noise-robust, adaptive decomposition method

    NASA Astrophysics Data System (ADS)

    Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta

    2015-09-01

    The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

  18. Noise-robust recognition of wide-field motion direction and the underlying neural mechanisms in Drosophila melanogaster.

    PubMed

    Suzuki, Yoshinori; Ikeda, Hideaki; Miyamoto, Takuya; Miyakawa, Hiroyoshi; Seki, Yoichi; Aonishi, Toru; Morimoto, Takako

    2015-05-14

    Appropriate and robust behavioral control in a noisy environment is important for the survival of most organisms. Understanding such robust behavioral control has been an attractive subject in neuroscience research. Here, we investigated the processing of wide-field motion with random dot noise at both the behavioral and neuronal level in Drosophila melanogaster. We measured the head yaw optomotor response (OMR) and the activity of motion-sensitive neurons, horizontal system (HS) cells, with in vivo whole-cell patch clamp recordings at various levels of noise intensity. We found that flies had a robust sensation of motion direction under noisy conditions, while membrane potential changes of HS cells were not correlated with behavioral responses. By applying signal classification theory to the distributions of HS cell responses, however, we found that motion direction under noise can be clearly discriminated by HS cells, and that this discrimination performance was quantitatively similar to that of OMR. Furthermore, we successfully reproduced HS cell activity in response to noisy motion stimuli with a local motion detector model including a spatial filter and threshold function. This study provides evidence for the physiological basis of noise-robust behavior in a tiny insect brain.

  19. Noise-robust recognition of wide-field motion direction and the underlying neural mechanisms in Drosophila melanogaster

    PubMed Central

    Suzuki, Yoshinori; Ikeda, Hideaki; Miyamoto, Takuya; Miyakawa, Hiroyoshi; Seki, Yoichi; Aonishi, Toru; Morimoto, Takako

    2015-01-01

    Appropriate and robust behavioral control in a noisy environment is important for the survival of most organisms. Understanding such robust behavioral control has been an attractive subject in neuroscience research. Here, we investigated the processing of wide-field motion with random dot noise at both the behavioral and neuronal level in Drosophila melanogaster. We measured the head yaw optomotor response (OMR) and the activity of motion-sensitive neurons, horizontal system (HS) cells, with in vivo whole-cell patch clamp recordings at various levels of noise intensity. We found that flies had a robust sensation of motion direction under noisy conditions, while membrane potential changes of HS cells were not correlated with behavioral responses. By applying signal classification theory to the distributions of HS cell responses, however, we found that motion direction under noise can be clearly discriminated by HS cells, and that this discrimination performance was quantitatively similar to that of OMR. Furthermore, we successfully reproduced HS cell activity in response to noisy motion stimuli with a local motion detector model including a spatial filter and threshold function. This study provides evidence for the physiological basis of noise-robust behavior in a tiny insect brain. PMID:25974721

  20. Robustness

    NASA Technical Reports Server (NTRS)

    Ryan, R.

    1993-01-01

    Robustness is a buzz word common to all newly proposed space systems design as well as many new commercial products. The image that one conjures up when the word appears is a 'Paul Bunyon' (lumberjack design), strong and hearty; healthy with margins in all aspects of the design. In actuality, robustness is much broader in scope than margins, including such factors as simplicity, redundancy, desensitization to parameter variations, control of parameter variations (environments flucation), and operational approaches. These must be traded with concepts, materials, and fabrication approaches against the criteria of performance, cost, and reliability. This includes manufacturing, assembly, processing, checkout, and operations. The design engineer or project chief is faced with finding ways and means to inculcate robustness into an operational design. First, however, be sure he understands the definition and goals of robustness. This paper will deal with these issues as well as the need for the requirement for robustness.

  1. Direction-specific adaptation of motion-onset auditory evoked potentials.

    PubMed

    Grzeschik, Ramona; Böckmann-Barthel, Martin; Mühler, Roland; Verhey, Jesko L; Hoffmann, Michael B

    2013-08-01

    Auditory evoked potentials (AEPs) to motion onset in humans are dominated by a fronto-central complex, with a change-negative deflection 1 (cN1) and a change-positive deflection 2 (cP2) component. Here the contribution of veridical motion detectors to motion-onset AEPs was investigated with the hypothesis that direction-specific adaptation effects would indicate the contribution of such motion detectors. AEPs were recorded from 33 electroencephalographic channels to the test stimulus, i.e. motion onset of horizontal virtual auditory motion (60° per s) from straight ahead to the left. AEPs were compared in two experiments for three conditions, which differed in their history prior to the motion-onset test stimulus: (i) without motion history (Baseline), (ii) with motion history in the same direction as the test stimulus (Adaptation Same), and (iii) a reference condition with auditory history. For Experiment 1, condition (iii) comprised motion in the opposite direction (Adaptation Opposite). For Experiment 2, a noise in the absence of coherent motion (Matched Noise) was used as the reference condition. In Experiment 1, the amplitude difference cP2 - cN1 obtained for Adaptation Same was significantly smaller than for Baseline and Adaptation Opposite. In Experiment 2, it was significantly smaller than for Matched Noise. Adaptation effects were absent for cN1 and cP2 latencies. These findings demonstrate direction-specific adaptation of the motion-onset AEP. This suggests that veridical auditory motion detectors contribute to the motion-onset AEP.

  2. Robust adaptive synchronization of Rossler and Chen chaotic systems via slide technique

    NASA Astrophysics Data System (ADS)

    Li, Zhi; Shi, Songjiao

    2003-05-01

    This Letter considers the robust adaptive synchronization problem of Rossler and Chen chaotic systems with different time-varying unknown parameters. When system's unknown parameters vary in bound intervals and the bounds of intervals are unknown, a robust adaptive controller is designed. In order to increase the robustness of the closed loop systems, the key idea is that a sliding mode type of controller is employed. Besides, instead of the estimate values of systems' unknown parameters being taken as updating object, a new updating object is introduced in constructing controller. The proposed controller can make the states of Rossler and Chen chaotic systems globally asymptotically robustly synchronized. Simulation results are given to show the effectiveness of the proposed method.

  3. A Methodology for Adaptable and Robust Ecosystem Services Assessment

    PubMed Central

    Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

    2014-01-01

    Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts. PMID:24625496

  4. A methodology for adaptable and robust ecosystem services assessment

    USGS Publications Warehouse

    Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

    2014-01-01

    Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

  5. Robust adaptive self-structuring fuzzy control design for nonaffine, nonlinear systems

    NASA Astrophysics Data System (ADS)

    Chen, Pin-Cheng; Wang, Chi-Hsu; Lee, Tsu-Tian

    2011-01-01

    In this article, a robust adaptive self-structuring fuzzy control (RASFC) scheme for the uncertain or ill-defined nonlinear, nonaffine systems is proposed. The RASFC scheme is composed of a robust adaptive controller and a self-structuring fuzzy controller. In the self-structuring fuzzy controller design, a novel self-structuring fuzzy system (SFS) is used to approximate the unknown plant nonlinearity, and the SFS can automatically grow and prune fuzzy rules to realise a compact fuzzy rule base. The robust adaptive controller is designed to achieve an L 2 tracking performance to stabilise the closed-loop system. This L 2 tracking performance can provide a clear expression of tracking error in terms of the sum of lumped uncertainty and external disturbance, which has not been shown in previous works. Finally, five examples are presented to show that the proposed RASFC scheme can achieve favourable tracking performance, yet heavy computational burden is relieved.

  6. Adaptive comb filtering for motion artifact reduction from PPG with a structure of adaptive lattice IIR notch filter.

    PubMed

    Lee, Boreom; Kee, Youngwook; Han, Jonghee; Yi, Won Jin

    2011-01-01

    Photoplethysmographic (PPG) signal can provide important information about cardiovascular and respiratory conditions of individuals in a hospital or daily life. However, PPG can be distorted by motion artifacts significantly. Therefore, the reduction of the effects of motion artifacts is very important procedure for monitoring cardio-respiratory system by PPG. There have been many adaptive techniques to reduce motion artifacts from PPG signal including normalized least mean squares (NLMS) method, recursive least squares (RLS) filter, and Kalman filter. In the present study, we propose the adaptive comb filter (ACF) for reducing the effects of motion artifacts from PPG signal. ACF with adaptive lattice infinite impulse response (IIR) notch filter (ALNF) successfully reduced the motion artifacts from the quasi-periodic PPG signal.

  7. A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

    NASA Astrophysics Data System (ADS)

    Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

    2015-04-01

    This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation.

  8. A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements

    NASA Astrophysics Data System (ADS)

    Kilicarslan, Atilla; Grossman, Robert G.; Contreras-Vidal, Jose Luis

    2016-04-01

    Objective. Non-invasive measurement of human neural activity based on the scalp electroencephalogram (EEG) allows for the development of biomedical devices that interface with the nervous system for scientific, diagnostic, therapeutic, or restorative purposes. However, EEG recordings are often considered as prone to physiological and non-physiological artifacts of different types and frequency characteristics. Among them, ocular artifacts and signal drifts represent major sources of EEG contamination, particularly in real-time closed-loop brain-machine interface (BMI) applications, which require effective handling of these artifacts across sessions and in natural settings. Approach. We extend the usage of a robust adaptive noise cancelling (ANC) scheme ({H}∞ filtering) for removal of eye blinks, eye motions, amplitude drifts and recording biases simultaneously. We also characterize the volume conduction, by estimating the signal propagation levels across all EEG scalp recording areas due to ocular artifact generators. We find that the amplitude and spatial distribution of ocular artifacts vary greatly depending on the electrode location. Therefore, fixed filtering parameters for all recording areas would naturally hinder the true overall performance of an ANC scheme for artifact removal. We treat each electrode as a separate sub-system to be filtered, and without the loss of generality, they are assumed to be uncorrelated and uncoupled. Main results. Our results show over 95-99.9% correlation between the raw and processed signals at non-ocular artifact regions, and depending on the contamination profile, 40-70% correlation when ocular artifacts are dominant. We also compare our results with the offline independent component analysis and artifact subspace reconstruction methods, and show that some local quantities are handled better by our sample-adaptive real-time framework. Decoding performance is also compared with multi-day experimental data from 2 subjects

  9. Robust adaptive neural network control of uncertain nonholonomic systems with strong nonlinear drifts.

    PubMed

    Wang, Z P; Ge, S S; Lee, T H

    2004-10-01

    In this paper, robust adaptive neural network (NN) control is presented to solve the control problem of nonholonomic systems in chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive NN control laws are developed using state scaling and backstepping. Uniform ultimate boundedness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neighborhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. The proposed adaptive NN control is free of control singularity problem. An adaptive control based switching strategy is used to overcome the uncontrollability problem associated with x0 (t0) = 0. The simulation results demonstrate the effectiveness of the proposed controllers.

  10. Distributed robust adaptive control for a class of dynamical complex networks against imperfect communications

    NASA Astrophysics Data System (ADS)

    Jin, Xiao-Zheng; Yang, Guang-Hong

    2011-03-01

    In this article, a robust tracking control problem of a class of dynamical complex networks is presented through a distributed adaptive approach. Uncertain network topology with unknown coupling strength, delayed and perturbed communications and external disturbances are considered, while the bounds of channel noises and coupling delays and disturbances are assumed to be unknown. Adaptation laws are proposed to estimate the network coupling strength and the upper and lower bounds of communication state errors and disturbances on-line. Based on the information from adaptive schemes, a class of distributed robust adaptive controllers is constructed to automatically compensate for the imperfect network and disturbance effects. Then, according to the Lyapunov stability theory, it is shown that the achievement of tracking for complex networks is effective on imperfect communications and disturbances. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of an F-18 aircraft.

  11. Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands

    NASA Astrophysics Data System (ADS)

    Haasnoot, M.; Schellekens, J.; Beersma, J. J.; Middelkoop, H.; Kwadijk, J. C. J.

    2015-10-01

    Climate scenarios are used to explore impacts of possible future climates and to assess the robustness of adaptation actions across a range of futures. Time-dependent climate scenarios are commonly used in mitigation studies. However, despite the dynamic nature of adaptation, most scenarios for local or regional decision making on climate adaptation are static ‘endpoint’ projections. This paper describes the development and use of transient (time-dependent) scenarios by means of a case on water management in the Netherlands. Relevant boundary conditions (sea level, precipitation and evaporation) were constructed by generating an ensemble of synthetic time-series with a rainfall generator and a transient delta change method. Climate change impacted river flows were then generated with a hydrological simulation model for the Rhine basin. The transient scenarios were applied in model simulations and game experiments. We argue that there are at least three important assets of using transient scenarios for supporting robust climate adaptation: (1) raise awareness about (a) the implications of climate variability and climate change for decision making and (b) the difficulty of finding proof of climate change in relevant variables for water management; (2) assessment of when to adapt by identifying adaptation tipping points which can then be used to explore adaptation pathways, and (3) identification of triggers for climate adaptation.

  12. Edge Detection to Isolate Motion in Adaptive Optics Systems

    SciTech Connect

    Chan, C W

    2003-07-11

    Adaptive optics uses signal processing techniques and deformable mirrors to minimize image degradation caused by phase aberrations. In the case of telescope imaging, the atmosphere causes phase aberrations. In the case of satellite imaging, errors due to the ultra-light-weight characteristics of the primary mirror cause phase aberrations. Scene-based Shack-Hartmann Wave Front Sensing takes the correlation between successive wavelets to determine these phase aberrations. A large problem with the scene-based approach is that motion, such as a moving car, can cause the correlation of two lenslets to peak, not where the scenes align, but where the moving object in each frame aligns. As such, the continued use of scene-based Wave Front Sensing necessitates successful isolation of moving objects from a stationary background scene. With the knowledge of which pixels are immobile, one should avoid the problem of locking onto a moving object when taking the correlation of two successive frames in time. Two main requirements of isolation are consistency and efficiency. In this document I will discuss the different edge detection algorithms explored for moving object isolation and how I came to the conclusion that, for our purposes of scene-based Shack-Hartmann WFS, edge detection is too inconsistent to be of any use. Because the Shack-Hartmann lenslets limits us to low resolutions, edge detection that works on higher resolution images will not work on our images. The results of each algorithm will show that with so few pixels per subaperature, edge detection is a poor method of identifying moving objects.

  13. Adaptive Denoising Technique for Robust Analysis of Functional Magnetic Resonance Imaging Data

    DTIC Science & Technology

    2007-11-02

    or receive while t fMRI o versatil of epoc method ER-fM to the studies comes intra-su functioADAPTIVE DENOISING TECHNIQUE FOR ROBUST ANALYSIS OF...supported in part by the Center for Advanced Software and Biomedical Engineering Consultations (CASBEC), Cairo University, and IBE Technologies , Egypt

  14. Adaptive resolution simulation of liquid para-hydrogen: testing the robustness of the quantum-classical adaptive coupling.

    PubMed

    Poma, A B; Delle Site, L

    2011-06-14

    Adaptive resolution simulations for classical systems are currently made within a reasonably consistent theoretical framework. Recently we have extended this approach to the quantum-classical coupling by mapping the quantum nature of an atom onto a classical polymer ring representation within the path integral approach [Poma & Delle Site, Phys. Rev. Lett., 2010, 104, 250201]. In this way the process of interfacing adaptively a quantum representation to a classical one corresponds to the problem of interfacing two regions with a different number of effective "classical" degrees of freedom; thus the classical formulation of the adaptive algorithm applies straightforwardly to the quantum-classical problem. In this work we show the robustness of such an approach for a liquid of para-hydrogen at low temperature. This system represents a highly challenging conceptual and technical test for the adaptive approach due to the extreme thermodynamical conditions where quantum effects play a central role.

  15. Robust speech perception: Recognize the familiar, generalize to the similar, and adapt to the novel

    PubMed Central

    Kleinschmidt, Dave F.; Jaeger, T. Florian

    2016-01-01

    Successful speech perception requires that listeners map the acoustic signal to linguistic categories. These mappings are not only probabilistic, but change depending on the situation. For example, one talker’s /p/ might be physically indistinguishable from another talker’s /b/ (cf. lack of invariance). We characterize the computational problem posed by such a subjectively non-stationary world and propose that the speech perception system overcomes this challenge by (1) recognizing previously encountered situations, (2) generalizing to other situations based on previous similar experience, and (3) adapting to novel situations. We formalize this proposal in the ideal adapter framework: (1) to (3) can be understood as inference under uncertainty about the appropriate generative model for the current talker, thereby facilitating robust speech perception despite the lack of invariance. We focus on two critical aspects of the ideal adapter. First, in situations that clearly deviate from previous experience, listeners need to adapt. We develop a distributional (belief-updating) learning model of incremental adaptation. The model provides a good fit against known and novel phonetic adaptation data, including perceptual recalibration and selective adaptation. Second, robust speech recognition requires listeners learn to represent the structured component of cross-situation variability in the speech signal. We discuss how these two aspects of the ideal adapter provide a unifying explanation for adaptation, talker-specificity, and generalization across talkers and groups of talkers (e.g., accents and dialects). The ideal adapter provides a guiding framework for future investigations into speech perception and adaptation, and more broadly language comprehension. PMID:25844873

  16. Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System.

    PubMed

    Wang, Ning; Er, Meng Joo; Sun, Jing-Chao; Liu, Yan-Cheng

    2016-07-01

    In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy.

  17. Adaptive Animation of Human Motion for E-Learning Applications

    ERIC Educational Resources Information Center

    Li, Frederick W. B.; Lau, Rynson W. H.; Komura, Taku; Wang, Meng; Siu, Becky

    2007-01-01

    Human motion animation has been one of the major research topics in the field of computer graphics for decades. Techniques developed in this area help present human motions in various applications. This is crucial for enhancing the realism as well as promoting the user interest in the applications. To carry this merit to e-learning applications,…

  18. Independent motion detection with a rival penalized adaptive particle filter

    NASA Astrophysics Data System (ADS)

    Becker, Stefan; Hübner, Wolfgang; Arens, Michael

    2014-10-01

    Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic

  19. Integrating Illumination, Motion, and Shape Models for Robust Face Recognition in Video

    NASA Astrophysics Data System (ADS)

    Xu, Yilei; Roy-Chowdhury, Amit; Patel, Keyur

    2007-12-01

    The use of video sequences for face recognition has been relatively less studied compared to image-based approaches. In this paper, we present an analysis-by-synthesis framework for face recognition from video sequences that is robust to large changes in facial pose and lighting conditions. This requires tracking the video sequence, as well as recognition algorithms that are able to integrate information over the entire video; we address both these problems. Our method is based on a recently obtained theoretical result that can integrate the effects of motion, lighting, and shape in generating an image using a perspective camera. This result can be used to estimate the pose and structure of the face and the illumination conditions for each frame in a video sequence in the presence of multiple point and extended light sources. We propose a new inverse compositional estimation approach for this purpose. We then synthesize images using the face model estimated from the training data corresponding to the conditions in the probe sequences. Similarity between the synthesized and the probe images is computed using suitable distance measurements. The method can handle situations where the pose and lighting conditions in the training and testing data are completely disjoint. We show detailed performance analysis results and recognition scores on a large video dataset.

  20. Adaptive integral LOS path following for an unmanned airship with uncertainties based on robust RBFNN backstepping.

    PubMed

    Zheng, Zewei; Zou, Yao

    2016-11-01

    This paper investigates the path following control problem for an unmanned airship in the presence of unknown wind and uncertainties. The backstepping technique augmented by a robust adaptive radial basis function neural network (RBFNN) is employed as the main control framework. Based on the horizontal dynamic model of the airship, an improved adaptive integral line-of-sight (LOS) guidance law is first proposed, which suits any parametric paths. The guidance law calculates the desired yaw angle and estimates the wind. Then the controller is extended to cope with the airship yaw tracking and velocity control by resorting to the augmented backstepping technique. The uncertainties of the dynamics are compensated by using the robust RBFNNs. Each robust RBFNN utilizes an nth-order smooth switching function to combine a conventional RBFNN with a robust control. The conventional RBFNN dominates in the neural active region, while the robust control retrieves the transient outside the active region, so that the stability range can be widened. Stability analysis shows that the controlled closed-loop system is globally uniformly ultimately bounded. Simulations are provided to validate the effectiveness of the proposed control approach.

  1. A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

    NASA Astrophysics Data System (ADS)

    Chen, Xianshun; Feng, Liang; Ong, Yew Soon

    2012-07-01

    In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

  2. Application of nonlinear adaptive motion washout to transport ground-handling simulation

    NASA Technical Reports Server (NTRS)

    Parrish, R. V.; Martin, D. J., Jr.

    1983-01-01

    The application of a nonlinear coordinated adaptive motion washout to the transport ground-handling environment is documented. Additions to both the aircraft math model and the motion washout system are discussed. The additions to the simulated-aircraft math model provided improved modeling fidelity for braking and reverse-thrust application, and the additions to the motion-base washout system allowed transition from the desired flight parameters to the less restrictive ground parameters of the washout.

  3. ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.

    PubMed

    Pruim, Raimon H R; Mennes, Maarten; van Rooij, Daan; Llera, Alberto; Buitelaar, Jan K; Beckmann, Christian F

    2015-05-15

    Head motion during functional MRI (fMRI) scanning can induce spurious findings and/or harm detection of true effects. Solutions have been proposed, including deleting ('scrubbing') or regressing out ('spike regression') motion volumes from fMRI time-series. These strategies remove motion-induced signal variations at the cost of destroying the autocorrelation structure of the fMRI time-series and reducing temporal degrees of freedom. ICA-based fMRI denoising strategies overcome these drawbacks but typically require re-training of a classifier, needing manual labeling of derived components (e.g. ICA-FIX; Salimi-Khorshidi et al. (2014)). Here, we propose an ICA-based strategy for Automatic Removal of Motion Artifacts (ICA-AROMA) that uses a small (n=4), but robust set of theoretically motivated temporal and spatial features. Our strategy does not require classifier re-training, retains the data's autocorrelation structure and largely preserves temporal degrees of freedom. We describe ICA-AROMA, its implementation, and initial validation. ICA-AROMA identified motion components with high accuracy and robustness as illustrated by leave-N-out cross-validation. We additionally validated ICA-AROMA in resting-state (100 participants) and task-based fMRI data (118 participants). Our approach removed (motion-related) spurious noise from both rfMRI and task-based fMRI data to larger extent than regression using 24 motion parameters or spike regression. Furthermore, ICA-AROMA increased sensitivity to group-level activation. Our results show that ICA-AROMA effectively reduces motion-induced signal variations in fMRI data, is applicable across datasets without requiring classifier re-training, and preserves the temporal characteristics of the fMRI data.

  4. Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

    NASA Astrophysics Data System (ADS)

    Du, Bing; Ruan, Chun

    With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

  5. Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

    PubMed

    Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

    2014-03-01

    In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method.

  6. Robust patella motion tracking using intensity-based 2D-3D registration on dynamic bi-plane fluoroscopy: towards quantitative assessment in MPFL reconstruction surgery

    NASA Astrophysics Data System (ADS)

    Otake, Yoshito; Esnault, Matthieu; Grupp, Robert; Kosugi, Shinichi; Sato, Yoshinobu

    2016-03-01

    The determination of in vivo motion of multiple-bones using dynamic fluoroscopic images and computed tomography (CT) is useful for post-operative assessment of orthopaedic surgeries such as medial patellofemoral ligament reconstruction. We propose a robust method to measure the 3D motion of multiple rigid objects with high accuracy using a series of bi-plane fluoroscopic images and a multi-resolution, intensity-based, 2D-3D registration. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer was used with a gradient correlation similarity metric. Four approaches to register three rigid objects (femur, tibia-fibula and patella) were implemented: 1) an individual bone approach registering one bone at a time, each with optimization of a six degrees of freedom (6DOF) parameter, 2) a sequential approach registering one bone at a time but using the previous bone results as the background in DRR generation, 3) a simultaneous approach registering all the bones together (18DOF) and 4) a combination of the sequential and the simultaneous approaches. These approaches were compared in experiments using simulated images generated from the CT of a healthy volunteer and measured fluoroscopic images. Over the 120 simulated frames of motion, the simultaneous approach showed improved registration accuracy compared to the individual approach: with less than 0.68mm root-mean-square error (RMSE) for translation and less than 1.12° RMSE for rotation. A robustness evaluation was conducted with 45 trials of a randomly perturbed initialization showed that the sequential approach improved robustness significantly (74% success rate) compared to the individual bone approach (34% success) for patella registration (femur and tibia-fibula registration had a 100% success rate with each approach).

  7. Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

    PubMed

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme.

  8. A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

    PubMed

    Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

    2017-01-01

    In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used.

  9. Robust background subtraction for automated detection and tracking of targets in wide area motion imagery

    NASA Astrophysics Data System (ADS)

    Kent, Phil; Maskell, Simon; Payne, Oliver; Richardson, Sean; Scarff, Larry

    2012-10-01

    Performing persistent surveillance of large populations of targets is increasingly important in both the defence and security domains. In response to this, Wide Area Motion Imagery (WAMI) sensors with Wide FoVs are growing in popularity. Such WAMI sensors simultaneously provide high spatial and temporal resolutions, giving extreme pixel counts over large geographical areas. The ensuing data rates are such that either very bandwidth data links are required (e.g. for human interpretation) or close-to-sensor automation is required to down-select salient information. For the latter case, we use an iterative quad-tree optical-flow algorithm to efficiently estimate the parameters of a perspective deformation of the background. We then use a robust estimator to simultaneously detect foreground pixels and infer the parameters of each background pixel in the current image. The resulting detections are referenced to the coordinates of the first frame and passed to a multi-target tracker. The multi-target tracker uses a Kalman filter per target and a Global Nearest Neighbour approach to multi-target data association, thereby including statistical models for missed detections and false alarms. We use spatial data structures to ensure that the tracker can scale to analysing thousands of targets. We demonstrate that real-time processing (on modest hardware) is feasible on an unclassified WAMI infra-red dataset consisting of 4096 by 4096 pixels at 1Hz simulating data taken from a Wide FoV sensor on a UAV. With low latency and despite intermittent obscuration and false alarms, we demonstrate persistent tracking of all but one (low-contrast) vehicular target, with no false tracks.

  10. The Retention of Protective Adaptation to Motion Sickness Induced by Cross - Coupled Angular Accelerations

    DTIC Science & Technology

    1975-02-01

    adaptability assessed in a single session are positively and significantly correlated with both motion sickness b history and the degree of per...that a reliable measure of individual adaptability on a single session can be obtained very quickly at Mi angular velocities up to 3 rev/min. Our

  11. Space motion sickness preflight adaptation training: preliminary studies with prototype trainers

    NASA Technical Reports Server (NTRS)

    Parker, D. E.; Rock, J. C.; von Gierke, H. E.; Ouyang, L.; Reschke, M. F.; Arrott, A. P.

    1987-01-01

    Preflight training frequently has been proposed as a potential solution to the problem of space motion sickness. The paper considers successively the otolith reinterpretation, the concept for a preflight adaptation trainer and the research with the Miami University Seesaw, the Wright Patterson Air-Force Base Dynamic Environment Simulator and the Visually Coupled Airborne Systems Simulator prototype adaptation trainers.

  12. Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations

    PubMed Central

    Puga-Guzmán, S.; Moreno-Valenzuela, J.; Santibáñez, V.

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910

  13. Adaptive neural network motion control of manipulators with experimental evaluations.

    PubMed

    Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller.

  14. Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator

    NASA Technical Reports Server (NTRS)

    Kaneshige, John T.; Campbell, Stefan Forrest

    2009-01-01

    The objective of this work is to assess the strengths, weaknesses, and robustness characteristics of several MRAC (Model-Reference Adaptive Control) based adaptive control technologies garnering interest from the community as a whole. To facilitate this, a control study using piloted and unpiloted simulations to evaluate sensitivities and handling qualities was conducted. The adaptive control technologies under consideration were ALR (Adaptive Loop Recovery), BLS (Bounded Linear Stability), Hybrid Adaptive Control, L1, OCM (Optimal Control Modification), PMRAC (Predictor-based MRAC), and traditional MRAC

  15. Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

    NASA Technical Reports Server (NTRS)

    Rohrs, C. E.; Valavani, L.; Athans, M.; Stein, G.

    1985-01-01

    This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.

  16. Dual adaptation of apparent concomitant motion contingent on head rotation frequency

    NASA Technical Reports Server (NTRS)

    Post, R. B.; Welch, R. B.

    1998-01-01

    Perceived movement of a stationary visual stimulus during head motion was measured before and after adaptation intervals during which participants performed voluntary head oscillations while viewing a moving spot. During these intervals, participants viewed the spot stimulus moving alternately in the same direction as the head was moving during either .25- or 2.0-Hz oscillations, and then in the opposite direction as the head at the other of the two frequencies. Postadaptation measures indicated that the visual stimuli were perceived as stationary only if traveling in the same direction as that viewed during adaptation at the same frequency of head motion. Thus, opposite directions of spot motion were perceived as stationary following adaptation depending on head movement frequency. The results provide an example of the ability to establish dual (or "context-specific") adaptations to altered visual-vestibular feedback.

  17. Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

    NASA Technical Reports Server (NTRS)

    Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

    1992-01-01

    A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

  18. A robust adaptive nonlinear fault-tolerant controller via norm estimation for reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Hu, Chaofang; Gao, Zhifei; Ren, Yanli; Liu, Yunbing

    2016-11-01

    In this paper, a reusable launch vehicle (RLV) attitude control problem with actuator faults is addressed via the robust adaptive nonlinear fault-tolerant control (FTC) with norm estimation. Firstly, the accurate tracking task of attitude angles in the presence of parameter uncertainties and external disturbances is considered. A fault-free controller is proposed using dynamic surface control (DSC) combined with fuzzy adaptive approach. Furthermore, the minimal learning parameter strategy via norm estimation technique is introduced to reduce the multi-parameter adaptive computation burden of fuzzy approximation of the lump uncertainties. Secondly, a compensation controller is designed to handle the partial loss fault of actuator effectiveness. The unknown maximum eigenvalue of actuator efficiency loss factors is estimated online. Moreover, stability analysis guarantees that all signals of the closed-loop control system are semi-global uniformly ultimately bounded. Finally, illustrative simulations show the effectiveness of the proposed method.

  19. Assistance using adaptive oscillators: robustness to errors in the identification of the limb parameters.

    PubMed

    Rinderknecht, Mike Domenik; Delaloye, Fabien André; Crespi, Alessandro; Ronsse, Renaud; Ijspeert, Auke Jan

    2011-01-01

    This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify.

  20. Content-Adaptive Robust Image Watermarking with Posterior HMM-Based Detector

    NASA Astrophysics Data System (ADS)

    Wang, Chuntao; Ni, Jiangqun; Zhang, Rongyue; Kwon, Goo-Rak; Ko, Sung-Jea

    Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.

  1. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

    PubMed Central

    Carmena, Jose M.

    2016-01-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to

  2. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    PubMed

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  3. Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster

    PubMed Central

    Williams, CM; Watanabe, M; Guarracino, MR; Ferraro, MB; Edison, AS; Morgan, TJ; Boroujerdi, AFB; Hahn, DA

    2015-01-01

    When ectotherms are exposed to low temperatures, they enter a cold-induced coma (chill coma) that prevents resource acquisition, mating, oviposition, and escape from predation. There is substantial variation in time taken to recover from chill coma both within and among species, and this variation is correlated with habitat temperatures such that insects from cold environments recover more quickly. This suggests an adaptive response, but the mechanisms underlying variation in recovery times are unknown, making it difficult to decisively test adaptive hypotheses. We use replicated lines of Drosophila melanogaster selected in the laboratory for fast (hardy) or slow (susceptible) chill-coma recovery times to investigate modifications to metabolic profiles associated with cold adaptation. We measured metabolite concentrations of flies before, during, and after cold exposure using NMR spectroscopy to test the hypotheses that hardy flies maintain metabolic homeostasis better during cold exposure and recovery, and that their metabolic networks are more robust to cold-induced perturbations. The metabolites of cold-hardy flies were less cold responsive and their metabolic networks during cold exposure were more robust, supporting our hypotheses. Metabolites involved in membrane lipid synthesis, tryptophan metabolism, oxidative stress, energy balance, and proline metabolism were altered by selection on cold tolerance. We discuss the potential significance of these alterations. PMID:25308124

  4. Reasoned Decision Making Without Math? Adaptability and Robustness in Response to Surprise.

    PubMed

    Smithson, Michael; Ben-Haim, Yakov

    2015-10-01

    Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam.

  5. Defense planning for the Post-Cold War Era. Giving Meaning to Flexibility, Adaptiveness, and Robustness of Capability

    DTIC Science & Technology

    1993-01-01

    care was guaranteed. Family policies helped to sup- port child care. Most importantly, it became extremely difficult to terminate employees for...management value seen in adaptiveness, flexibilty , and processes robustness of capabilities. Increasing flexibility Decentralization to CINCs where

  6. Model-Based Nonrigid Motion Analysis Using Natural Feature Adaptive Mesh

    SciTech Connect

    Zhang, Y.; Goldgof, D.B.; Sarkar, S.; Tsap, L.V.

    2000-04-25

    The success of nonrigid motion analysis using physical finite element model is dependent on the mesh that characterizes the object's geometric structure. We suggest a deformable mesh adapted to the natural features of images. The adaptive mesh requires much fewer number of nodes than the fixed mesh which was used in our previous work. We demonstrate the higher efficiency of the adaptive mesh in the context of estimating burn scar elasticity relative to normal skin elasticity using the observed 2D image sequence. Our results show that the scar assessment method based on the physical model using natural feature adaptive mesh can be applied to images which do not have artificial markers.

  7. Effect of adaptive motion on cyclic fatigue resistance of a nickel titanium instrument designed for retreatment

    PubMed Central

    Yılmaz, Koray; Uslu, Gülşah

    2017-01-01

    Objectives The aim of this study was to evaluate the cyclic fatigue resistance of the ProTaper Universal D1 file (Dentsply Maillefer) under continuous and adaptive motion. Materials and Methods Forty ProTaper Universal D1 files were included in this study. The cyclic fatigue tests were performed using a dynamic cyclic fatigue testing device, which had an artificial stainless steel canal with a 60° angle of curvature and a 5 mm radius of curvature. The files were randomly divided into two groups (Group 1, Rotary motion; Group 2, Adaptive motion). The time to failure of the files were recorded in seconds. The number of cycles to failure (NCF) was calculated for each group. The data were statistically analyzed using Student's t-test. The statistical significant level was set at p < 0.05. Results The cyclic fatigue resistance of the adaptive motion group was significantly higher than the rotary motion group (p < 0.05). Conclusion Within the limitations of the present study, the ‘Adaptive motion’ significantly increased the resistance of the ProTaper Universal D1 file to cyclic facture. PMID:28194362

  8. Robust adaptive tracking control of MIMO nonlinear systems in the presence of actuator hysteresis

    NASA Astrophysics Data System (ADS)

    Fu, Guiyuan; Ou, Linlin; Zhang, Weidong

    2016-07-01

    Adaptive tracking control of a class of MIMO nonlinear system preceded by unknown hysteresis is investigated. Based on dynamic surface control, an adaptive robust control law is developed and compensators are designed to mitigate the influences of both the unknown bounded external uncertainties and the unknown Prandtl-Islinskii hysteresis. By adopting the low-pass filters, the explosion of complexity caused by tedious computation of the time derivatives of the virtual control laws is overcome. With the proposed control scheme, the closed-loop system is proved to be semi-globally ultimately bounded by the Lyapunov stability theory, and the output of the controlled system can track the desired trajectories with an arbitrarily small error. Finally, numerical simulations are given to verify the effectiveness of the proposed approach.

  9. Robust respiration rate estimation using adaptive Kalman filtering with textile ECG sensor and accelerometer.

    PubMed

    Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi; Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi; Koizumi, Hiroshi; Ogasawara, Takayuki; Tajima, Takuro; Kasahara, Ryoichi; Lepine, Nicholas N

    2016-08-01

    An adaptive Kalman filter-based fusion algorithm capable of estimating respiration rate for unobtrusive respiratory monitoring is proposed. Using both signal characteristics and a priori information, the Kalman filter is adaptively optimized to improve accuracy. Furthermore, the system is able to combine the respiration-related signals extracted from a textile ECG sensor and an accelerometer to create a single robust measurement. We measured derived respiratory rates and, when compared to a reference, found root-mean-square error of 2.11 breaths-per-minute (BrPM) while lying down, 2.30 BrPM while sitting, 5.97 BrPM while walking, and 5.98 BrPM while running. These results demonstrate that the proposed system is applicable to unobtrusive monitoring for various applications.

  10. A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts

    PubMed Central

    Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin

    2017-01-01

    The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking. PMID:28212327

  11. A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts.

    PubMed

    Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin

    2017-02-16

    The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.

  12. Application and assessment of a robust elastic motion correction algorithm to dynamic MRI.

    PubMed

    Herrmann, K-H; Wurdinger, S; Fischer, D R; Krumbein, I; Schmitt, M; Hermosillo, G; Chaudhuri, K; Krishnan, A; Salganicoff, M; Kaiser, W A; Reichenbach, J R

    2007-01-01

    The purpose of this study was to assess the performance of a new motion correction algorithm. Twenty-five dynamic MR mammography (MRM) data sets and 25 contrast-enhanced three-dimensional peripheral MR angiographic (MRA) data sets which were affected by patient motion of varying severeness were selected retrospectively from routine examinations. Anonymized data were registered by a new experimental elastic motion correction algorithm. The algorithm works by computing a similarity measure for the two volumes that takes into account expected signal changes due to the presence of a contrast agent while penalizing other signal changes caused by patient motion. A conjugate gradient method is used to find the best possible set of motion parameters that maximizes the similarity measures across the entire volume. Images before and after correction were visually evaluated and scored by experienced radiologists with respect to reduction of motion, improvement of image quality, disappearance of existing lesions or creation of artifactual lesions. It was found that the correction improves image quality (76% for MRM and 96% for MRA) and diagnosability (60% for MRM and 96% for MRA).

  13. Motion-adapted pulse sequences for oriented sample (OS) solid-state NMR of biopolymers.

    PubMed

    Lu, George J; Opella, Stanley J

    2013-08-28

    One of the main applications of solid-state NMR is to study the structure and dynamics of biopolymers, such as membrane proteins, under physiological conditions where the polypeptides undergo global motions as they do in biological membranes. The effects of NMR radiofrequency irradiations on nuclear spins are strongly influenced by these motions. For example, we previously showed that the MSHOT-Pi4 pulse sequence yields spectra with resonance line widths about half of those observed using the conventional pulse sequence when applied to membrane proteins undergoing rapid uniaxial rotational diffusion in phospholipid bilayers. In contrast, the line widths were not changed in microcrystalline samples where the molecules did not undergo global motions. Here, we demonstrate experimentally and describe analytically how some Hamiltonian terms are susceptible to sample motions, and it is their removal through the critical π/2 Z-rotational symmetry that confers the "motion adapted" property to the MSHOT-Pi4 pulse sequence. This leads to the design of separated local field pulse sequence "Motion-adapted SAMPI4" and is generalized to an approach for the design of decoupling sequences whose performance is superior in the presence of molecular motions. It works by cancelling the spin interaction by explicitly averaging the reduced Wigner matrix to zero, rather than utilizing the 2π nutation to average spin interactions. This approach is applicable to both stationary and magic angle spinning solid-state NMR experiments.

  14. Evolution of motion uncertainty in rectal cancer: implications for adaptive radiotherapy

    NASA Astrophysics Data System (ADS)

    Kleijnen, Jean-Paul J. E.; van Asselen, Bram; Burbach, Johannes P. M.; Intven, Martijn; Philippens, Marielle E. P.; Reerink, Onne; Lagendijk, Jan J. W.; Raaymakers, Bas W.

    2016-01-01

    Reduction of motion uncertainty by applying adaptive radiotherapy strategies depends largely on the temporal behavior of this motion. To fully optimize adaptive strategies, insight into target motion is needed. The purpose of this study was to analyze stability and evolution in time of motion uncertainty of both the gross tumor volume (GTV) and clinical target volume (CTV) for patients with rectal cancer. We scanned 16 patients daily during one week, on a 1.5 T MRI scanner in treatment position, prior to each radiotherapy fraction. Single slice sagittal cine MRIs were made at the beginning, middle, and end of each scan session, for one minute at 2 Hz temporal resolution. GTV and CTV motion were determined by registering a delineated reference frame to time-points later in time. The 95th percentile of observed motion (dist95%) was taken as a measure of motion. The stability of motion in time was evaluated within each cine-MRI separately. The evolution of motion was investigated between the reference frame and the cine-MRIs of a single scan session and between the reference frame and the cine-MRIs of several days later in the course of treatment. This observed motion was then converted into a PTV-margin estimate. Within a one minute cine-MRI scan, motion was found to be stable and small. Independent of the time-point within the scan session, the average dist95% remains below 3.6 mm and 2.3 mm for CTV and GTV, respectively 90% of the time. We found similar motion over time intervals from 18 min to 4 days. When reducing the time interval from 18 min to 1 min, a large reduction in motion uncertainty is observed. A reduction in motion uncertainty, and thus the PTV-margin estimate, of 71% and 75% for CTV and tumor was observed, respectively. Time intervals of 15 and 30 s yield no further reduction in motion uncertainty compared to a 1 min time interval.

  15. Reversible adapting layer produces robust single-crystal electrocatalyst for oxygen evolution

    PubMed Central

    Tung, Ching-Wei; Hsu, Ying-Ya; Shen, Yen-Ping; Zheng, Yixin; Chan, Ting-Shan; Sheu, Hwo-Shuenn; Cheng, Yuan-Chung; Chen, Hao Ming

    2015-01-01

    Electrochemically converting water into oxygen/hydrogen gas is ideal for high-density renewable energy storage in which robust electrocatalysts for efficient oxygen evolution play crucial roles. To date, however, electrocatalysts with long-term stability have remained elusive. Here we report that single-crystal Co3O4 nanocube underlay with a thin CoO layer results in a high-performance and high-stability electrocatalyst in oxygen evolution reaction. An in situ X-ray diffraction method is developed to observe a strong correlation between the initialization of the oxygen evolution and the formation of active metal oxyhydroxide phase. The lattice of skin layer adapts to the structure of the active phase, which enables a reversible facile structural change that facilitates the chemical reactions without breaking the scaffold of the electrocatalysts. The single-crystal nanocube electrode exhibits stable, continuous oxygen evolution for >1,000 h. This robust stability is attributed to the complementary nature of defect-free single-crystal electrocatalyst and the reversible adapting layer. PMID:26315066

  16. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images.

    PubMed

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-07-05

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms.

  17. Robustness study of the pseudo open-loop controller for multiconjugate adaptive optics.

    PubMed

    Piatrou, Piotr; Gilles, Luc

    2005-02-20

    Robustness of the recently proposed "pseudo open-loop control" algorithm against various system errors has been investigated for the representative example of the Gemini-South 8-m telescope multiconjugate adaptive-optics system. The existing model to represent the adaptive-optics system with pseudo open-loop control has been modified to account for misalignments, noise and calibration errors in deformable mirrors, and wave-front sensors. Comparison with the conventional least-squares control model has been done. We show with the aid of both transfer-function pole-placement analysis and Monte Carlo simulations that POLC remains remarkably stable and robust against very large levels of system errors and outperforms in this respect least-squares control. Approximate stability margins as well as performance metrics such as Strehl ratios and rms wave-front residuals averaged over a 1-arc min field of view have been computed for different types and levels of system errors to quantify the expected performance degradation.

  18. 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.

  19. Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

    NASA Astrophysics Data System (ADS)

    Kim, Y.; Chung, E. S.

    2014-12-01

    This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

  20. Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings

    NASA Technical Reports Server (NTRS)

    Knospe, Carl R.; Tamer, Samir M.; Fedigan, Stephen J.

    1996-01-01

    Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.

  1. Robust adaptive feedforward control and achievable tracking for systems with time delays

    NASA Astrophysics Data System (ADS)

    Buehner, Michael R.; Young, Peter M.

    2015-04-01

    A feedback/feedforward controller architecture is developed that characterises the achievable reference tracking of real time inputs for both minimum phase and non-minimum phase systems with time delays, when there are no modelling errors or external disturbances. This characterisation is obtained by factoring the plant into its minimum phase, non-minimum phase, and time delay components, which are used to design two feedforward controllers that inject signals into two points of the feedback loop. Design constraints are provided that determine both the types of signals that may be achieved, and the feedforward controllers that will generate that output. Of course, in practice, both modelling errors and external disturbances will be present. In this case, we develop robust analysis tools that both guide the feedback controller design process, and provide rigorous robust tracking performance that guarantees for the overall resulting closed-loop system. Robust methods for designing the feedforward controllers are presented, and numerical examples are provided. The performance of this architecture depends strongly on the choice of design parameters, and the accuracy of the plant model used. Hence, the use of adaptation methods is also considered, and it is shown that they can readily be employed to improve the performance of this control methodology.

  2. Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system.

    PubMed

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

    2009-06-01

    In this paper, a robust dynamic sliding mode control system (RDSMC) using a recurrent Elman neural network (RENN) is proposed to control the position of a levitated object of a magnetic levitation system considering the uncertainties. First, a dynamic model of the magnetic levitation system is derived. Then, a proportional-integral-derivative (PID)-type sliding-mode control system (SMC) is adopted for tracking of the reference trajectories. Moreover, a new PID-type dynamic sliding-mode control system (DSMC) is proposed to reduce the chattering phenomenon. However, due to the hardware being limited and the uncertainty bound being unknown of the switching function for the DSMC, an RDSMC is proposed to improve the control performance and further increase the robustness of the magnetic levitation system. In the RDSMC, an RENN estimator is used to estimate an unknown nonlinear function of lumped uncertainty online and replace the switching function in the hitting control of the DSMC directly. The adaptive learning algorithms that trained the parameters of the RENN online are derived using Lyapunov stability theorem. Furthermore, a robust compensator is proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher order terms in Taylor series. Finally, some experimental results of tracking the various periodic trajectories demonstrate the validity of the proposed RDSMC for practical applications.

  3. Robust Scale Adaptive Tracking by Combining Correlation Filters with Sequential Monte Carlo

    PubMed Central

    Ma, Junkai; Luo, Haibo; Hui, Bin; Chang, Zheng

    2017-01-01

    A robust and efficient object tracking algorithm is required in a variety of computer vision applications. Although various modern trackers have impressive performance, some challenges such as occlusion and target scale variation are still intractable, especially in the complex scenarios. This paper proposes a robust scale adaptive tracking algorithm to predict target scale by a sequential Monte Carlo method and determine the target location by the correlation filter simultaneously. By analyzing the response map of the target region, the completeness of the target can be measured by the peak-to-sidelobe rate (PSR), i.e., the lower the PSR, the more likely the target is being occluded. A strict template update strategy is designed to accommodate the appearance change and avoid template corruption. If the occlusion occurs, a retained scheme is allowed and the tracker refrains from drifting away. Additionally, the feature integration is incorporated to guarantee the robustness of the proposed approach. The experimental results show that our method outperforms other state-of-the-art trackers in terms of both the distance precision and overlap precision on the publicly available TB-50 dataset. PMID:28273840

  4. Flying triangulation--an optical 3D sensor for the motion-robust acquisition of complex objects.

    PubMed

    Ettl, Svenja; Arold, Oliver; Yang, Zheng; Häusler, Gerd

    2012-01-10

    Three-dimensional (3D) shape acquisition is difficult if an all-around measurement of an object is desired or if a relative motion between object and sensor is unavoidable. An optical sensor principle is presented-we call it "flying triangulation"-that enables a motion-robust acquisition of 3D surface topography. It combines a simple handheld sensor with sophisticated registration algorithms. An easy acquisition of complex objects is possible-just by freely hand-guiding the sensor around the object. Real-time feedback of the sequential measurement results enables a comfortable handling for the user. No tracking is necessary. In contrast to most other eligible sensors, the presented sensor generates 3D data from each single camera image.

  5. SU-E-T-527: Is CTV-Based Robust Optimized IMPT in Non-Small-Cell Lung Cancer Robust Against Respiratory Motion?

    SciTech Connect

    Anetai, Y; Mizuno, H; Sumida, I; Ogawa, K; Takegawa, H; Inoue, T; Koizumi, M; Veld, A van’t; Korevaar, E

    2015-06-15

    Purpose: To determine which proton planning technique on average-CT is more vulnerable to respiratory motion induced density changes and interplay effect among (a) IMPT of CTV-based minimax robust optimization with 5mm set-up error considered, (b, c) IMPT/SFUD of 5mm-expanded PTV optimization. Methods: Three planning techniques were optimized in Raystation with a prescription of 60/25 (Gy/fractions) and almost the same OAR constraints/objectives for each of 10 NSCLC patients. 4D dose without/with interplay effect was recalculated on eight 4D-CT phases and accumulated after deforming the dose of each phase to a reference (exhalation phase). The change of D98% of each CTV caused by density changes and interplay was determined. In addition, evaluation of the DVH information vector (D99%, D98%, D95%, Dave, D50%, D2%, D1%) which compares the whole DVH by η score = (cosine similarity × Pearson correlation coefficient − 0.9) × 1000 quantified the degree of DVH change: score below 100 indicates changed DVH. Results: Three 3D plans of each technique satisfied our clinical goals. D98% shift mean±SD (Gy) due to density changes was largest in (c): −0.78±1.1 while (a): −0.11±0.65 and (b): − 0.59±0.93. Also the shift due to interplay effect most was (c): −.54±0.70 whereas (a): −0.25±0.93 and (b): −0.12±0.13. Moreover lowest η score caused by density change was also (c): 69, while (a) and (b) kept around 90. η score also indicated less effect of interplay than density changes. Note that generally the changed DVH were still acceptable clinically. Paired T-tests showed a significantly smaller density change effect in (a) (p<0.05) than in (b) or (c) and no significant difference in interplay effect. Conclusion: CTV-based robust optimized IMPT was more robust against respiratory motion induced density changes than PTV-based IMPT and SFUD. The interplay effect was smaller than the effect of density changes and similar among the three techniques. The JSPS Core

  6. Lightweight wrist photoplethysmography for heavy exercise: motion robust heart rate monitoring algorithm

    PubMed Central

    Kim, Insoo

    2015-01-01

    The challenge of heart rate monitoring based on wrist photoplethysmography (PPG) during heavy exercise is addressed. PPG is susceptible to motion artefacts, which have to be mitigated for accurate heart rate estimation. Motion artefacts are particularly apparent for wrist devices, for example, a smart watch, because of the high mobility of the arms. Proposed is a low complexity highly accurate heart rate estimation method for continuous heart rate monitoring using wrist PPG. The proposed method achieved 2.57% mean absolute error in a test data set where subjects ran for a maximum speed of 17 km/h. PMID:26609397

  7. An adaptive-gain complementary filter for real-time human motion tracking with MARG sensors in free-living environments.

    PubMed

    Tian, Ya; Wei, Hongxing; Tan, Jindong

    2013-03-01

    High-resolution, real-time data obtained by human motion tracking systems can be used for gait analysis, which helps better understanding the cause of many diseases for more effective treatments, such as rehabilitation for outpatients or recovery from lost motor functions after a stroke. In order to achieve real-time ambulatory human motion tracking with low-cost MARG (magnetic, angular rate, and gravity) sensors, a computationally efficient and robust algorithm for orientation estimation is critical. This paper presents an analytically derived method for an adaptive-gain complementary filter based on the convergence rate from the Gauss-Newton optimization algorithm (GNA) and the divergence rate from the gyroscope, which is referred as adaptive-gain orientation filter (AGOF) in this paper. The AGOF has the advantages of one iteration calculation to reduce the computing load and accurate estimation of gyroscope measurement error. Moreover, for handling magnetic distortions especially in indoor environments and movements with excessive acceleration, adaptive measurement vectors and a reference vector for earth's magnetic field selection schemes are introduced to help the GNA find more accurate direction of gyroscope error. The features of this approach include the accurate estimation of the gyroscope bias to correct the instantaneous gyroscope measurements and robust estimation in conditions of fast motions and magnetic distortions. Experimental results are presented to verify the performance of the proposed method, which shows better accuracy of orientation estimation than several well-known methods.

  8. Robust Impacts of Climate Change in Europe and Why Study Scale is Important for Adaptation

    NASA Astrophysics Data System (ADS)

    Donnelly, C.; Andersson, J.; Olsson, J.; Bosshard, T.; Yang, W.; Berg, P.; Arheimer, B.

    2015-12-01

    Impacts of climate change on water resources in Europe have been studied using multiple climate, hydrological and downscaling models and at multiple scales. Although results seem to differ largely between these studies, robust qualitative results have emerged at the European scale. Generally, a drying trend coupled with more intense extremes (floods & droughts) is observed in southern Europe, whereas a wetting trend coupled with less intense extremes is observed in Northern Europe. The location of the change between wetting and drying leads to uncertainty of climate change impacts in central Europe. Also, temperature-related hydrological processes lead to more robust predictions than precipitation-related processes as climate models are more consistent for temperature. For European hydrology, this leads to more robust predictions in regions with snow-dominated hydrology and where evapotranspiration dominates the water cycle. Robust predictions of changes to the seasonality of discharge are seen in snow-dominated regions (Fennoscandinavia, Alps) while robust predictions of decreases in runoff are seen for the Iberian peninsula. While uncertainty in the projections mostly comes from climate uncertainty, predictions of impacts on soil moisture and low flows can be largely dependent on the choice of hydrological model where methods to estimate evapotranspiration and runoff differ widely. While the regional-scale results show some robustness, there can be large local-scale differences even where the same catchment is considered at different scales. Furthermore, understanding of uncertainties due to correction and downscaling procedures are only beginning to emerge. Our evaluations of bias-correction indicate that uncertainties vary considerably depending on the variable. The scale of uncertainty due to bias-correction can be similar to the projected climate changes and to the uncertainty from the climate models. In this presentation we put forward a new bottom-up method

  9. Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG

    NASA Astrophysics Data System (ADS)

    Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.

    2011-12-01

    The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

  10. New principle for measuring arterial blood oxygenation, enabling motion-robust remote monitoring

    PubMed Central

    van Gastel, Mark; Stuijk, Sander; de Haan, Gerard

    2016-01-01

    Finger-oximeters are ubiquitously used for patient monitoring in hospitals worldwide. Recently, remote measurement of arterial blood oxygenation (SpO2) with a camera has been demonstrated. Both contact and remote measurements, however, require the subject to remain static for accurate SpO2 values. This is due to the use of the common ratio-of-ratios measurement principle that measures the relative pulsatility at different wavelengths. Since the amplitudes are small, they are easily corrupted by motion-induced variations. We introduce a new principle that allows accurate remote measurements even during significant subject motion. We demonstrate the main advantage of the principle, i.e. that the optimal signature remains the same even when the SNR of the PPG signal drops significantly due to motion or limited measurement area. The evaluation uses recordings with breath-holding events, which induce hypoxemia in healthy moving subjects. The events lead to clinically relevant SpO2 levels in the range 80–100%. The new principle is shown to greatly outperform current remote ratio-of-ratios based methods. The mean-absolute SpO2-error (MAE) is about 2 percentage-points during head movements, where the benchmark method shows a MAE of 24 percentage-points. Consequently, we claim ours to be the first method to reliably measure SpO2 remotely during significant subject motion. PMID:27924930

  11. A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

    NASA Astrophysics Data System (ADS)

    Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick

    2013-05-01

    This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.

  12. Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm

    SciTech Connect

    Yi, Jianbing; Yang, Xuan Li, Yan-Ran; Chen, Guoliang

    2015-10-15

    Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the

  13. Adaptive search range adjustment and multiframe selection algorithm for motion estimation in H.264/AVC

    NASA Astrophysics Data System (ADS)

    Liu, Yingzhe; Wang, Jinxiang; Fu, Fangfa

    2013-04-01

    The H.264/AVC video standard adopts a fixed search range (SR) and fixed reference frame (RF) for motion estimation. These fixed settings result in a heavy computational load in the video encoder. We propose a dynamic SR and multiframe selection algorithm to improve the computational efficiency of motion estimation. By exploiting the relationship between the predicted motion vector and the SR size, we develop an adaptive SR adjustment algorithm. We also design a RF selection scheme based on the correlation between the different block sizes of the macroblock. Experimental results show that our algorithm can significantly reduce the computational complexity of motion estimation compared with the JM15.1 reference software, with a negligible decrease in peak signal-to-noise ratio and a slight increase in bit rate. Our algorithm also outperforms existing methods in terms of its low complexity and high coding quality.

  14. An SRWNN-based approach on developing a self-learning and self-evolving adaptive control system for motion platforms

    NASA Astrophysics Data System (ADS)

    Onur Ari, Evrim; Kocaoglan, Erol

    2016-02-01

    In this paper, a self-recurrent wavelet neural network (SRWNN)-based indirect adaptive control architecture is modified for performing speed control of a motion platform. The transient behaviour of the original learning algorithm has been improved by modifying the learning rate updates. The contribution of the proposed modification has been verified via both simulations and experiments. Moreover, the performance of the proposed architecture is compared with robust RST designs performed on a similar benchmark system, to show that via adaptive nonlinear control, it is possible to obtain a fast step response without degrading the robustness of a multi-body mechanical system. Finally, the architecture is further improved so as to possess structural learning for populating the SRWNNs automatically, rather than employing static network structures, and simulation results are provided to show the performance of the proposed structural learning algorithm.

  15. Robust motion tracking control of robotic arms based on the generalized energy accumulation principle

    NASA Technical Reports Server (NTRS)

    Song, Y. D.; Anderson, J. N.; Homaifar, A.; Lai, H. Y.

    1992-01-01

    Consider a rigid-link robot with the dynamic model tau = H(q;p)q''+C(q,q',p)q'+G(q;p)+Nu(t) where Nu(.) denotes a bounded external disturbance. The objective addressed herein is to find a control strategy that exhibits the following features: (1) simple to implement, (2) easy to code for program, and (3) robust to possible time-varying uncertainties.

  16. Robust adaptive neural control for a class of uncertain MIMO nonlinear systems

    NASA Astrophysics Data System (ADS)

    Wang, Chenliang; Lin, Yan

    2015-08-01

    In this paper, a novel robust adaptive neural control scheme is proposed for a class of uncertain multi-input multi-output nonlinear systems. The proposed scheme has the following main features: (1) a kind of Hurwitz condition is introduced to handle the state-dependent control gain matrix and some assumptions in existing schemes are relaxed; (2) by introducing a novel matrix normalisation technique, it is shown that all bound restrictions imposed on the control gain matrix in existing schemes can be removed; (3) the singularity problem is avoided without any extra effort, which makes the control law quite simple. Besides, with the aid of the minimal learning parameter technique, only one parameter needs to be updated online regardless of the system input-output dimension and the number of neural network nodes. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

  17. Adaptive robust synchronization of Rossler systems in the presence of unknown matched time-varying parameters

    NASA Astrophysics Data System (ADS)

    Arefi, M. M.; Jahed-Motlagh, M. R.

    2010-12-01

    This paper deals with the problem of adaptive robust synchronization of chaotic systems based on the Lyapunov theory. A controller is designed for a feedback linearizable error system with matched uncertainties. The proposed method shows that the drive and response systems are synchronized and states of the response system track the states of the drive system as time tends to infinity. Since this approach does not require any information about the bound of uncertainties, this information is not needed in advance. In order to prevent the frequent switching phenomenon in the control signal, the method is modified such that the norm of tracking error is bounded. Numerical simulations on two uncertain Rossler systems with matched uncertainties show fast responses of tracking error, while the errors are Uniformly Ultimately Bounded, and the control signal is reasonably smooth.

  18. Pressure regulation for earth pressure balance control on shield tunneling machine by using adaptive robust control

    NASA Astrophysics Data System (ADS)

    Xie, Haibo; Liu, Zhibin; Yang, Huayong

    2016-05-01

    Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

  19. A self-adaptive and nonmechanical motion autofocusing system for optical microscopes.

    PubMed

    Qu, Yufu; Zhu, Shenyu; Zhang, Ping

    2016-11-01

    For the design of a passive autofocusing (AF) system for optical microscopes, many time-consuming and tedious experiments have been performed to determine and design a better focus criterion function, owing to the sample-dependence of this function. To accelerate the development of the AF systems in optical microscopes and to increase AF speed as well as maintain the AF accuracy, this study proposes a self-adaptive and nonmechanical motion AF system. The presented AF system does not require the selection and design of a focus criterion function when it is developed. Instead, the system can automatically determine a better focus criterion function for an observed sample by analyzing the texture features of the sample and subsequently perform an AF procedure to bring the sample into focus in the objective of an optical microscope. In addition, to increase the AF speed, the Z axis scanning of the mechanical motion of the sample or the objective is replaced by focusing scanning performed by a liquid lens, which is driven by an electrical current and does not involve mechanical motion. Experiments show that the reproducibility of the results obtained with the proposed self-adaptive and nonmechanical motion AF system is better than that provided by that of traditional AF systems, and that the AF speed is 10 times faster than that of traditional AF systems. Also, the self-adaptive function increased the speed of AF process by an average of 10.5% than Laplacian and Tenegrad functions.

  20. Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

    PubMed

    Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

    2013-09-01

    Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. .

  1. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    PubMed

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical.

  2. The adaptation of GDL motion recognition system to sport and rehabilitation techniques analysis.

    PubMed

    Hachaj, Tomasz; Ogiela, Marek R

    2016-06-01

    The main novelty of this paper is presenting the adaptation of Gesture Description Language (GDL) methodology to sport and rehabilitation data analysis and classification. In this paper we showed that Lua language can be successfully used for adaptation of the GDL classifier to those tasks. The newly applied scripting language allows easily extension and integration of classifier with other software technologies and applications. The obtained execution speed allows using the methodology in the real-time motion capture data processing where capturing frequency differs from 100 Hz to even 500 Hz depending on number of features or classes to be calculated and recognized. Due to this fact the proposed methodology can be used to the high-end motion capture system. We anticipate that using novel, efficient and effective method will highly help both sport trainers and physiotherapist in they practice. The proposed approach can be directly applied to motion capture data kinematics analysis (evaluation of motion without regard to the forces that cause that motion). The ability to apply pattern recognition methods for GDL description can be utilized in virtual reality environment and used for sport training or rehabilitation treatment.

  3. Adaptive three-dimensional motion-compensated wavelet transform for image sequence coding

    NASA Astrophysics Data System (ADS)

    Leduc, Jean-Pierre

    1994-09-01

    This paper describes a 3D spatio-temporal coding algorithm for the bit-rate compression of digital-image sequences. The coding scheme is based on different specificities namely, a motion representation with a four-parameter affine model, a motion-adapted temporal wavelet decomposition along the motion trajectories and a signal-adapted spatial wavelet transform. The motion estimation is performed on the basis of four-parameter affine transformation models also called similitude. This transformation takes into account translations, rotations and scalings. The temporal wavelet filter bank exploits bi-orthogonal linear-phase dyadic decompositions. The 2D spatial decomposition is based on dyadic signal-adaptive filter banks with either para-unitary or bi-orthogonal bases. The adaptive filtering is carried out according to a performance criterion to be optimized under constraints in order to eventually maximize the compression ratio at the expense of graceful degradations of the subjective image quality. The major principles of the present technique is, in the analysis process, to extract and to separate the motion contained in the sequences from the spatio-temporal redundancy and, in the compression process, to take into account of the rate-distortion function on the basis of the spatio-temporal psycho-visual properties to achieve the most graceful degradations. To complete this description of the coding scheme, the compression procedure is therefore composed of scalar quantizers which exploit the spatio-temporal 3D psycho-visual properties of the Human Visual System and of entropy coders which finalize the bit rate compression.

  4. Motion Analysis of 100 Mediastinal Lymph Nodes: Potential Pitfalls in Treatment Planning and Adaptive Strategies

    SciTech Connect

    Pantarotto, Jason R.; Piet, Anna H.M.; Vincent, Andrew; Soernsen de Koste, John R. van; Senan, Suresh

    2009-07-15

    Purpose: The motion of mediastinal lymph nodes may undermine local control with involved-field radiotherapy. We studied patterns of nodal and tumor motion in 41 patients with lung cancer. Methods and Materials: Four-dimensional (4D) computed tomography planning scans were retrospectively evaluated to identify patients with clearly visible mediastinal lymph nodes. One hundred nodes from 14 patients with Stage I and 27 patients with Stage III were manually contoured in all 4D computed tomography respiratory phases. Motion was derived from changes in the nodal center-of-mass position. Primary tumors were also delineated in all phases for 16 patients with Stage III disease. Statistical analysis included a multivariate mixed-effects model of grouped data. Results: Average 3D nodal motion during quiet breathing was 0.68 cm (range, 0.17-1.64 cm); 77% moved greater than 0.5 cm, and 10% moved greater than 1.0 cm. Motion was greatest in the lower mediastinum (p = 0.002), and nodes measuring 2 cm or greater in diameter showed motion similar to that in smaller nodes. In 11 of 16 patients studied, at least one node moved more than the corresponding primary tumor. No association between 3D primary tumor motion and nodal motion was observed. For mobile primary tumors, phase offsets between the primary tumor and nodes of two or more and three or more phases were observed for 33% and 12% of nodes, respectively. Conclusions: Mediastinal nodal motion is common, with phase offsets seen between the primary tumor and different nodes in the same patient. Patient-specific information is needed to ensure geometric coverage, and adaptive strategies based solely on the primary tumor may be misleading.

  5. Flight control design using a blend of modern nonlinear adaptive and robust techniques

    NASA Astrophysics Data System (ADS)

    Yang, Xiaolong

    In this dissertation, the modern control techniques of feedback linearization, mu synthesis, and neural network based adaptation are used to design novel control laws for two specific applications: F/A-18 flight control and reusable launch vehicle (an X-33 derivative) entry guidance. For both applications, the performance of the controllers is assessed. As a part of a NASA Dryden program to develop and flight test experimental controllers for an F/A-18 aircraft, a novel method of combining mu synthesis and feedback linearization is developed to design longitudinal and lateral-directional controllers. First of all, the open-loop and closed-loop dynamics of F/A-18 are investigated. The production F/A-18 controller as well as the control distribution mechanism are studied. The open-loop and closed-loop handling qualities of the F/A-18 are evaluated using low order transfer functions. Based on this information, a blend of robust mu synthesis and feedback linearization is used to design controllers for a low dynamic pressure envelope of flight conditions. For both the longitudinal and the lateral-directional axes, a robust linear controller is designed for a trim point in the center of the envelope. Then by including terms to cancel kinematic nonlinearities and variations in the aerodynamic forces and moments over the flight envelope, a complete nonlinear controller is developed. In addition, to compensate for the model uncertainty, linearization error and variations between operating points, neural network based adaptation is added to the designed longitudinal controller. The nonlinear simulations, robustness and handling qualities analysis indicate that the performance is similar to or better than that for the production F/A-18 controllers. When the dynamic pressure is very low, the performance of both the experimental and the production flight controllers is degraded, but Level I handling qualities are still achieved. A new generation of Reusable Launch Vehicles

  6. Robustness of target dose coverage to motion uncertainties for scanned carbon ion beam tracking therapy of moving tumors

    NASA Astrophysics Data System (ADS)

    Eley, John Gordon; Newhauser, Wayne David; Richter, Daniel; Lüchtenborg, Robert; Saito, Nami; Bert, Christoph

    2015-02-01

    Beam tracking with scanned carbon ion radiotherapy achieves highly conformal target dose by steering carbon pencil beams to follow moving tumors using real-time magnetic deflection and range modulation. The purpose of this study was to evaluate the robustness of target dose coverage from beam tracking in light of positional uncertainties of moving targets and beams. To accomplish this, we simulated beam tracking for moving targets in both water phantoms and a sample of lung cancer patients using a research treatment planning system. We modeled various deviations from perfect tracking that could arise due to uncertainty in organ motion and limited precision of a scanned ion beam tracking system. We also investigated the effects of interfractional changes in organ motion on target dose coverage by simulating a complete course of treatment using serial (weekly) 4DCTs from six lung cancer patients. For perfect tracking of moving targets, we found that target dose coverage was high ({{\\overline{V}}95} was 94.8% for phantoms and 94.3% for lung cancer patients, respectively) but sensitive to changes in the phase of respiration at the start of treatment and to the respiratory period. Phase delays in tracking the moving targets led to large degradation of target dose coverage (up to 22% drop for a 15° delay). Sensitivity to technical uncertainties in beam tracking delivery was minimal for a lung cancer case. However, interfractional changes in anatomy and organ motion led to large decreases in target dose coverage (target coverage dropped approximately 8% due to anatomy and motion changes after 1 week). Our findings provide a better understand of the importance of each of these uncertainties for beam tracking with scanned carbon ion therapy and can be used to inform the design of future scanned ion beam tracking systems.

  7. Robustness of Target Dose Coverage to Motion Uncertainties for Scanned Carbon Ion Beam Tracking Therapy of Moving Tumors

    PubMed Central

    Eley, John Gordon; Newhauser, Wayne David; Richter, Daniel; Lüchtenborg, Robert; Saito, Nami; Bert, Christoph

    2015-01-01

    Beam tracking with scanned carbon ion radiotherapy achieves highly conformal target dose by steering carbon pencil beams to follow moving tumors using real-time magnetic deflection and range modulation. The purpose of this study was to evaluate the robustness of target dose coverage from beam tracking in light of positional uncertainties of moving targets and beams. To accomplish this, we simulated beam tracking for moving targets in both water phantoms and a sample of lung cancer patients using a research treatment planning system. We modeled various deviations from perfect tracking that could arise due to uncertainty in organ motion and limited precision of a scanned ion beam tracking system. We also investigated the effects of interfractional changes in organ motion on target dose coverage by simulating a complete course of treatment using serial (weekly) 4DCTs from 6 lung cancer patients. For perfect tracking of moving targets, we found that target dose coverage was high (V̄95 was 94.8% for phantoms and 94.3% for lung cancer patients, respectively) but sensitive to changes in the phase of respiration at the start of treatment and to the respiratory period. Phase delays in tracking the moving targets led to large degradation of target dose coverage (up to 22% drop for a 15 degree delay). Sensitivity to technical uncertainties in beam tracking delivery was minimal for a lung cancer case. However, interfractional changes in anatomy and organ motion led to large decreases in target dose coverage (target coverage dropped approximately 8% due to anatomy and motion changes after 1 week). Our findings provide a better understand of the importance of each of these uncertainties for beam tracking with scanned carbon ion therapy and can be used to inform the design of future scanned ion beam tracking systems. PMID:25650520

  8. Robustness of target dose coverage to motion uncertainties for scanned carbon ion beam tracking therapy of moving tumors.

    PubMed

    Eley, John Gordon; Newhauser, Wayne David; Richter, Daniel; Lüchtenborg, Robert; Saito, Nami; Bert, Christoph

    2015-02-21

    Beam tracking with scanned carbon ion radiotherapy achieves highly conformal target dose by steering carbon pencil beams to follow moving tumors using real-time magnetic deflection and range modulation. The purpose of this study was to evaluate the robustness of target dose coverage from beam tracking in light of positional uncertainties of moving targets and beams. To accomplish this, we simulated beam tracking for moving targets in both water phantoms and a sample of lung cancer patients using a research treatment planning system. We modeled various deviations from perfect tracking that could arise due to uncertainty in organ motion and limited precision of a scanned ion beam tracking system. We also investigated the effects of interfractional changes in organ motion on target dose coverage by simulating a complete course of treatment using serial (weekly) 4DCTs from six lung cancer patients. For perfect tracking of moving targets, we found that target dose coverage was high ([Formula: see text] was 94.8% for phantoms and 94.3% for lung cancer patients, respectively) but sensitive to changes in the phase of respiration at the start of treatment and to the respiratory period. Phase delays in tracking the moving targets led to large degradation of target dose coverage (up to 22% drop for a 15° delay). Sensitivity to technical uncertainties in beam tracking delivery was minimal for a lung cancer case. However, interfractional changes in anatomy and organ motion led to large decreases in target dose coverage (target coverage dropped approximately 8% due to anatomy and motion changes after 1 week). Our findings provide a better understand of the importance of each of these uncertainties for beam tracking with scanned carbon ion therapy and can be used to inform the design of future scanned ion beam tracking systems.

  9. Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics.

    PubMed

    Li, Dongming; Sun, Changming; Yang, Jinhua; Liu, Huan; Peng, Jiaqi; Zhang, Lijuan

    2017-04-06

    An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.

  10. An adaptive and robust biological network based on the vacant-particle transportation model.

    PubMed

    Gunji, Yukio-Pegio; Shirakawa, Tomohiro; Niizato, Takayuki; Yamachiyo, Masaki; Tani, Iori

    2011-03-07

    A living system reveals local computing by referring to a whole system beyond the exploration-exploitation dilemma. The slime mold, Physarum polycephalum, uses protoplasmic flow to change its own outer shape, which yields the boundary condition and forms an adaptive and robust network. This observation suggests that the whole Physarum can be represented as a local protoplasmic flow system. Here, we show that a system composed of particles, which move and are modified based upon the particle transformation that contains the relationship between the parts and the whole, can emulate the network formed by Physarum. This system balances the exploration-exploitation trade-off and shows a scale-free sub-domain. By decreasing the number of particles, our model, VP-S, can emulate the Physarum adaptive network as it is attracted to a food stimulus. By increasing the number of particles, our model, VP-D, can emulate the pattern of a growing Physarum. The patterns produced by our model were compared with those of the Physarum pattern quantitatively, which showed that both patterns balance exploration with exploitation. This model should have a wide applicability to study biological collective phenomena in general.

  11. Structural and functional robustness of the adaptive-sorting signaling network

    NASA Astrophysics Data System (ADS)

    Pang, Ning-Ning

    2016-06-01

    A major task of study on ligand discrimination by T cells is the construction of a mechanistic model to account for threshold setting in response to variant ligands interacting with the same T-cell receptors. Recently, Lalanne and Francois in a seminal paper (2013 Phys. Rev. Lett. 110 218102) have addressed this question by constructing minimal core circuits such that the biological outputs can satisfy the essential properties of early T-cell activation. To make this core set of network topology a valuable tool for synthetic biologists to robustly engineer biological circuits, we are motivated to ask a general question: is adaptive response encoded by the proposed circuit topology structurally stable, regardless of the values of the kinetic parameters? This has particularly relevant effects for the network reliability, since failures in ligand discrimination result in either infection or autoimmune diseases. To the best of our knowledge, a rigorous and complete mathematical proof of this issue is still lacking in the literature. In this paper, by giving a rigorous mathematical proof, we have shown that this regulatory circuitry is appropriately designed and the existence, uniqueness, and globally asymptotic attractiveness of the steady state are preserved. Moreover, we further generalize the adaptive sorting module and undertake an extensive analysis on the trade-off between antagonism and sensitivity of T-cell ligand discrimination in various cellular conditions. Notably, the optimal phosphorylation step in which to place the regulatory motif is analytically obtained and numerically confirmed. Finally, relevant experimental facts and biological implications are discussed.

  12. Adaptive tracking of discriminative frequency components in electroencephalograms for a robust brain-computer interface

    NASA Astrophysics Data System (ADS)

    Thomas, Kavitha P.; Guan, Cuntai; Tong Lau, Chiew; Vinod, A. P.; Keng Ang, Kai

    2011-06-01

    In an electroencephalogram (EEG)-based brain-computer interface (BCI), motor imagery has been successfully used as a communication strategy. Motor imagery causes detectable amplitude changes in certain frequency bands of EEGs, which are dubbed event-related desynchronization\\synchronization. The frequency components that give effective discrimination between different types of motor imagery are subject specific and identification of these subject-specific discriminative frequency components (DFCs) is important for the accurate classification of motor imagery activities. In this paper, we propose a new method to estimate the DFC using the Fisher criterion and investigate the variability of these DFCs over multiple sessions of EEG recording. Observing the variability of DFC over sessions in the analysis, a new BCI approach called the Adaptively Weighted Spectral-Spatial Patterns (AWSSP) algorithm is proposed. AWSSP tracks the variation in DFC over time adaptively based on the deviation of discriminative weight values of frequency components. The classification performance of the proposed AWSSP is compared with a static BCI approach that employs fixed DFCs. In the offline and online experiments, AWSSP offers better classification performance than the static approach, emphasizing the significance of tracking the variability of DFCs in EEGs for developing robust motor imagery-based BCI systems. A study of the effect of feedback on the variation in DFCs is also performed in online experiments and it is found that the presence of visual feedback results in increased variation in DFCs.

  13. Robust Adaptive Beamforming Based on Low-Rank and Cross-Correlation Techniques

    NASA Astrophysics Data System (ADS)

    Ruan, Hang; de Lamare, Rodrigo C.

    2016-08-01

    This work presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the output of the beamformer. Firstly, we construct a general linear equation considered in large dimensions whose solution yields the steering vector mismatch. Then, we employ the idea of the full orthogonalization method (FOM), an orthogonal Krylov subspace based method, to iteratively estimate the steering vector mismatch in a reduced-dimensional subspace, resulting in the proposed orthogonal Krylov subspace projection mismatch estimation (OKSPME) method. We also devise adaptive algorithms based on stochastic gradient (SG) and conjugate gradient (CG) techniques to update the beamforming weights with low complexity and avoid any costly matrix inversion. The main advantages of the proposed low-rank and mismatch estimation techniques are their cost-effectiveness when dealing with high dimension subspaces or large sensor arrays. Simulations results show excellent performance in terms of the output signal-to-interference-plus-noise ratio (SINR) of the beamformer among all the compared RAB methods.

  14. Robust Visual Knowledge Transfer via Extreme Learning Machine Based Domain Adaptation.

    PubMed

    Zhang, Lei; Zhang, David

    2016-08-10

    We address the problem of visual knowledge adaptation by leveraging labeled patterns from source domain and a very limited number of labeled instances in target domain to learn a robust classifier for visual categorization. This paper proposes a new extreme learning machine based cross-domain network learning framework, that is called Extreme Learning Machine (ELM) based Domain Adaptation (EDA). It allows us to learn a category transformation and an ELM classifier with random projection by minimizing the -norm of the network output weights and the learning error simultaneously. The unlabeled target data, as useful knowledge, is also integrated as a fidelity term to guarantee the stability during cross domain learning. It minimizes the matching error between the learned classifier and a base classifier, such that many existing classifiers can be readily incorporated as base classifiers. The network output weights cannot only be analytically determined, but also transferrable. Additionally, a manifold regularization with Laplacian graph is incorporated, such that it is beneficial to semi-supervised learning. Extensively, we also propose a model of multiple views, referred as MvEDA. Experiments on benchmark visual datasets for video event recognition and object recognition, demonstrate that our EDA methods outperform existing cross-domain learning methods.

  15. Robust spectral analysis of thoraco-abdominal motion and oxymetry in obstructive sleep apnea.

    PubMed

    Nino, Cesar L; Rodriguez-Martinez, Carlos E; Gutierrez, Maria J; Singareddi, Ravi; Nino, Gustavo

    2013-01-01

    The diagnosis of obstructive sleep apnea (OSA) relies on polysomnography (PSG), a multidimensional biosignal recording that is conducted in sleep laboratories. Standard PSG montage involves the use of nasal-oral airflow sensors to visualize cyclic episodes of upper airflow interruption, which are considered diagnostic of sleep apnea. Given the high-cost and discomfort associated with in-laboratory PSG, there is an emergent need for novel technology that simplifies OSA screening and diagnosis with less expensive methods. The main goal of this project was to identify novel OSA signatures based on the spectral analysis of thoraco-abdominal motion channels. Our main hypothesis was that proper spectral analysis can detect OSA cycles in adults using simultaneous recording of oxygen saturation (SaO2) and either, chest or abdominal motion. A sample study on 35 individuals was conducted with statistically significant results that suggest a strong relationship between airflow-independent signals and oxygen saturation. The impact of this new approach is that it may allow the design of more comfortable and reliable portable devices for screening, diagnosis and monitoring of OSA, functioning only with oximetry and airflow-independent (abdominal or chest) breathing sensors.

  16. SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers

    SciTech Connect

    Liu, W; Schild, S; Bues, M; Liao, Z; Sahoo, N; Park, P; Li, H; Li, Y; Li, X; Shen, J; Anand, A; Dong, L; Zhu, X; Mohan, R

    2014-06-01

    Purpose: We compared conventionally optimized intensity-modulated proton therapy (IMPT) treatment plans against the worst-case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set-up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods: For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from the internal target volume (ITV). The second employed the worst-case robust optimization scheme that addressed set-up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two-sided paired t-tests. Results: Without respiratory motion considered, we affirmed that worst-case robust optimization is superior to PTV-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% - D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)]. Conclusion: Worst-case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly

  17. Local stimulus disambiguation with global motion filters predicts adaptive surround modulation.

    PubMed

    Dellen, Babette; Torras, Carme

    2013-10-01

    Humans have no problem segmenting different motion stimuli despite the ambiguity of local motion signals. Adaptive surround modulation, i.e., the apparent switching between integrative and antagonistic modes, is assumed to play a crucial role in this process. However, so far motion processing models based on local integration have not been able to provide a unifying explanation for this phenomenon. This motivated us to investigate the problem of local stimulus disambiguation in an alternative and fundamentally distinct motion-processing model which uses global motion filters for velocity computation. Local information is reconstructed at the end of the processing stream through the constructive interference of global signals, i.e., inverse transformations. We show that in this model local stimulus disambiguation can be achieved by means of a novel filter embedded in this architecture. This gives rise to both integrative and antagonistic effects which are in agreement with those observed in psychophysical experiments with humans, providing a functional explanation for effects of motion repulsion.

  18. Robust motion estimation on a low-power multi-core DSP

    NASA Astrophysics Data System (ADS)

    Igual, Francisco D.; Botella, Guillermo; García, Carlos; Prieto, Manuel; Tirado, Francisco

    2013-12-01

    This paper addresses the efficient implementation of a robust gradient-based optical flow model in a low-power platform based on a multi-core digital signal processor (DSP). The aim of this work was to carry out a feasibility study on the use of these devices in autonomous systems such as robot navigation, biomedical assistance, or tracking, with not only power restrictions but also real-time requirements. We consider the C6678 DSP from Texas Instruments (Dallas, TX, USA) as the target platform of our implementation. The interest of this research is particularly relevant in optical flow scope because this system can be considered as an alternative solution for mid-range video resolutions when a combination of in-processor parallelism with optimizations such as efficient memory-hierarchy exploitation and multi-processor parallelization are applied.

  19. Adaptive update using visual models for lifting-based motion-compensated temporal filtering

    NASA Astrophysics Data System (ADS)

    Li, Song; Xiong, H. K.; Wu, Feng; Chen, Hong

    2005-03-01

    Motion compensated temporal filtering is a useful framework for fully scalable video compression schemes. However, when supposed motion models cannot represent a real motion perfectly, both the temporal high and the temporal low frequency sub-bands may contain artificial edges, which possibly lead to a decreased coding efficiency, and ghost artifacts appear in the reconstructed video sequence at lower bit rates or in case of temporal scaling. We propose a new technique that is based on utilizing visual models to mitigate ghosting artifacts in the temporal low frequency sub-bands. Specifically, we propose content adaptive update schemes where visual models are used to determine image dependent upper bounds on information to be updated. Experimental results show that the proposed algorithm can significantly improve subjective visual quality of the low-pass temporal frames and at the same time, coding performance can catch or exceed the classical update steps.

  20. Effects of pre-exposures to a rotating optokinetic drum on adaptation to motion sickness

    NASA Technical Reports Server (NTRS)

    Hu, Senqi; Stern, Robert M.; Koch, Kenneth L.

    1991-01-01

    The effects of two different preexposure procedures on the adaptation to motion-sickness-causing rotation motion in a rotating optokinetic drum were investigated in three groups of human subjects. The first (control) group had a standard 16-min exposure in a drum rotating at 60 deg/sec, with no preexposure. The second (incremental exposure) group had two separated 4-min preexposure periods, at 15 deg/min and 30 deg/min, immediately prior to the standard 16-min exposure. The third (abrupt exposure) group had the same preexposure but with the second rotation at 60 deg/min, followed by the standard exposure. It was found that subjects in the incremental exposure group had significantly fewer motion sickness symptoms during the standard rotation period than did the subjects in the other two groups.

  1. Flying triangulation - A motion-robust optical 3D sensor for the real-time shape acquisition of complex objects

    NASA Astrophysics Data System (ADS)

    Willomitzer, Florian; Ettl, Svenja; Arold, Oliver; Häusler, Gerd

    2013-05-01

    The three-dimensional shape acquisition of objects has become more and more important in the last years. Up to now, there are several well-established methods which already yield impressive results. However, even under quite common conditions like object movement or a complex shaping, most methods become unsatisfying. Thus, the 3D shape acquisition is still a difficult and non-trivial task. We present our measurement principle "Flying Triangulation" which enables a motion-robust 3D acquisition of complex-shaped object surfaces by a freely movable handheld sensor. Since "Flying Triangulation" is scalable, a whole sensor-zoo for different object sizes is presented. Concluding, an overview of current and future fields of investigation is given.

  2. Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression.

    PubMed

    Riaz, Nadeem; Shanker, Piyush; Wiersma, Rodney; Gudmundsson, Olafur; Mao, Weihua; Widrow, Bernard; Xing, Lei

    2009-10-07

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

  3. Robust motion-free and error-correcting method of estimating the focal length of a lens.

    PubMed

    Reza, Syed Azer; Anjum, Arslan

    2017-01-10

    This paper presents a motion-free technique to characterize the focal length of any spherical convex or concave lens. The measurement test-bench uses a Gaussian laser beam, an electronically controlled variable focus lens (ECVFL), a digital micro-mirror device (DMD), and a standard photo-detector (PD). The method requires measuring beam spot sizes for different focal length settings of the ECVFL and using the measurement data to obtain a focal length estimate through an iterative least-squares-based curve-fitting algorithm. The method is also shown to overcome potential measurement errors that arise due to inaccurate placement of optical components on the test-bench as well as unknown principal plane locations of asymmetric lens samples such as plano-convex lenses. Contrary to the commercially deployed and other proposed methods of focal length characterization, this method does not involve any bulk mechanical motion of optical elements. This approach eliminates measurement errors due to gradual mechanical wear and tear and improves measurement repeatability by minimizing mechanical hysteresis. The compact and fully automated method delivers fast, repeatable, and reliable measurements, which we believe makes it ideal for deployment in industrial lens production units and characterizing lenses used in sensitive imaging systems and various other optical experiments and systems. Measured focal lengths are within the 1% manufacturer-provided tolerance values showing excellent agreement between theory and experiments. We also demonstrate measurement robustness by rectifying discrepancies between known and actual separation distances on the measurement test bench.

  4. Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

    PubMed Central

    Ye-Lin, Yiyao; Alberola-Rubio, José; Perales, Alfredo

    2014-01-01

    Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. PMID:24523828

  5. Heart Motion Prediction Based on Adaptive Estimation Algorithms for Robotic Assisted Beating Heart Surgery

    PubMed Central

    Tuna, E. Erdem; Franke, Timothy J.; Bebek, Özkan; Shiose, Akira; Fukamachi, Kiyotaka; Çavuşoğlu, M. Cenk

    2013-01-01

    Robotic assisted beating heart surgery aims to allow surgeons to operate on a beating heart without stabilizers as if the heart is stationary. The robot actively cancels heart motion by closely following a point of interest (POI) on the heart surface—a process called Active Relative Motion Canceling (ARMC). Due to the high bandwidth of the POI motion, it is necessary to supply the controller with an estimate of the immediate future of the POI motion over a prediction horizon in order to achieve sufficient tracking accuracy. In this paper, two least-square based prediction algorithms, using an adaptive filter to generate future position estimates, are implemented and studied. The first method assumes a linear system relation between the consecutive samples in the prediction horizon. On the contrary, the second method performs this parametrization independently for each point over the whole the horizon. The effects of predictor parameters and variations in heart rate on tracking performance are studied with constant and varying heart rate data. The predictors are evaluated using a 3 degrees of freedom test-bed and prerecorded in-vivo motion data. Then, the one-step prediction and tracking performances of the presented approaches are compared with an Extended Kalman Filter predictor. Finally, the essential features of the proposed prediction algorithms are summarized. PMID:23976889

  6. A multi-layer robust adaptive fault tolerant control system for high performance aircraft

    NASA Astrophysics Data System (ADS)

    Huo, Ying

    Modern high-performance aircraft demand advanced fault-tolerant flight control strategies. Not only the control effector failures, but the aerodynamic type failures like wing-body damages often result in substantially deteriorate performance because of low available redundancy. As a result the remaining control actuators may yield substantially lower maneuvering capabilities which do not authorize the accomplishment of the air-craft's original specified mission. The problem is to solve the control reconfiguration on available control redundancies when the mission modification is urged to save the aircraft. The proposed robust adaptive fault-tolerant control (RAFTC) system consists of a multi-layer reconfigurable flight controller architecture. It contains three layers accounting for different types and levels of failures including sensor, actuator, and fuselage damages. In case of the nominal operation with possible minor failure(s) a standard adaptive controller stands to achieve the control allocation. This is referred to as the first layer, the controller layer. The performance adjustment is accounted for in the second layer, the reference layer, whose role is to adjust the reference model in the controller design with a degraded transit performance. The upmost mission adjust is in the third layer, the mission layer, when the original mission is not feasible with greatly restricted control capabilities. The modified mission is achieved through the optimization of the command signal which guarantees the boundedness of the closed-loop signals. The main distinguishing feature of this layer is the the mission decision property based on the current available resources. The contribution of the research is the multi-layer fault-tolerant architecture that can address the complete failure scenarios and their accommodations in realities. Moreover, the emphasis is on the mission design capabilities which may guarantee the stability of the aircraft with restricted post

  7. A robust impact assessment that informs actionable climate change adaptation: future sunburn browning risk in apple

    NASA Astrophysics Data System (ADS)

    Webb, Leanne; Darbyshire, Rebecca; Erwin, Tim; Goodwin, Ian

    2016-11-01

    Climate change impact assessments are predominantly undertaken for the purpose of informing future adaptation decisions. Often, the complexity of the methodology hinders the actionable outcomes. The approach used here illustrates the importance of considering uncertainty in future climate projections, at the same time providing robust and simple to interpret information for decision-makers. By quantifying current and future exposure of Royal Gala apple to damaging temperature extremes across ten important pome fruit-growing locations in Australia, differences in impact to ripening fruit are highlighted, with, by the end of the twenty-first century, some locations maintaining no sunburn browning risk, while others potentially experiencing the risk for the majority of the January ripening period. Installation of over-tree netting can reduce the impact of sunburn browning. The benefits from employing this management option varied across the ten study locations. The two approaches explored to assist decision-makers assess this information (a) using sunburn browning risk analogues and (b) through identifying hypothetical sunburn browning risk thresholds, resulted in varying recommendations for introducing over-tree netting. These recommendations were location and future time period dependent with some sites showing no benefit for sunburn protection from nets even by the end of the twenty-first century and others already deriving benefits from employing this adaptation option. Potential best and worst cases of sunburn browning risk and its potential reduction through introduction of over-tree nets were explored. The range of results presented highlights the importance of addressing uncertainty in climate projections that result from different global climate models and possible future emission pathways.

  8. Adaptive tuning of a 2DOF controller for robust cell manipulation using IPMC actuators

    NASA Astrophysics Data System (ADS)

    McDaid, A. J.; Aw, K. C.; Haemmerle, E.; Shahinpoor, M.; Xie, S. Q.

    2011-12-01

    Rapid advancement in medicine and bioscience is causing demand for faster, more accurate and dexterous as well as safer and more reliable micro-manipulators capable of handling biological cells. Current micro-manipulation techniques commonly damage cell walls and membranes due to their stiffness and rigidity. Ionic polymer-metal composite (IPMC) actuators have inherent compliance and with their ability to operate well in fluid and cellular environments they present a unique solution for safe cell manipulation. The reason for the downfall of IPMCs is that their complex behaviour makes them hard to control precisely in unknown environments and in the presence of sizeable external disturbances. This paper presents a novel scheme for adaptively tuning IPMC actuators for precise and robust micro-manipulation of biological cells. A two-degree-of-freedom (2DOF) controller is developed to allow optimal performance for both disturbance rejection (DR) and set point (SP) tracking. These criteria are optimized using a proposed IFT algorithm which adaptively updates the controller parameters, with no model or prior knowledge of the operating conditions, to achieve a compliant manipulation system which can precisely track targets in the presence of large external disturbances, as will be encountered in real biological environments. Experiments are presented showing the performance optimization of an IPMC actuator in the presence of external mechanical disturbances as well as the optimization of the SP tracking. The IFT algorithm successfully tunes the DR and SP to an 85% and 69% improvement, respectively. Results are also presented for a one-degree-of-freedom (1DOF) controller tuned first for DR and then for SP, for a comparison with the 2DOF controller. Validation has been undertaken to verify that the 2DOF controller does indeed outperform both 1DOF controllers over a variety of operating conditions.

  9. Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores.

    PubMed

    Zhang, Jiong; Dashtbozorg, Behdad; Bekkers, Erik; Pluim, Josien P W; Duits, Remco; Ter Haar Romeny, Bart M

    2016-12-01

    This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations [Formula: see text]. By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain [Formula: see text], vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a left-invariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the left-invariant Hessian matrix (computed with the LID). After multi-scale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-of-the-art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.

  10. Robustness and management adaptability in tropical rangelands: a viability-based assessment under the non-equilibrium paradigm.

    PubMed

    Accatino, F; Sabatier, R; De Michele, C; Ward, D; Wiegand, K; Meyer, K M

    2014-08-01

    Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.

  11. Robust adaptive control for a class of uncertain non-affine nonlinear systems using affine-type neural networks

    NASA Astrophysics Data System (ADS)

    Zhao, Shitie; Gao, Xianwen

    2016-08-01

    A robust adaptive control is proposed for a class of single-input single-output non-affine nonlinear systems. In order to approximate the unknown nonlinear function, a novel affine-type neural network is used, and then to compensate the approximation error and external disturbance a robust control term is employed. By Lyapunov stability analysis for the closed-loop system, it is proved that tracking errors asymptotically converge to zero. Moreover, an observer is designed to estimate the system states because all the states may not be available for measurements. Furthermore, the adaptation laws of neural networks and the robust controller are given out based on the Lyapunov stability theory. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method.

  12. Robust dynamic myocardial perfusion CT deconvolution using adaptive-weighted tensor total variation regularization

    NASA Astrophysics Data System (ADS)

    Gong, Changfei; Zeng, Dong; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

    2016-03-01

    Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for diagnosis and risk stratification of coronary artery disease by assessing the myocardial perfusion hemodynamic maps (MPHM). Meanwhile, the repeated scanning of the same region results in a relatively large radiation dose to patients potentially. In this work, we present a robust MPCT deconvolution algorithm with adaptive-weighted tensor total variation regularization to estimate residue function accurately under the low-dose context, which is termed `MPD-AwTTV'. More specifically, the AwTTV regularization takes into account the anisotropic edge property of the MPCT images compared with the conventional total variation (TV) regularization, which can mitigate the drawbacks of TV regularization. Subsequently, an effective iterative algorithm was adopted to minimize the associative objective function. Experimental results on a modified XCAT phantom demonstrated that the present MPD-AwTTV algorithm outperforms and is superior to other existing deconvolution algorithms in terms of noise-induced artifacts suppression, edge details preservation and accurate MPHM estimation.

  13. Improving Robustness of Deep Neural Network Acoustic Models via Speech Separation and Joint Adaptive Training

    PubMed Central

    Narayanan, Arun; Wang, DeLiang

    2015-01-01

    Although deep neural network (DNN) acoustic models are known to be inherently noise robust, especially with matched training and testing data, the use of speech separation as a frontend and for deriving alternative feature representations has been shown to improve performance in challenging environments. We first present a supervised speech separation system that significantly improves automatic speech recognition (ASR) performance in realistic noise conditions. The system performs separation via ratio time-frequency masking; the ideal ratio mask (IRM) is estimated using DNNs. We then propose a framework that unifies separation and acoustic modeling via joint adaptive training. Since the modules for acoustic modeling and speech separation are implemented using DNNs, unification is done by introducing additional hidden layers with fixed weights and appropriate network architecture. On the CHiME-2 medium-large vocabulary ASR task, and with log mel spectral features as input to the acoustic model, an independently trained ratio masking frontend improves word error rates by 10.9% (relative) compared to the noisy baseline. In comparison, the jointly trained system improves performance by 14.4%. We also experiment with alternative feature representations to augment the standard log mel features, like the noise and speech estimates obtained from the separation module, and the standard feature set used for IRM estimation. Our best system obtains a word error rate of 15.4% (absolute), an improvement of 4.6 percentage points over the next best result on this corpus. PMID:26973851

  14. Region of interest based robust watermarking scheme for adaptation in small displays

    NASA Astrophysics Data System (ADS)

    Vivekanandhan, Sapthagirivasan; K. B., Kishore Mohan; Vemula, Krishna Manohar

    2010-02-01

    Now-a-days Multimedia data can be easily replicated and the copyright is not legally protected. Cryptography does not allow the use of digital data in its original form and once the data is decrypted, it is no longer protected. Here we have proposed a new double protected digital image watermarking algorithm, which can embed the watermark image blocks into the adjacent regions of the host image itself based on their blocks similarity coefficient which is robust to various noise effects like Poisson noise, Gaussian noise, Random noise and thereby provide double security from various noises and hackers. As instrumentation application requires a much accurate data, the watermark image which is to be extracted back from the watermarked image must be immune to various noise effects. Our results provide better extracted image compared to the present/existing techniques and in addition we have done resizing the same for various displays. Adaptive resizing for various size displays is being experimented wherein we crop the required information in a frame, zoom it for a large display or resize for a small display using a threshold value and in either cases background is not given much importance but it is only the fore-sight object which gains importance which will surely be helpful in performing surgeries.

  15. Linear matrix inequality-based nonlinear adaptive robust control with application to unmanned aircraft systems

    NASA Astrophysics Data System (ADS)

    Kun, David William

    Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external

  16. Motion-adapted catheter navigation with real-time instantiation and improved visualisation.

    PubMed

    Lee, Su-Lin; Kwok, Ka-Wai; Wang, Lichao; Riga, Celia; Bicknell, Colin; Cheshire, Nicholas; Yang, Guang-Zhong

    2013-09-01

    The improvements to catheter manipulation by the use of robot-assisted catheter navigation for endovascular procedures include increased precision, stability of motion and operator comfort. However, navigation through the vasculature under fluoroscopic guidance is still challenging, mostly due to physiological motion and when tortuous vessels are involved. In this paper, we propose a motion-adaptive catheter navigation scheme based on shape modelling to compensate for these dynamic effects, permitting predictive and dynamic navigations. This allows for timed manipulations synchronised with the vascular motion. The technical contribution of the paper includes the following two aspects. Firstly, a dynamic shape modelling and real-time instantiation scheme based on sparse data obtained intra-operatively is proposed for improved visualisation of the 3D vasculature during endovascular intervention. Secondly, a reconstructed frontal view from the catheter tip using the derived dynamic model is used as an interventional aid to user guidance. To demonstrate the practical value of the proposed framework, a simulated aortic branch cannulation procedure is used with detailed user validation to demonstrate the improvement in navigation quality and efficiency.

  17. Motion-direction specificity for adaptation-induced duration compression depends on temporal frequency

    PubMed Central

    Bruno, Aurelio; Ng, Eugenie; Johnston, Alan

    2013-01-01

    Adapting to a 20 Hz oscillating grating reduces the apparent duration of a 10 Hz drifting grating displayed subsequently in the same location as the adaptor. The effect is orientation-independent as it remains once the adaptor is rotated 90° relative to the tests (Johnston, Arnold, & Nishida, 2006). However, it was shown that, for random dots moving at 3°/s, duration compression follows adaptation only when the adaptor and test drift in the same direction, and it disappears when they drift in opposite directions (Curran & Benton, 2012). Here, we explored the relationship between the relative motion direction of adaptor and test and the strength of duration compression for a wider range of speeds and for narrow-band stimuli (temporal frequencies between 3 and 18 Hz). We first measured perceived temporal frequency for the same stimuli after adaptation, and we used these estimates to match the apparent rate of the adapted and unadapted tests in the duration task. We found that, whereas at 3 Hz the effect of adaptation in the opposite direction on duration is marginal, at higher frequencies there is substantial duration compression in the opposite direction. These results indicate that there may be two contributions to apparent duration compression: a cortical contribution sensitive to orientation and motion direction at a wide range of temporal frequencies and a direction-independent subcortical contribution, which is revealed at higher frequencies. However, while direction specificity implies cortical involvement, subcortical orientation dependency and the influence of feedback to subcortical areas should not be ignored. PMID:24167162

  18. Design and experimental evaluation of a robust position controller for an electrohydrostatic actuator using adaptive antiwindup sliding mode scheme.

    PubMed

    Lee, Ji Min; Park, Sung Hwan; Kim, Jong Shik

    2013-01-01

    A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error, this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA system. An optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance. An EHA prototype is developed, carrying out system modeling and parameter identification in designing the position controller. The simply identified linear model serves as the basis for the design of the position controllers, while the robustness of the control systems is compared by experiments. The adaptive anti-windup PID sliding mode controller has been found to have the desired performance and become robust against hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities.

  19. Design and Experimental Evaluation of a Robust Position Controller for an Electrohydrostatic Actuator Using Adaptive Antiwindup Sliding Mode Scheme

    PubMed Central

    Lee, Ji Min; Park, Sung Hwan; Kim, Jong Shik

    2013-01-01

    A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error, this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA system. An optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance. An EHA prototype is developed, carrying out system modeling and parameter identification in designing the position controller. The simply identified linear model serves as the basis for the design of the position controllers, while the robustness of the control systems is compared by experiments. The adaptive anti-windup PID sliding mode controller has been found to have the desired performance and become robust against hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. PMID:23983640

  20. The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation

    PubMed Central

    Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

    2016-01-01

    This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix ‘R’ and the system noise V-C matrix ‘Q’. Then, the global filter uses R to calculate the information allocation factor ‘β’ for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively. PMID:27438835

  1. The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.

    PubMed

    Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

    2016-07-16

    This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'β' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively.

  2. Motion correction of magnetic resonance imaging data by using adaptive moving least squares method.

    PubMed

    Nam, Haewon; Lee, Yeon Ju; Jeong, Byeongseon; Park, Hae-Jeong; Yoon, Jungho

    2015-06-01

    Image artifacts caused by subject motion during the imaging sequence are one of the most common problems in magnetic resonance imaging (MRI) and often degrade the image quality. In this study, we develop a motion correction algorithm for the interleaved-MR acquisition. An advantage of the proposed method is that it does not require either additional equipment or redundant over-sampling. The general framework of this study is similar to that of Rohlfing et al. [1], except for the introduction of the following fundamental modification. The three-dimensional (3-D) scattered data approximation method is used to correct the artifacted data as a post-processing step. In order to obtain a better match to the local structures of the given image, we use the data-adapted moving least squares (MLS) method that can improve the performance of the classical method. Numerical results are provided to demonstrate the advantages of the proposed algorithm.

  3. Interindividual variation in functionally adapted trait sets is established during postnatal growth and predictable based on bone robustness.

    PubMed

    Pandey, Nirnimesh; Bhola, Siddharth; Goldstone, Andrew; Chen, Fred; Chrzanowski, Jessica; Terranova, Carl J; Ghillani, Richard; Jepsen, Karl J

    2009-12-01

    Adults acquire unique sets of morphological and tissue-quality bone traits that are predictable based on robustness and deterministic of strength and fragility. How and when individual trait sets arise during growth has not been established. Longitudinal structural changes of the metacarpal diaphysis were measured for boys and girls from 3 mo to 8 yr of age using hand radiographs obtained from the Bolton-Brush collection. Robustness varied approximately 2-fold among boys and girls, and individual values were established by 2 yr of age, indicating that genetic and environmental factors controlling the relationship between growth in width and growth in length were established early during postnatal growth. Significant negative correlations between robustness and relative cortical area and a significant positive correlation between robustness and a novel measure capturing the efficiency of growth indicated that coordination of the subperiosteal and endocortical surfaces was responsible for this population acquiring a narrow range of trait sets that was predictable based on robustness. Boys and girls with robust diaphyses had proportionally thinner cortices to minimize mass, whereas children with slender diaphyses had proportionally thicker cortices to maximize stiffness. Girls had more slender metacarpals with proportionally thicker cortices compared with boys at all prepubertal ages. Although postnatal growth patterns varied in fundamentally different ways with sex and robustness, the dependence of trait sets on robustness indicated that children sustained variants affecting subperiosteal growth because they shared a common biological factor regulating functional adaptation. Considering the natural variation in acquired trait sets may help identify determinants of fracture risk, because age-related bone loss and gain will affect slender and robust structures differently.

  4. Adaptive Photothermal Emission Analysis Techniques for Robust Thermal Property Measurements of Thermal Barrier Coatings

    NASA Astrophysics Data System (ADS)

    Valdes, Raymond

    The characterization of thermal barrier coating (TBC) systems is increasingly important because they enable gas turbine engines to operate at high temperatures and efficiency. Phase of photothermal emission analysis (PopTea) has been developed to analyze the thermal behavior of the ceramic top-coat of TBCs, as a nondestructive and noncontact method for measuring thermal diffusivity and thermal conductivity. Most TBC allocations are on actively-cooled high temperature turbine blades, which makes it difficult to precisely model heat transfer in the metallic subsystem. This reduces the ability of rote thermal modeling to reflect the actual physical conditions of the system and can lead to higher uncertainty in measured thermal properties. This dissertation investigates fundamental issues underpinning robust thermal property measurements that are adaptive to non-specific, complex, and evolving system characteristics using the PopTea method. A generic and adaptive subsystem PopTea thermal model was developed to account for complex geometry beyond a well-defined coating and substrate system. Without a priori knowledge of the subsystem characteristics, two different measurement techniques were implemented using the subsystem model. In the first technique, the properties of the subsystem were resolved as part of the PopTea parameter estimation algorithm; and, the second technique independently resolved the subsystem properties using a differential "bare" subsystem. The confidence in thermal properties measured using the generic subsystem model is similar to that from a standard PopTea measurement on a "well-defined" TBC system. Non-systematic bias-error on experimental observations in PopTea measurements due to generic thermal model discrepancies was also mitigated using a regression-based sensitivity analysis. The sensitivity analysis reported measurement uncertainty and was developed into a data reduction method to filter out these "erroneous" observations. It was found

  5. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    NASA Astrophysics Data System (ADS)

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E.; Lo, Yeh-Chi

    2016-04-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as  -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  6. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    PubMed Central

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

    2017-01-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as −0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients. PMID:27008349

  7. Adaptation-induced modification of motion selectivity tuning in visual tectal neurons of adult zebrafish

    PubMed Central

    Lucks, Valerie; Kurtz, Rafael; Engelmann, Jacob

    2015-01-01

    In the developing brain, training-induced emergence of direction selectivity and plasticity of orientation tuning appear to be widespread phenomena. These are found in the visual pathway across different classes of vertebrates. Moreover, short-term plasticity of orientation tuning in the adult brain has been demonstrated in several species of mammals. However, it is unclear whether neuronal orientation and direction selectivity in nonmammalian species remains modifiable through short-term plasticity in the fully developed brain. To address this question, we analyzed motion tuning of neurons in the optic tectum of adult zebrafish by calcium imaging. In total, orientation and direction selectivity was enhanced by adaptation, responses of previously orientation-selective neurons were sharpened, and even adaptation-induced emergence of selectivity in previously nonselective neurons was observed in some cases. The different observed effects are mainly based on the relative distance between the previously preferred and the adaptation direction. In those neurons in which a shift of the preferred orientation or direction was induced by adaptation, repulsive shifts (i.e., away from the adapter) were more prevalent than attractive shifts. A further novel finding for visually induced adaptation that emerged from our study was that repulsive and attractive shifts can occur within one brain area, even with uniform stimuli. The type of shift being induced also depends on the difference between the adapting and the initially preferred stimulus direction. Our data indicate that, even within the fully developed optic tectum, short-term plasticity might have an important role in adjusting neuronal tuning functions to current stimulus conditions. PMID:26378206

  8. Towards a robust methodology to assess coastal impacts and adaptation policies for Europe

    NASA Astrophysics Data System (ADS)

    Vousdoukas, Michalis; Voukouvalas, Evangelos; Mentaschi, Lorenzo; Feyen, Luc

    2016-04-01

    The present contribution aims to present preliminary results from efforts towards (i) the development of the integrated risk assessment tool LISCoAsT for Europe (Large scale Integrated Sea-level and Coastal Assessment Tool); (ii) the assessment of coastal risk along the European coastline in view of climate change; and (iii) the development and application of a robust methodology to evaluate adaptation options for the European coastline under climate change scenarios. The overall approach builds on the disaster risk methodology proposed by the IPCC SREX (2012) report, defining risk as the combination of hazard, exposure and vulnerability. Substantial effort has been put in all the individual components of the risk assessment chain, including: (1) the development of dynamic scenarios of catastrophic coastal hazards (e.g., storm surges, sea-level rise) in view of climate change; (2) quantification, mapping and forecasting exposure and vulnerability in coastal areas; (3) carrying out a bottom-up, highly disaggregated assessment of climate impacts on coastal areas in Europe in view of global warming; (4) estimating the costs and assessing the effectiveness of different adaptation options. Projections indicate that, by the end of this century, sea levels in Europe will rise on average between 45 and 70 cm; while projections of coastal hazard showed that for some European regions, the increased storminess can be an additional significant driver of further risk. Projections of increasing extreme storm surge levels (SSL) were even more pronounced under the business-as-usual RCP8.5 concentration pathway, in particular along the Northern Europe coastline. The above are also reflected in the coastal impact projections, which show a significant increase in the expected annual damage (EAD) from coastal flooding. The present EAD for Europe of 800 million €/year is projected to increase up to 2.4 and 3.2 billion €/year by 2040 under RCP 4.5 and 8.5, respectively, and to 11

  9. A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

    NASA Astrophysics Data System (ADS)

    Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu

    This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

  10. Robust-adaptive active vibration control of alloy and flexible matrix composite rotorcraft drivelines via magnetic bearings: Theory and experiment

    NASA Astrophysics Data System (ADS)

    Desmidt, Hans A.

    This thesis explores the use of Active Magnetic Bearing (AMB) technology and newly emerging Flexible Matrix Composite (FMC) materials to advance the state-of-the-art of rotorcraft and other high performance driveline systems. Specifically, two actively controlled tailrotor driveline configurations are explored. The first driveline configuration (Configuration I) consists of a multi-segment alloy driveline connected by Non-Constant-Velocity (NCV) flexible couplings and mounted on non-contact AMB devices. The second configuration (Configuration II) consists of a single piece, rigidly coupled, FMC shaft supported by AMBs. For each driveline configuration, a novel hybrid robust-adaptive vibration control strategy is theoretically developed and experimentally validated based on the specific driveline characteristics and uncertainties. In the case of Configuration I, the control strategy is based on a hybrid design consisting of a PID feedback controller augmented with a slowly adapting, Multi-Harmonic Adaptive Vibration Control (MHAVC) input. Here, the control is developed to ensure robustness with respect to the driveline operating conditions e.g. driveline misalignment, load-torque, shaft speed and shaft imbalance. The analysis shows that the hybrid PID/MHAVC control strategy achieves multi-harmonic suppression of the imbalance, misalignment and load-torque induced driveline vibration over a range of operating conditions. Furthermore, the control law developed for Configuration II is based on a hybrid robust Hinfinity feedback/Synchronous Adaptive Vibration Control (SAVC) strategy. Here, the effects of temperature dependent FMC material properties, rotating-frame damping and shaft imbalance are considered in the control design. The analysis shows that the hybrid Hinfinity/SAVC control strategy guarantees stability, convergence and imbalance vibration suppression under the conditions of bounded temperature deviations and unknown imbalance. Finally, the robustness and

  11. Finite time-Lyapunov based approach for robust adaptive control of wind-induced oscillations in power transmission lines

    NASA Astrophysics Data System (ADS)

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2016-06-01

    Large amplitude oscillation of the power transmission lines, which is also known as galloping phenomenon, has hazardous consequences such as short circuiting and failure of transmission line. In this article, to suppress the undesirable vibrations of the transmission lines, first the governing equations of transmission line are derived via mode summation technique. Then, due to the occurrence of large amplitude vibrations, nonlinear quadratic and cubic terms are included in the derived linear equations. To suppress the vibrations, arbitrary number of the piezoelectric actuators is assumed to exert the actuation forces. Afterwards, a Lyapunov based approach is proposed for the robust adaptive suppression of the undesirable vibrations in the finite time. To compensate the supposed parametric uncertainties with unknown bands, proper adaption laws are introduced. To avoid the vibration devastating consequences as quickly as possible, appropriate control laws are designed. The vibration suppression in the finite time with supposed adaption and control laws is mathematically proved via Lyapunov finite time stability theory. Finally, to illustrate and validate the efficiency and robustness of the proposed finite time control scheme, a parametric case study with three piezoelectric actuators is performed. It is observed that the proposed active control strategy is more efficient and robust than the passive control methods.

  12. Robust image transmission using a new joint source channel coding algorithm and dual adaptive OFDM

    NASA Astrophysics Data System (ADS)

    Farshchian, Masoud; Cho, Sungdae; Pearlman, William A.

    2004-01-01

    In this paper we consider the problem of robust image coding and packetization for the purpose of communications over slow fading frequency selective channels and channels with a shaped spectrum like those of digital subscribe lines (DSL). Towards this end, a novel and analytically based joint source channel coding (JSCC) algorithm to assign unequal error protection is presented. Under a block budget constraint, the image bitstream is de-multiplexed into two classes with different error responses. The algorithm assigns unequal error protection (UEP) in a way to minimize the expected mean square error (MSE) at the receiver while minimizing the probability of catastrophic failure. In order to minimize the expected mean square error at the receiver, the algorithm assigns unequal protection to the value bit class (VBC) stream. In order to minimizes the probability of catastrophic error which is a characteristic of progressive image coders, the algorithm assigns more protection to the location bit class (LBC) stream than the VBC stream. Besides having the advantage of being analytical and also numerically solvable, the algorithm is based on a new formula developed to estimate the distortion rate (D-R) curve for the VBC portion of SPIHT. The major advantage of our technique is that the worst case instantaneous minimum peak signal to noise ratio (PSNR) does not differ greatly from the averge MSE while this is not the case for the optimal single stream (UEP) system. Although both average PSNR of our method and the optimal single stream UEP are about the same, our scheme does not suffer erratic behavior because we have made the probability of catastrophic error arbitarily small. The coded image is sent via orthogonal frequency division multiplexing (OFDM) which is a known and increasing popular modulation scheme to combat ISI (Inter Symbol Interference) and impulsive noise. Using dual adaptive energy OFDM, we use the minimum energy necessary to send each bit stream at a

  13. Motion.

    ERIC Educational Resources Information Center

    Brand, Judith, Ed.

    2002-01-01

    This issue of Exploratorium Magazine focuses on the topic of motion. Contents include: (1) "First Word" (Zach Tobias); (2) "Cosmic Collisions" (Robert Irion); (3) "The Mobile Cell" (Karen E. Kalumuck); (4) "The Paths of Paths" (Steven Vogel); (5) "Fragments" (Pearl Tesler); (6) "Moving Pictures" (Amy Snyder); (7) "Plants on the Go" (Katharine…

  14. Motion.

    ERIC Educational Resources Information Center

    Gerhart, James B.; Nussbaum, Rudi H.

    This monograph was written for the Conference on the New Instructional Materials in Physics held at the University of Washington in summer, 1965. It is intended for use in an introductory course in college physics. It consists of an extensive qualitative discussion of motion followed by a detailed development of the quantitative methods needed to…

  15. Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter

    PubMed Central

    2014-01-01

    Background The calculation of arterial oxygen saturation (SpO2) relies heavily on the amplitude information of the high-quality photoplethysmographic (PPG) signals, which could be contaminated by motion artifacts (MA) during monitoring. Methods A new method combining temporally constrained independent component analysis (cICA) and adaptive filters is presented here to extract the clean PPG signals from the MA corrupted PPG signals with the amplitude information reserved. The underlying PPG signal could be extracted from the MA contaminated PPG signals automatically by using cICA algorithm. Then the amplitude information of the PPG signals could be recovered by using adaptive filters. Results Compared with conventional ICA algorithms, the proposed approach is permutation and scale ambiguity-free. Numerical examples with both synthetic datasets and real-world MA corrupted PPG signals demonstrate that the proposed method could remove the MA from MA contaminated PPG signals more effectively than the two existing FFT-LMS and moving average filter (MAF) methods. Conclusions This paper presents a new method which combines the cICA algorithm and adaptive filter to extract the underlying PPG signals from the MA contaminated PPG signals with the amplitude information reserved. The new method could be used in the situations where one wants to extract the interested source automatically from the mixed observed signals with the amplitude information reserved. The results of study demonstrated the efficacy of this proposed method. PMID:24761769

  16. Robust Matching Cost Function for Stereo Correspondence Using Matching by Tone Mapping and Adaptive Orthogonal Integral Image.

    PubMed

    Dinh, Vinh Quang; Nguyen, Vinh Dinh; Jeon, Jae Wook

    2015-12-01

    Real-world stereo images are inevitably affected by radiometric differences, including variations in exposure, vignetting, lighting, and noise. Stereo images with severe radiometric distortion can have large radiometric differences and include locally nonlinear changes. In this paper, we first introduce an adaptive orthogonal integral image, which is an improved version of an orthogonal integral image. After that, based on matching by tone mapping and the adaptive orthogonal integral image, we propose a robust and accurate matching cost function that can tolerate locally nonlinear intensity distortion. By using the adaptive orthogonal integral image, the proposed matching cost function can adaptively construct different support regions of arbitrary shapes and sizes for different pixels in the reference image, so it can operate robustly within object boundaries. Furthermore, we develop techniques to automatically estimate the values of the parameters of our proposed function. We conduct experiments using the proposed matching cost function and compare it with functions employing the census transform, supporting local binary pattern, and adaptive normalized cross correlation, as well as a mutual information-based matching cost function using different stereo data sets. By using the adaptive orthogonal integral image, the proposed matching cost function reduces the error from 21.51% to 15.73% in the Middlebury data set, and from 15.9% to 10.85% in the Kitti data set, as compared with using the orthogonal integral image. The experimental results indicate that the proposed matching cost function is superior to the state-of-the-art matching cost functions under radiometric variation.

  17. Investigation of whether in-room CT-based adaptive intracavitary brachytherapy for uterine cervical cancer is robust against interfractional location variations of organs and/or applicators

    PubMed Central

    Oku, Yoshifumi; Arimura, Hidetaka; Nguyen, Tran Thi Thao; Hiraki, Yoshiyuki; Toyota, Masahiko; Saigo, Yasumasa; Yoshiura, Takashi; Hirata, Hideki

    2016-01-01

    This study investigates whether in-room computed tomography (CT)-based adaptive treatment planning (ATP) is robust against interfractional location variations, namely, interfractional organ motions and/or applicator displacements, in 3D intracavitary brachytherapy (ICBT) for uterine cervical cancer. In ATP, the radiation treatment plans, which have been designed based on planning CT images (and/or MR images) acquired just before the treatments, are adaptively applied for each fraction, taking into account the interfractional location variations. 2D and 3D plans with ATP for 14 patients were simulated for 56 fractions at a prescribed dose of 600 cGy per fraction. The standard deviations (SDs) of location displacements (interfractional location variations) of the target and organs at risk (OARs) with 3D ATP were significantly smaller than those with 2D ATP (P < 0.05). The homogeneity index (HI), conformity index (CI) and tumor control probability (TCP) in 3D ATP were significantly higher for high-risk clinical target volumes than those in 2D ATP. The SDs of the HI, CI, TCP, bladder and rectum D2cc, and the bladder and rectum normal tissue complication probability (NTCP) in 3D ATP were significantly smaller than those in 2D ATP. The results of this study suggest that the interfractional location variations give smaller impacts on the planning evaluation indices in 3D ATP than in 2D ATP. Therefore, the 3D plans with ATP are expected to be robust against interfractional location variations in each treatment fraction. PMID:27296250

  18. The tactile speed aftereffect depends on the speed of adapting motion across the skin rather than other spatiotemporal features.

    PubMed

    McIntyre, Sarah; Seizova-Cajic, Tatjana; Holcombe, Alex O

    2016-03-01

    After prolonged exposure to a surface moving across the skin, this felt movement appears slower, a phenomenon known as the tactile speed aftereffect (tSAE). We asked which feature of the adapting motion drives the tSAE: speed, the spacing between texture elements, or the frequency with which they cross the skin. After adapting to a ridged moving surface with one hand, participants compared the speed of test stimuli on adapted and unadapted hands. We used surfaces with different spatial periods (SPs; 3, 6, 12 mm) that produced adapting motion with different combinations of adapting speed (20, 40, 80 mm/s) and temporal frequency (TF; 3.4, 6.7, 13.4 ridges/s). The primary determinant of tSAE magnitude was speed of the adapting motion, not SP or TF. This suggests that adaptation occurs centrally, after speed has been computed from SP and TF, and/or that it reflects a speed cue independent of those features in the first place (e.g., indentation force). In a second experiment, we investigated the properties of the neural code for speed. Speed tuning predicts that adaptation should be greatest for speeds at or near the adapting speed. However, the tSAE was always stronger when the adapting stimulus was faster (242 mm/s) than the test (30-143 mm/s) compared with when the adapting and test speeds were matched. These results give no indication of speed tuning and instead suggest that adaptation occurs at a level where an intensive code dominates. In an intensive code, the faster the stimulus, the more the neurons fire.

  19. Influence of environmental information in natural scenes and the effects of motion adaptation on a fly motion-sensitive neuron during simulated flight

    PubMed Central

    Ullrich, Thomas W.; Kern, Roland; Egelhaaf, Martin

    2015-01-01

    ABSTRACT Gaining information about the spatial layout of natural scenes is a challenging task that flies need to solve, especially when moving at high velocities. A group of motion sensitive cells in the lobula plate of flies is supposed to represent information about self-motion as well as the environment. Relevant environmental features might be the nearness of structures, influencing retinal velocity during translational self-motion, and the brightness contrast. We recorded the responses of the H1 cell, an individually identifiable lobula plate tangential cell, during stimulation with image sequences, simulating translational motion through natural sceneries with a variety of differing depth structures. A correlation was found between the average nearness of environmental structures within large parts of the cell's receptive field and its response across a variety of scenes, but no correlation was found between the brightness contrast of the stimuli and the cell response. As a consequence of motion adaptation resulting from repeated translation through the environment, the time-dependent response modulations induced by the spatial structure of the environment were increased relatively to the background activity of the cell. These results support the hypothesis that some lobula plate tangential cells do not only serve as sensors of self-motion, but also as a part of a neural system that processes information about the spatial layout of natural scenes. PMID:25505148

  20. Visual motion aftereffects arise from a cascade of two isomorphic adaptation mechanisms

    PubMed Central

    Stocker, Alan A.; Simoncelli, Eero P.

    2013-01-01

    Prolonged exposure to a moving stimulus can substantially alter the perceived velocity (both speed and direction) of subsequently presented stimuli. Here, we show that these changes can be parsimoniously explained with a model that combines the effects of two isomorphic adaptation mechanisms, one nondirectional and one directional. Each produces a pattern of velocity biases that serves as an observable “signature” of the corresponding mechanism. The net effect on perceived velocity is a superposition of these two signatures. By examining human velocity judgments in the context of different adaptor velocities, we are able to separate these two signatures. The model fits the data well, successfully predicts subjects’ behavior in an additional experiment using a nondirectional adaptor, and is in agreement with a variety of previous experimental results. As such, the model provides a unifying explanation for the diversity of motion aftereffects. PMID:19761342

  1. Visually induced self-motion sensation adapts rapidly to left-right reversal of vision

    NASA Technical Reports Server (NTRS)

    Oman, C. M.; Bock, O. L.

    1981-01-01

    Three experiments were conducted using 15 adult volunteers with no overt oculomotor or vestibular disorders. In all experiments, left-right vision reversal was achieved using prism goggles, which permitted a binocular field of vision subtending approximately 45 deg horizontally and 28 deg vertically. In all experiments, circularvection (CV) was tested before and immediately after a period of exposure to reversed vision. After one to three hours of active movement while wearing vision-reversing goggles, 10 of 15 (stationary) human subjects viewing a moving stripe display experienced a self-rotation illusion in the same direction as seen stripe motion, rather than in the opposite (normal) direction, demonstrating that the central neural pathways that process visual self-rotation cues can undergo rapid adaptive modification.

  2. Adaptive robust image registration approach based on adequately sampling polar transform and weighted angular projection function

    NASA Astrophysics Data System (ADS)

    Wei, Zhao; Tao, Feng; Jun, Wang

    2013-10-01

    An efficient, robust, and accurate approach is developed for image registration, which is especially suitable for large-scale change and arbitrary rotation. It is named the adequately sampling polar transform and weighted angular projection function (ASPT-WAPF). The proposed ASPT model overcomes the oversampling problem of conventional log-polar transform. Additionally, the WAPF presented as the feature descriptor is robust to the alteration in the fovea area of an image, and reduces the computational cost of the following registration process. The experimental results show two major advantages of the proposed method. First, it can register images with high accuracy even when the scale factor is up to 10 and the rotation angle is arbitrary. However, the maximum scaling estimated by the state-of-the-art algorithms is 6. Second, our algorithm is more robust to the size of the sampling region while not decreasing the accuracy of the registration.

  3. Anticipatory Control of Motion-to-Force Transitions With the Fingertips Adapts Optimally to Task Difficulty

    PubMed Central

    Cianchetti, Flor A.

    2010-01-01

    Moving our fingertips toward objects to produce well-directed forces immediately upon contact is fundamental to dexterous manipulation. This apparently simple motion-to-force transition in fact involves a time-critical, predictive switch in control strategy. Given that dexterous manipulation must accommodate multiple mechanical conditions, we investigated whether and how this transition adapts to task difficulty. Eight adults (19–39 yr) produced ramps of isometric vertical fingertip force against a rigid surface immediately following a tapping motion. By changing target surface friction and size, we defined an easier (sandpaper, 11 mm diam) versus a more difficult (polished steel, 5 mm diam) task. As in prior work, we assembled fine-wire electromyograms from all seven muscles of the index finger into a seven-dimensional vector defining the full muscle coordination pattern—and quantified its temporal evolution as its alignment with a reference coordination pattern vector for steady-state force production. As predicted by numerical optimizations to neuromuscular delays, our empirical and sigmoidal nonlinear regression analyses show that the coordination pattern transitions begin sooner for the more difficult tasks than for the easier tasks (∼120 ms, P < 0.02, and ∼115 ms, P < 0.015, respectively) and that the coordination pattern transition in alignment is well represented by a sigmoidal trend (R^2 > 0.7 in most cases). Importantly, the force vector following contact had smaller directional error (P < 0.02) for the more difficult task even though the transition in coordination pattern was less stereotypical and uniform than for the easier task. These adaptations of transition strategy to task difficulty are compatible with an optimization to counteract neuromuscular delays and noise to enable this fundamental element of dexterous manipulation. PMID:19889857

  4. Age-related differences in pelvic and trunk motion and gait adaptability at different walking speeds.

    PubMed

    Gimmon, Yoav; Riemer, Raziel; Rashed, Hisham; Shapiro, Amir; Debi, Ronen; Kurz, Ilan; Melzer, Itshak

    2015-10-01

    This study aimed at investigating age-related changes in gait kinematics and in kinematic adaptations over a wide range of walking velocities. Thirty-four older adults and 14 younger adults walked on a treadmill; the treadmill velocity was gradually increased in increments of 0.2miles/hour (mph) (1.1-1.9mph) and then decreased in the same increments. Pelvic, trunk, upper limbs and lower limbs angular total ranges of motion (tROM), stride time, stride length, and step width were measured. The older adults had lower pelvic, trunk tROM and shorter strides and stride time compared with the younger adults. As the treadmill speed was gradually increased, the older adults showed an inability to change the pelvic list angular motions (3.1±1.3° to 3.2±1.4°) between different walking velocities, while the younger adults showed changes (5.1±1.8° to 6.3±1.7°) as a function of the walking velocity. As the walking velocity increased, the older adults increased their stride length (from 57.0±10cm to 90.2±0.1cm) yet stride times remained constant (from 1.17±0.3sec to 1.08±0.1sec), while the younger adults increased stride length and reduced stride times (from 71.4±10cm to 103.0±7.9m and from 1.45±0.2sec to 1.22±0.1sec, respectively). In conclusion, the older adults were unable to make adaptations in pelvic and trunk kinematics between different walking speeds (rigid behavior), while the younger adults showed more flexible behavior. Pelvic and trunk kinematics in different walking speeds can be used as variables in the assessment of gait in older adults.

  5. Anticipatory control of motion-to-force transitions with the fingertips adapts optimally to task difficulty.

    PubMed

    Cianchetti, Flor A; Valero-Cuevas, Francisco J

    2010-01-01

    Moving our fingertips toward objects to produce well-directed forces immediately upon contact is fundamental to dexterous manipulation. This apparently simple motion-to-force transition in fact involves a time-critical, predictive switch in control strategy. Given that dexterous manipulation must accommodate multiple mechanical conditions, we investigated whether and how this transition adapts to task difficulty. Eight adults (19-39 yr) produced ramps of isometric vertical fingertip force against a rigid surface immediately following a tapping motion. By changing target surface friction and size, we defined an easier (sandpaper, 11 mm diam) versus a more difficult (polished steel, 5 mm diam) task. As in prior work, we assembled fine-wire electromyograms from all seven muscles of the index finger into a seven-dimensional vector defining the full muscle coordination pattern-and quantified its temporal evolution as its alignment with a reference coordination pattern vector for steady-state force production. As predicted by numerical optimizations to neuromuscular delays, our empirical and sigmoidal nonlinear regression analyses show that the coordination pattern transitions begin sooner for the more difficult tasks than for the easier tasks ( approximately 120 ms, P < 0.02, and approximately 115 ms, P < 0.015, respectively) and that the coordination pattern transition in alignment is well represented by a sigmoidal trend (R;2 > 0.7 in most cases). Importantly, the force vector following contact had smaller directional error (P < 0.02) for the more difficult task even though the transition in coordination pattern was less stereotypical and uniform than for the easier task. These adaptations of transition strategy to task difficulty are compatible with an optimization to counteract neuromuscular delays and noise to enable this fundamental element of dexterous manipulation.

  6. Experimental Evaluation of a Braille-Reading-Inspired Finger Motion Adaptive Algorithm.

    PubMed

    Ulusoy, Melda; Sipahi, Rifat

    2016-01-01

    Braille reading is a complex process involving intricate finger-motion patterns and finger-rubbing actions across Braille letters for the stimulation of appropriate nerves. Although Braille reading is performed by smoothly moving the finger from left-to-right, research shows that even fluent reading requires right-to-left movements of the finger, known as "reversal". Reversals are crucial as they not only enhance stimulation of nerves for correctly reading the letters, but they also show one to re-read the letters that were missed in the first pass. Moreover, it is known that reversals can be performed as often as in every sentence and can start at any location in a sentence. Here, we report experimental results on the feasibility of an algorithm that can render a machine to automatically adapt to reversal gestures of one's finger. Through Braille-reading-analogous tasks, the algorithm is tested with thirty sighted subjects that volunteered in the study. We find that the finger motion adaptive algorithm (FMAA) is useful in achieving cooperation between human finger and the machine. In the presence of FMAA, subjects' performance metrics associated with the tasks have significantly improved as supported by statistical analysis. In light of these encouraging results, preliminary experiments are carried out with five blind subjects with the aim to put the algorithm to test. Results obtained from carefully designed experiments showed that subjects' Braille reading accuracy in the presence of FMAA was more favorable then when FMAA was turned off. Utilization of FMAA in future generation Braille reading devices thus holds strong promise.

  7. Experimental Evaluation of a Braille-Reading-Inspired Finger Motion Adaptive Algorithm

    PubMed Central

    2016-01-01

    Braille reading is a complex process involving intricate finger-motion patterns and finger-rubbing actions across Braille letters for the stimulation of appropriate nerves. Although Braille reading is performed by smoothly moving the finger from left-to-right, research shows that even fluent reading requires right-to-left movements of the finger, known as “reversal”. Reversals are crucial as they not only enhance stimulation of nerves for correctly reading the letters, but they also show one to re-read the letters that were missed in the first pass. Moreover, it is known that reversals can be performed as often as in every sentence and can start at any location in a sentence. Here, we report experimental results on the feasibility of an algorithm that can render a machine to automatically adapt to reversal gestures of one’s finger. Through Braille-reading-analogous tasks, the algorithm is tested with thirty sighted subjects that volunteered in the study. We find that the finger motion adaptive algorithm (FMAA) is useful in achieving cooperation between human finger and the machine. In the presence of FMAA, subjects’ performance metrics associated with the tasks have significantly improved as supported by statistical analysis. In light of these encouraging results, preliminary experiments are carried out with five blind subjects with the aim to put the algorithm to test. Results obtained from carefully designed experiments showed that subjects’ Braille reading accuracy in the presence of FMAA was more favorable then when FMAA was turned off. Utilization of FMAA in future generation Braille reading devices thus holds strong promise. PMID:26849058

  8. Store-and-feedforward adaptive gaming system for hand-finger motion tracking in telerehabilitation.

    PubMed

    Lockery, Daniel; Peters, James F; Ramanna, Sheela; Shay, Barbara L; Szturm, Tony

    2011-05-01

    This paper presents a telerehabilitation system that encompasses a webcam and store-and-feedforward adaptive gaming system for tracking finger-hand movement of patients during local and remote therapy sessions. Gaming-event signals and webcam images are recorded as part of a gaming session and then forwarded to an online healthcare content management system (CMS) that separates incoming information into individual patient records. The CMS makes it possible for clinicians to log in remotely and review gathered data using online reports that are provided to help with signal and image analysis using various numerical measures and plotting functions. Signals from a 6 degree-of-freedom magnetic motion tracking system provide a basis for video-game sprite control. The MMT provides a path for motion signals between common objects manipulated by a patient and a computer game. During a therapy session, a webcam that captures images of the hand together with a number of performance metrics provides insight into the quality, efficiency, and skill of a patient.

  9. Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network.

    PubMed

    Li, Limin; Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms.

  10. Adaptive search range adjustment scheme for fast motion estimation in AVC/H.264

    NASA Astrophysics Data System (ADS)

    Lee, Sunyoung; Choi, Kiho; Jang, Euee S.

    2011-06-01

    AVC/H.264 supports the use of multiple reference frames (e.g., 5 frames in AVC/H.264) for motion estimation (ME), which demands a huge computational complexity in ME. We propose an adaptive search range adjustment scheme to reduce the computational complexity of ME by reducing the search range of each reference frame--from the (t-1)'th frame to the (t-5)'th frame--for each macroblock. Based on the statistical analysis that the 16×16 mode type is dominantly selected rather than the other block partition mode types, the proposed method reduces the search range of the remaining ME process in the given reference frame according to the motion vector (MV) position of the 16×16 block ME. In the case of the (t-1)'th frame, the MV position of the 8×8 block ME--in addition to that of 16×16 block ME--is also used for the search range reduction to sub-block partition mode types of the 8×8 block. The experimental results show that the proposed method reduces about 50% and 65% of the total encoding time over CIF/SIF and full HD test sequences, respectively, without any noticeable visual degradation, compared to the full search method of the AVC/H.264 encoder.

  11. Motion Adaptive Vertical Handoff in Cellular/WLAN Heterogeneous Wireless Network

    PubMed Central

    Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms. PMID:24741347

  12. Clinical Implementation of an Online Adaptive Plan-of-the-Day Protocol for Nonrigid Motion Management in Locally Advanced Cervical Cancer IMRT

    SciTech Connect

    Heijkoop, Sabrina T. Langerak, Thomas R.; Quint, Sandra; Bondar, Luiza; Mens, Jan Willem M.; Heijmen, Ben J.M.; Hoogeman, Mischa S.

    2014-11-01

    Purpose: To evaluate the clinical implementation of an online adaptive plan-of-the-day protocol for nonrigid target motion management in locally advanced cervical cancer intensity modulated radiation therapy (IMRT). Methods and Materials: Each of the 64 patients had four markers implanted in the vaginal fornix to verify the position of the cervix during treatment. Full and empty bladder computed tomography (CT) scans were acquired prior to treatment to build a bladder volume-dependent cervix-uterus motion model for establishment of the plan library. In the first phase of clinical implementation, the library consisted of one IMRT plan based on a single model-predicted internal target volume (mpITV), covering the target for the whole pretreatment observed bladder volume range, and a 3D conformal radiation therapy (3DCRT) motion-robust backup plan based on the same mpITV. The planning target volume (PTV) combined the ITV and nodal clinical target volume (CTV), expanded with a 1-cm margin. In the second phase, for patients showing >2.5-cm bladder-induced cervix-uterus motion during planning, two IMRT plans were constructed, based on mpITVs for empty-to-half-full and half-full-to-full bladder. In both phases, a daily cone beam CT (CBCT) scan was acquired to first position the patient based on bony anatomy and nodal targets and then select the appropriate plan. Daily post-treatment CBCT was used to verify plan selection. Results: Twenty-four and 40 patients were included in the first and second phase, respectively. In the second phase, 11 patients had two IMRT plans. Overall, an IMRT plan was used in 82.4% of fractions. The main reasons for selecting the motion-robust backup plan were uterus outside the PTV (27.5%) and markers outside their margin (21.3%). In patients with two IMRT plans, the half-full-to-full bladder plan was selected on average in 45% of the first 12 fractions, which was reduced to 35% in the last treatment fractions. Conclusions: The implemented

  13. Robust, integrated computational control of NMR experiments to achieve optimal assignment by ADAPT-NMR.

    PubMed

    Bahrami, Arash; Tonelli, Marco; Sahu, Sarata C; Singarapu, Kiran K; Eghbalnia, Hamid R; Markley, John L

    2012-01-01

    ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches.

  14. Robust Wave-front Correction in a Small Scale Adaptive Optics System Using a Membrane Deformable Mirror

    NASA Astrophysics Data System (ADS)

    Choi, Y.; Park, S.; Baik, S.; Jung, J.; Lee, S.; Yoo, J.

    A small scale laboratory adaptive optics system using a Shack-Hartmann wave-front sensor (WFS) and a membrane deformable mirror (DM) has been built for robust image acquisition. In this study, an adaptive limited control technique is adopted to maintain the long-term correction stability of an adaptive optics system. To prevent the waste of dynamic correction range for correcting small residual wave-front distortions which are inefficient to correct, the built system tries to limit wave-front correction when a similar small difference wave-front pattern is repeatedly generated. Also, the effect of mechanical distortion in an adaptive optics system is studied and a pre-recognition method for the distortion is devised to prevent low-performance system operation. A confirmation process for a balanced work assignment among deformable mirror (DM) actuators is adopted for the pre-recognition. The corrected experimental results obtained by using a built small scale adaptive optics system are described in this paper.

  15. Adaptive Modulation Approach for Robust MPEG-4 AAC Encoded Audio Transmission

    DTIC Science & Technology

    2011-11-01

    to switch to a higher source rate at a given channel bandwidth, which is not possible using single (non-adaptive) modulation, such as 4- QAM for all...case of QPSK/4- QAM , again at high Eb/No (negligible BER), the source rate can be switched to 128kbps (ignoring other transmission overhead) thus...adaptive scheme uses the 4- QAM modulation, whereas the adaptive modulation scheme employs the 4, 8, and 16 QAM for ESC1, ESC2 and ESC3, respectively

  16. Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

    PubMed

    Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

    2014-05-01

    In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

  17. SU-F-BRB-07: A Plan Comparison Tool to Ensure Robustness and Deliverability in Online-Adaptive Radiotherapy

    SciTech Connect

    Hill, P; Labby, Z; Bayliss, R A; Geurts, M; Bayouth, J

    2015-06-15

    Purpose: To develop a plan comparison tool that will ensure robustness and deliverability through analysis of baseline and online-adaptive radiotherapy plans using similarity metrics. Methods: The ViewRay MRIdian treatment planning system allows export of a plan file that contains plan and delivery information. A software tool was developed to read and compare two plans, providing information and metrics to assess their similarity. In addition to performing direct comparisons (e.g. demographics, ROI volumes, number of segments, total beam-on time), the tool computes and presents histograms of derived metrics (e.g. step-and-shoot segment field sizes, segment average leaf gaps). Such metrics were investigated for their ability to predict that an online-adapted plan reasonably similar to a baseline plan where deliverability has already been established. Results: In the realm of online-adaptive planning, comparing ROI volumes offers a sanity check to verify observations found during contouring. Beyond ROI analysis, it has been found that simply editing contours and re-optimizing to adapt treatment can produce a delivery that is substantially different than the baseline plan (e.g. number of segments increased by 31%), with no changes in optimization parameters and only minor changes in anatomy. Currently the tool can quickly identify large omissions or deviations from baseline expectations. As our online-adaptive patient population increases, we will continue to develop and refine quantitative acceptance criteria for adapted plans and relate them historical delivery QA measurements. Conclusion: The plan comparison tool is in clinical use and reports a wide range of comparison metrics, illustrating key differences between two plans. This independent check is accomplished in seconds and can be performed in parallel to other tasks in the online-adaptive workflow. Current use prevents large planning or delivery errors from occurring, and ongoing refinements will lead to

  18. EPICS and VxWorks for real-time motion control of the Altair adaptive optics instrument for Gemini

    NASA Astrophysics Data System (ADS)

    Ebbers, Angelic W.; Dunn, Jennifer

    2002-12-01

    The Instrument Group in the National Research Council of Canada's Herzberg Institute of Astrophysics develops instrumentation for large Astronomical telescopes including Altair (Gemini's ALTitude conjugate Adaptive optics for the InfraRed). This paper discusses how we responded to a need for adaptive intelligence and complex choreography and sequencing of mechanisms in the design of Altair's motion control systems. Our primary goal has been to maximize code reusability without sacrificing performance or flexibility.

  19. Simple robust control laws for robot manipulators. Part 2: Adaptive case

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

    A new class of asymptotically stable adaptive control laws is introduced for application to the robotic manipulator. Unlike most applications of adaptive control theory to robotic manipulators, this analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and utilizes a parameterization based on physical (time-invariant) quantities. This approach is made possible by using energy-like Lyapunov functions which retain the nonlinear character and structure of the dynamics, rather than simple quadratic forms which are ubiquitous to the adaptive control literature, and which have bound the theory tightly to linear systems with unknown parameters. It is a unique feature of these results that the adaptive forms arise by straightforward certainty equivalence adaptation of their nonadaptive counterparts found in the companion to this paper (i.e., by replacing unknown quantities by their estimates) and that this simple approach leads to asymptotically stable closed-loop adaptive systems. Furthermore, it is emphasized that this approach does not require convergence of the parameter estimates (i.e., via persistent excitation), invertibility of the mass matrix estimate, or measurement of the joint accelerations.

  20. Regionally Adaptable Ground Motion Prediction Equation (GMPE) from Empirical Models of Fourier and Duration of Ground Motion

    NASA Astrophysics Data System (ADS)

    Bora, Sanjay; Scherbaum, Frank; Kuehn, Nicolas; Stafford, Peter; Edwards, Benjamin

    2016-04-01

    The current practice of deriving empirical ground motion prediction equations (GMPEs) involves using ground motions recorded at multiple sites. However, in applications like site-specific (e.g., critical facility) hazard ground motions obtained from the GMPEs are need to be adjusted/corrected to a particular site/site-condition under investigation. This study presents a complete framework for developing a response spectral GMPE, within which the issue of adjustment of ground motions is addressed in a manner consistent with the linear system framework. The present approach is a two-step process in which the first step consists of deriving two separate empirical models, one for Fourier amplitude spectra (FAS) and the other for a random vibration theory (RVT) optimized duration (Drvto) of ground motion. In the second step the two models are combined within the RVT framework to obtain full response spectral amplitudes. Additionally, the framework also involves a stochastic model based extrapolation of individual Fourier spectra to extend the useable frequency limit of the empirically derived FAS model. The stochastic model parameters were determined by inverting the Fourier spectral data using an approach similar to the one as described in Edwards and Faeh (2013). Comparison of median predicted response spectra from present approach with those from other regional GMPEs indicates that the present approach can also be used as a stand-alone model. The dataset used for the presented analysis is a subset of the recently compiled database RESORCE-2012 across Europe, the Middle East and the Mediterranean region.

  1. WE-G-BRD-08: Motion Analysis for Rectal Cancer: Implications for Adaptive Radiotherapy On the MR-Linac

    SciTech Connect

    Kleijnen, J; Asselen, B van; Burbach, M; Intven, M; Philippens, M; Reerink, O; Lagendijk, J; Raaymakers, B

    2015-06-15

    Purpose: Purpose of this study is to find the optimal trade-off between adaptation interval and margin reduction and to define the implications of motion for rectal cancer boost radiotherapy on a MR-linac. Methods: Daily MRI scans were acquired of 16 patients, diagnosed with rectal cancer, prior to each radiotherapy fraction in one week (N=76). Each scan session consisted of T2-weighted and three 2D sagittal cine-MRI, at begin (t=0 min), middle (t=9:30 min) and end (t=18:00 min) of scan session, for 1 minute at 2 Hz temporal resolution. Tumor and clinical target volume (CTV) were delineated on each T2-weighted scan and transferred to each cine-MRI. The start frame of the begin scan was used as reference and registered to frames at time-points 15, 30 and 60 seconds, 9:30 and 18:00 minutes and 1, 2, 3 and 4 days later. Per time-point, motion of delineated voxels was evaluated using the deformation vector fields of the registrations and the 95th percentile distance (dist95%) was calculated as measure of motion. Per time-point, the distance that includes 90% of all cases was taken as estimate of required planning target volume (PTV)-margin. Results: Highest motion reduction is observed going from 9:30 minutes to 60 seconds. We observe a reduction in margin estimates from 10.6 to 2.7 mm and 16.1 to 4.6 mm for tumor and CTV, respectively, when adapting every 60 seconds compared to not adapting treatment. A 75% and 71% reduction, respectively. Further reduction in adaptation time-interval yields only marginal motion reduction. For adaptation intervals longer than 18:00 minutes only small motion reductions are observed. Conclusion: The optimal adaptation interval for adaptive rectal cancer (boost) treatments on a MR-linac is 60 seconds. This results in substantial smaller PTV-margin estimates. Adaptation intervals of 18:00 minutes and higher, show little improvement in motion reduction.

  2. A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

    NASA Technical Reports Server (NTRS)

    Wen, John T.; Kreutz, Kenneth; Bayard, David S.

    1988-01-01

    A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

  3. Final Progress Report on Robust and/or Adaptive Filtering by Neural Networks

    DTIC Science & Technology

    2007-11-02

    Transactions on Automatic Control , November 2002 (with Thomas Wanner). Existence and uniqueness of conditional expectations and thus minimum-variance estimates...are guaranteed by the Radon-Nikodym theorem in measure theory . Existence and uniqueness issues of robust estimates with respect to the risk-sensitive...sensitive estimates, i.e., exhibiting an extremely high level of nonuniqueness . • Recurrent Multilayer Perceptrons for Discrete-Time Dynamic System

  4. Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

    PubMed

    Whitacre, James M; Bender, Axel

    2010-06-15

    A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

  5. A Robust and Scalable Software Library for Parallel Adaptive Refinement on Unstructured Meshes

    NASA Technical Reports Server (NTRS)

    Lou, John Z.; Norton, Charles D.; Cwik, Thomas A.

    1999-01-01

    The design and implementation of Pyramid, a software library for performing parallel adaptive mesh refinement (PAMR) on unstructured meshes, is described. This software library can be easily used in a variety of unstructured parallel computational applications, including parallel finite element, parallel finite volume, and parallel visualization applications using triangular or tetrahedral meshes. The library contains a suite of well-designed and efficiently implemented modules that perform operations in a typical PAMR process. Among these are mesh quality control during successive parallel adaptive refinement (typically guided by a local-error estimator), parallel load-balancing, and parallel mesh partitioning using the ParMeTiS partitioner. The Pyramid library is implemented in Fortran 90 with an interface to the Message-Passing Interface (MPI) library, supporting code efficiency, modularity, and portability. An EM waveguide filter application, adaptively refined using the Pyramid library, is illustrated.

  6. HIFI-C: a robust and fast method for determining NMR couplings from adaptive 3D to 2D projections.

    PubMed

    Cornilescu, Gabriel; Bahrami, Arash; Tonelli, Marco; Markley, John L; Eghbalnia, Hamid R

    2007-08-01

    We describe a novel method for the robust, rapid, and reliable determination of J couplings in multi-dimensional NMR coupling data, including small couplings from larger proteins. The method, "High-resolution Iterative Frequency Identification of Couplings" (HIFI-C) is an extension of the adaptive and intelligent data collection approach introduced earlier in HIFI-NMR. HIFI-C collects one or more optimally tilted two-dimensional (2D) planes of a 3D experiment, identifies peaks, and determines couplings with high resolution and precision. The HIFI-C approach, demonstrated here for the 3D quantitative J method, offers vital features that advance the goal of rapid and robust collection of NMR coupling data. (1) Tilted plane residual dipolar couplings (RDC) data are collected adaptively in order to offer an intelligent trade off between data collection time and accuracy. (2) Data from independent planes can provide a statistical measure of reliability for each measured coupling. (3) Fast data collection enables measurements in cases where sample stability is a limiting factor (for example in the presence of an orienting medium required for residual dipolar coupling measurements). (4) For samples that are stable, or in experiments involving relatively stronger couplings, robust data collection enables more reliable determinations of couplings in shorter time, particularly for larger biomolecules. As a proof of principle, we have applied the HIFI-C approach to the 3D quantitative J experiment to determine N-C' RDC values for three proteins ranging from 56 to 159 residues (including a homodimer with 111 residues in each subunit). A number of factors influence the robustness and speed of data collection. These factors include the size of the protein, the experimental set up, and the coupling being measured, among others. To exhibit a lower bound on robustness and the potential for time saving, the measurement of dipolar couplings for the N-C' vector represents a realistic

  7. Robustness of Adaptive Control Algorithms in the Presence of Unmodeled Dynamics,

    DTIC Science & Technology

    1982-09-01

    result, two possible noch - tt (t (3a) anisms of instability are isolated and discussed. It is argued, that the destabilizing effects in the presence L t [J...to Modeling Errors, Ph.D. Thesis, Dept. of Elec. Eng., Univ. of Illinois at 2. A. uer mad A.S. Norse, *Adaptive Control of Urbana -ahampaign, Report

  8. Adaptive Changes In Postural Equilibrium And Motion Sickness Following Repeated Exposures To Virtual Environments

    NASA Technical Reports Server (NTRS)

    Harm, D. L.; Taylor, L. C.

    2006-01-01

    Virtual environments offer unique training opportunities, particularly for training astronauts and preadapting them to the novel sensory conditions of microgravity. Two unresolved human factors issues in virtual reality (VR) systems are: 1) potential "cybersickness", and 2) maladaptive sensorimotor performance following exposure to VR systems. Interestingly, these aftereffects are often quite similar to adaptive sensorimotor responses observed in astronauts during and/or following space flight. Changes in the environmental sensory stimulus conditions and the way we interact with the new stimuli may result in motion sickness, and perceptual, spatial orientation and sensorimotor disturbances. Initial interpretation of novel sensory information may be inappropriate and result in perceptual errors. Active exploratory behavior in a new environment, with resulting feedback and the formation of new associations between sensory inputs and response outputs, promotes appropriate perception and motor control in the new environment. Thus, people adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, unilateral labyrinthectomy and experimentally produced stimulus rearrangements. Adaptation is revealed by aftereffects including perceptual disturbances and sensorimotor control disturbances. The purpose of the current study was to compare disturbances in postural control produced by dome and head-mounted virtual environment displays, and to examine the effects of exposure duration, and repeated exposures to VR systems. Forty-one subjects (21 men, 20 women) participated in the study with an age range of 21-49 years old. One training session was completed in order to achieve stable performance on the posture and VR tasks before participating in the experimental sessions. Three experimental sessions were performed each separated by one day. The subjects performed a navigation and pick and place task in either a dome or head-mounted display

  9. Motion robust magnetic susceptibility and field inhomogeneity estimation using regularized image restoration techniques for fMRI.

    PubMed

    Yeo, Desmond Teck Beng; Fessler, Jeffrey A; Kim, Boklye

    2008-01-01

    In functional MRI, head motion may cause dynamic nonlinear field-inhomogeneity changes, especially with large out-of-plane rotations. This may lead to dynamic geometric distortion or blurring in the time series, which may reduce activation detection accuracy. The use of image registration to estimate dynamic field inhomogeneity maps from a static field map is not sufficient in the presence of such rotations. This paper introduces a retrospective approach to estimate magnetic susceptibility induced field maps of an object in motion, given a static susceptibility induced field map and the associated object motion parameters. It estimates a susceptibility map from a static field map using regularized image restoration techniques, and applies rigid body motion to the former. The dynamic field map is then computed using susceptibility voxel convolution. The method addresses field map changes due to out-of-plane rotations during time series acquisition and does not involve real time field map acquisitions.

  10. Tumor tracking and motion compensation with an adaptive tumor tracking system (ATTS): system description and prototype testing.

    PubMed

    Wilbert, Jürgen; Meyer, Jürgen; Baier, Kurt; Guckenberger, Matthias; Herrmann, Christian; Hess, Robin; Janka, Christian; Ma, Lei; Mersebach, Torben; Richter, Anne; Roth, Michael; Schilling, Klaus; Flentje, Michael

    2008-09-01

    A novel system for real-time tumor tracking and motion compensation with a robotic HexaPOD treatment couch is described. The approach is based on continuous tracking of the tumor motion in portal images without implanted fiducial markers, using the therapeutic megavoltage beam, and tracking of abdominal breathing motion with optical markers. Based on the two independently acquired data sets the table movements for motion compensation are calculated. The principle of operation of the entire prototype system is detailed first. In the second part the performance of the HexaPOD couch was investigated with a robotic four-dimensional-phantom capable of simulating real patient tumor trajectories in three-dimensional space. The performance and limitations of the HexaPOD table and the control system were characterized in terms of its dynamic behavior. The maximum speed and acceleration of the HexaPOD were 8 mm/s and 34.5 mm/s2 in the lateral direction, and 9.5 mm/s and 29.5 mm/s2 in longitudinal and anterior-posterior direction, respectively. Base line drifts of the mean tumor position of realistic lung tumor trajectories could be fully compensated. For continuous tumor tracking and motion compensation a reduction of tumor motion up to 68% of the original amplitude was achieved. In conclusion, this study demonstrated that it is technically feasible to compensate breathing induced tumor motion in the lung with the adaptive tumor tracking system.

  11. A robust face recognition algorithm under varying illumination using adaptive retina modeling

    NASA Astrophysics Data System (ADS)

    Cheong, Yuen Kiat; Yap, Vooi Voon; Nisar, Humaira

    2013-10-01

    Variation in illumination has a drastic effect on the appearance of a face image. This may hinder the automatic face recognition process. This paper presents a novel approach for face recognition under varying lighting conditions. The proposed algorithm uses adaptive retina modeling based illumination normalization. In the proposed approach, retina modeling is employed along with histogram remapping following normal distribution. Retina modeling is an approach that combines two adaptive nonlinear equations and a difference of Gaussians filter. Two databases: extended Yale B database and CMU PIE database are used to verify the proposed algorithm. For face recognition Gabor Kernel Fisher Analysis method is used. Experimental results show that the recognition rate for the face images with different illumination conditions has improved by the proposed approach. Average recognition rate for Extended Yale B database is 99.16%. Whereas, the recognition rate for CMU-PIE database is 99.64%.

  12. Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation.

    PubMed

    Koofigar, Hamid Reza

    2016-01-01

    The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed.

  13. Complex lung motion estimation via adaptive bilateral filtering of the deformation field.

    PubMed

    Papiez, Bartlomiej W; Heinrich, Mattias Paul; Risser, Laurent; Schnabel, Julia A

    2013-01-01

    Estimation of physiologically plausible deformations is critical for several medical applications. For example, lung cancer diagnosis and treatment requires accurate image registration which preserves sliding motion in the pleural cavity, and the rigidity of chest bones. This paper addresses these challenges by introducing a novel approach for regularisation of non-linear transformations derived from a bilateral filter. For this purpose, the classic Gaussian kernel is replaced by a new kernel that smoothes the estimated deformation field with respect to the spatial position, intensity and deformation dissimilarity. The proposed regularisation is a spatially adaptive filter that is able to preserve discontinuity between the lungs and the pleura and reduces any rigid structures deformations in volumes. Moreover, the presented framework is fully automatic and no prior knowledge of the underlying anatomy is required. The performance of our novel regularisation technique is demonstrated on phantom data for a proof of concept as well as 3D inhale and exhale pairs of clinical CT lung volumes. The results of the quantitative evaluation exhibit a significant improvement when compared to the corresponding state-of-the-art method using classic Gaussian smoothing.

  14. What benefit could be derived from on-line adaptive prostate radiotherapy using rectal diameter as a predictor of motion?

    PubMed Central

    Oates, Richard; Gill, Suki; Foroudi, Farshad; Joon, Michael Lim; Schneider, Michal; Bressel, Mathias; Kron, Tomas

    2015-01-01

    This study investigated a relationship between rectum diameter and prostate motion during treatment with a view to reducing planning target volume (PTV) margins for an adaptive protocol. One hundred and ninety-four cone-beam computed tomography (CBCT) images of 10 patients were used to relate rectum diameter on CBCT to prostate intrafraction displacement. A threshold rectum diameter was used to model the impact of an adaptive PTV margin on rectum and bladder dose. Potential dose escalation with a 6 mm uniform margin adaptive protocol was compared to a PTV margin of 10 mm expansion of the clinical target volume (CTV) except 6 mm posterior. Of 194 fractions, 104 had a maximum rectal diameter of ≤3.5 cm. The prostate displaced ≤4 mm in 102 of those fractions. Changing from a standard to an adaptive PTV margin reduced the volume of rectum receiving 25, 50, 60, and 70 Gy by around 12, 9, 10, and 16%, respectively and bladder by approximately 21, 27, 29, and 35%, respectively. An average dose escalation of 4.2 Gy may be possible with an adaptive prostate radiotherapy protocol. In conclusion, a relationship between the prostate motion and the diameter of the rectum on CBCT potentially could enable daily adaptive radiotherapy which can be implemented from the first fraction. PMID:26150683

  15. Adaptive Changes In Postural Equilibrium And Motion Sickness Following Repeated Exposures To Virtual Environments

    NASA Technical Reports Server (NTRS)

    Harm, D. L.; Taylor, L. C.

    2006-01-01

    Virtual environments offer unique training opportunities, particularly for training astronauts and preadapting them to the novel sensory conditions of microgravity. Two unresolved human factors issues in virtual reality (VR) systems are: 1) potential "cybersickness", and 2) maladaptive sensorimotor performance following exposure to VR systems. Interestingly, these aftereffects are often quite similar to adaptive sensorimotor responses observed in astronauts during and/or following space flight. Changes in the environmental sensory stimulus conditions and the way we interact with the new stimuli may result in motion sickness, and perceptual, spatial orientation and sensorimotor disturbances. Initial interpretation of novel sensory information may be inappropriate and result in perceptual errors. Active exploratory behavior in a new environment, with resulting feedback and the formation of new associations between sensory inputs and response outputs, promotes appropriate perception and motor control in the new environment. Thus, people adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, unilateral labyrinthectomy and experimentally produced stimulus rearrangements. Adaptation is revealed by aftereffects including perceptual disturbances and sensorimotor control disturbances. The purpose of the current study was to compare disturbances in postural control produced by dome and head-mounted virtual environment displays, and to examine the effects of exposure duration, and repeated exposures to VR systems. Forty-one subjects (21 men, 20 women) participated in the study with an age range of 21-49 years old. One training session was completed in order to achieve stable performance on the posture and VR tasks before participating in the experimental sessions. Three experimental sessions were performed each separated by one day. The subjects performed a navigation and pick and place task in either a dome or head-mounted display

  16. Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

    PubMed

    Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

    2015-09-01

    To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.

  17. Experimental Investigation on Adaptive Robust Controller Designs Applied to Constrained Manipulators

    PubMed Central

    Nogueira, Samuel L.; Pazelli, Tatiana F. P. A. T.; Siqueira, Adriano A. G.; Terra, Marco H.

    2013-01-01

    In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear ℋ∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose. PMID:23598503

  18. An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles.

    PubMed

    Johansson, A Torbjorn; White, Paul R

    2011-08-01

    This paper proposes an adaptive filter-based method for detection and frequency estimation of whistle calls, such as the calls of birds and marine mammals, which are typically analyzed in the time-frequency domain using a spectrogram. The approach taken here is based on adaptive notch filtering, which is an established technique for frequency tracking. For application to automatic whistle processing, methods for detection and improved frequency tracking through frequency crossings as well as interfering transients are developed and coupled to the frequency tracker. Background noise estimation and compensation is accomplished using order statistics and pre-whitening. Using simulated signals as well as recorded calls of marine mammals and a human whistled speech utterance, it is shown that the proposed method can detect more simultaneous whistles than two competing spectrogram-based methods while not reporting any false alarms on the example datasets. In one example, it extracts complete 1.4 and 1.8 s bottlenose dolphin whistles successfully through frequency crossings. The method performs detection and estimates frequency tracks even at high sweep rates. The algorithm is also shown to be effective on human whistled utterances.

  19. Experimental investigation on adaptive robust controller designs applied to constrained manipulators.

    PubMed

    Nogueira, Samuel L; Pazelli, Tatiana F P A T; Siqueira, Adriano A G; Terra, Marco H

    2013-04-18

    In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear H∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose.

  20. An experimental comparison of proportional-integral, sliding mode, and robust adaptive control for piezo-actuated nanopositioning stages.

    PubMed

    Gu, Guo-Ying; Zhu, Li-Min

    2014-05-01

    This paper presents a comparative study of the proportional-integral (PI) control, sliding mode control (SMC), and robust adaptive control (RAC) for applications to piezo-actuated nanopositioning stages without the inverse hysteresis construction. For a fair comparison, the control parameters of the SMC and RAC are selected on the basis of the well-tuned parameters of the PI controller under same desired trajectories and sampling frequencies. The comparative results show that the RAC improves the tracking performance by 17 and 37 times than the PI controller in terms of the maximum tracking error e(m) and the root mean tracking error e(rms), respectively, while the RAC improves the tracking performance by 7 and 9 times than the SMC in terms of e(m) and e(rms), respectively.

  1. Demonstration of a 17 cm robust carbon fiber deformable mirror for adaptive optics

    SciTech Connect

    Ammons, S M; Hart, M; Coughenour, B; Romeo, R; Martin, R; Rademacher, M

    2011-09-12

    Carbon-fiber reinforced polymer (CFRP) composite is an attractive material for fabrication of optics due to its high stiffness-to-weight ratio, robustness, zero coefficient of thermal expansion (CTE), and the ability to replicate multiple optics from the same mandrel. We use 8 and 17 cm prototype CFRP thin-shell deformable mirrors to show that residual CTE variation may be addressed with mounted actuators for a variety of mirror sizes. We present measurements of surface quality at a range of temperatures characteristic of mountaintop observatories. For the 8 cm piece, the figure error of the Al-coated reflective surface under best actuator correction is {approx}43 nm RMS. The 8 cm mirror has a low surface error internal to the outer ring of actuators (17 nm RMS at 20 C and 33 nm RMS at -5 C). Surface roughness is low (< 3 nm P-V) at a variety of temperatures. We present new figure quality measurements of the larger 17 cm mirror, showing that the intra-actuator figure error internal to the outer ring of actuators (38 nm RMS surface with one-third the actuator density of the 8 cm mirror) does not scale sharply with mirror diameter.

  2. Biologically-inspired robust and adaptive multi-sensor fusion and active control

    NASA Astrophysics Data System (ADS)

    Khosla, Deepak; Dow, Paul A.; Huber, David J.

    2009-04-01

    In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space; (2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them; and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt- zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs.

  3. Sensitive on-chip quantitative real-time PCR performed on an adaptable and robust platform.

    PubMed

    Lund-Olesen, Torsten; Dufva, Martin; Dahl, John Arne; Collas, Philippe; Hansen, Mikkel Fougt

    2008-12-01

    A robust, flexible and efficient system for performing high sensitivity quantitative on-chip real-time PCR for research purposes is presented. The chips used consist of microchannels etched in silicon. The surface in the channels is a thermally grown silicon dioxide and the channel is sealed by a glass lid. The chips contain four PCR chambers but this number can be increased for further multiplexing. Contrary to PCR chips with oil covered open chambers, these channel-like chambers are easily integrated in lab-on-a-chip devices. The temperature is controlled by a Peltier element and the fluorochrome detector system is a commercially available fluorescence stereo microscope equipped with a CCD camera. The setup shows an excellent signal-to-noise ratio of about 400 compared to that of about 150 obtained in a commercial real time PCR machine. A detection limit of a few copies of target molecules is found, which is 100 to 100,000-fold better than other on-chip real-time PCR systems presented in the literature. This demonstrates that the PCR system can be used for critical applications. We also demonstrate that high quality melting curves can be obtained. Such curves are important in lab-on-a-chip systems for identification of amplified product. The usability of the system is validated by performing quantitative on-chip measurements of the amount of specific gene sequences co-immunoprecipitated with various posttranslationally modified histone proteins. Similar results are obtained from on-chip experiments and experiments carried out in a commercial system on larger sample volumes.

  4. The Motions and Morphologies of cloud features on Neptune: continued monitoring with Keck Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Martin, S. C.; de Pater, I.; Gibbard, S. G.; Macintosh, B. A.; Roe, H. G.; Max, C. E.

    2002-09-01

    We present near infrared images taken in the H band (1.4-1.8 microns) using the newly commissioned NIRC2 at the W. M. Keck II telescope as part of a continuing program to monitor the atmospheric dynamics of Neptune using Adaptive Optics. These images with a resolution of .06 arcseconds reveal five infrared bright groups of features. Two groups of features (30-40 deg N and 20-50 deg S) are confined in latitude but span all longitudes creating bands around the planet. Small cloud morphology and relative motions in the wide Southern band (20-50 deg S) identify apparent cloud shearing events and differences in relative speeds within latitude bands. One localized group of features (30 deg N) shows interesting morphologies with marked departures from lines of latitude. Another localized group of South Polar features (70 deg S) show changes in morphology from a teardrop to a train of clouds to an arc of features during three years of observations. The final group of features is spatially diffuse and spans many latitude lines but is tightly confined in longitude. This research was supported in part by the STC Program of the National Science Foundation under Agreement No. AST-9876783, and in part under the auspices of the US Department of Energy at Lawrence Livermore National Laboratory, Univ. of Calif. under contract No. W-7405-Eng-48. Data presented herein were obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W.M. Keck Foundation.

  5. Robust and adaptive techniques for numerical simulation of nonlinear partial differential equations of fractional order

    NASA Astrophysics Data System (ADS)

    Owolabi, Kolade M.

    2017-03-01

    In this paper, some nonlinear space-fractional order reaction-diffusion equations (SFORDE) on a finite but large spatial domain x ∈ [0, L], x = x(x , y , z) and t ∈ [0, T] are considered. Also in this work, the standard reaction-diffusion system with boundary conditions is generalized by replacing the second-order spatial derivatives with Riemann-Liouville space-fractional derivatives of order α, for 0 < α < 2. Fourier spectral method is introduced as a better alternative to existing low order schemes for the integration of fractional in space reaction-diffusion problems in conjunction with an adaptive exponential time differencing method, and solve a range of one-, two- and three-components SFORDE numerically to obtain patterns in one- and two-dimensions with a straight forward extension to three spatial dimensions in a sub-diffusive (0 < α < 1) and super-diffusive (1 < α < 2) scenarios. It is observed that computer simulations of SFORDE give enough evidence that pattern formation in fractional medium at certain parameter value is practically the same as in the standard reaction-diffusion case. With application to models in biology and physics, different spatiotemporal dynamics are observed and displayed.

  6. Robust fundamental frequency estimation in sustained vowels: detailed algorithmic comparisons and information fusion with adaptive Kalman filtering.

    PubMed

    Tsanas, Athanasios; Zañartu, Matías; Little, Max A; Fox, Cynthia; Ramig, Lorraine O; Clifford, Gari D

    2014-05-01

    There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F(0)) of speech signals. This study examines ten F(0) estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F(0) in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F(0) estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F(0) estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F(0) estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F(0) estimation is required.

  7. Robust fundamental frequency estimation in sustained vowels: Detailed algorithmic comparisons and information fusion with adaptive Kalman filtering

    PubMed Central

    Tsanas, Athanasios; Zañartu, Matías; Little, Max A.; Fox, Cynthia; Ramig, Lorraine O.; Clifford, Gari D.

    2014-01-01

    There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F0) of speech signals. This study examines ten F0 estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F0 in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F0 estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F0 estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F0 estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F0 estimation is required. PMID:24815269

  8. Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model.

    PubMed

    Maindal, Helle Terkildsen; Kayser, Lars; Norgaard, Ole; Bo, Anne; Elsworth, Gerald R; Osborne, Richard H

    2016-01-01

    Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.

  9. Adaptive Radiation Therapy for Postprostatectomy Patients Using Real-Time Electromagnetic Target Motion Tracking During External Beam Radiation Therapy

    SciTech Connect

    Zhu, Mingyao; Bharat, Shyam; Michalski, Jeff M.; Gay, Hiram A.; Hou, Wei-Hsien; Parikh, Parag J.

    2013-03-15

    Purpose: Using real-time electromagnetic (EM) transponder tracking data recorded by the Calypso 4D Localization System, we report inter- and intrafractional target motion of the prostate bed, describe a strategy to evaluate treatment adequacy in postprostatectomy patients receiving intensity modulated radiation therapy (IMRT), and propose an adaptive workflow. Methods and Materials: Tracking data recorded by Calypso EM transponders was analyzed for postprostatectomy patients that underwent step-and-shoot IMRT. Rigid target motion parameters during beam delivery were calculated from recorded transponder positions in 16 patients with rigid transponder geometry. The delivered doses to the clinical target volume (CTV) were estimated from the planned dose matrix and the target motion for the first 3, 5, 10, and all fractions. Treatment adequacy was determined by comparing the delivered minimum dose (D{sub min}) with the planned D{sub min} to the CTV. Treatments were considered adequate if the delivered CTV D{sub min} is at least 95% of the planned CTV D{sub min}. Results: Translational target motion was minimal for all 16 patients (mean: 0.02 cm; range: −0.12 cm to 0.07 cm). Rotational motion was patient-specific, and maximum pitch, yaw, and roll were 12.2, 4.1, and 10.5°, respectively. We observed inadequate treatments in 5 patients. In these treatments, we observed greater target rotations along with large distances between the CTV centroid and transponder centroid. The treatment adequacy from the initial 10 fractions successfully predicted the overall adequacy in 4 of 5 inadequate treatments and 10 of 11 adequate treatments. Conclusion: Target rotational motion could cause underdosage to partial volume of the postprostatectomy targets. Our adaptive treatment strategy is applicable to post-prostatectomy patients receiving IMRT to evaluate and improve radiation therapy delivery.

  10. Adapting to a Changing Colorado River: Making Future Water Deliveries More Reliable Through Robust Management Strategies

    NASA Astrophysics Data System (ADS)

    Groves, D.; Bloom, E.; Fischbach, J. R.; Knopman, D.

    2013-12-01

    The U.S. Bureau of Reclamation and water management agencies representing the seven Colorado River Basin States initiated the Colorado River Basin Study in January 2010 to evaluate the resiliency of the Colorado River system over the next 50 years and compare different options for ensuring successful management of the river's resources. RAND was asked to join this Basin Study Team in January 2012 to help develop an analytic approach to identify key vulnerabilities in managing the Colorado River basin over the coming decades and to evaluate different options that could reduce this vulnerability. Using a quantitative approach for planning under uncertainty called Robust Decision Making (RDM), the RAND team assisted the Basin Study by: identifying future vulnerable conditions that could lead to imbalances that could cause the basin to be unable to meet its water delivery objectives; developing a computer-based tool to define 'portfolios' of management options reflecting different strategies for reducing basin imbalances; evaluating these portfolios across thousands of future scenarios to determine how much they could improve basin outcomes; and analyzing the results from the system simulations to identify key tradeoffs among the portfolios. This talk will describe RAND's contribution to the Basin Study, focusing on the methodologies used to to identify vulnerabilities for Upper Basin and Lower Basin water supply reliability and to compare portfolios of options. Several key findings emerged from the study. Future Streamflow and Climate Conditions Are Key: - Vulnerable conditions arise in a majority of scenarios where streamflows are lower than historical averages and where drought conditions persist for eight years or more. - Depending where the shortages occur, problems will arise for delivery obligations for the upper river basin and the lower river basin. The lower river basin is vulnerable to a broader range of plausible future conditions. Additional Investments in

  11. Opposite effects of high- and low-frequency transcranial random noise stimulation probed with visual motion adaptation

    PubMed Central

    Campana, Gianluca; Camilleri, Rebecca; Moret, Beatrice; Ghin, Filippo; Pavan, Andrea

    2016-01-01

    Transcranial random noise stimulation (tRNS) is a recent neuro-modulation technique whose effects at both behavioural and neural level are still debated. Here we employed the well-known phenomenon of motion after-effect (MAE) in order to investigate the effects of high- vs. low-frequency tRNS on motion adaptation and recovery. Participants were asked to estimate the MAE duration following prolonged adaptation (20 s) to a complex moving pattern, while being stimulated with either sham or tRNS across different blocks. Different groups were administered with either high- or low-frequency tRNS. Stimulation sites were either bilateral human MT complex (hMT+) or frontal areas. The results showed that, whereas no effects on MAE duration were induced by stimulating frontal areas, when applied to the bilateral hMT+, high-frequency tRNS caused a significant decrease in MAE duration whereas low-frequency tRNS caused a significant corresponding increase in MAE duration. These findings indicate that high- and low-frequency tRNS have opposed effects on the adaptation-dependent unbalance between neurons tuned to opposite motion directions, and thus on neuronal excitability. PMID:27934947

  12. Accurate respiration measurement using DC-coupled continuous-wave radar sensor for motion-adaptive cancer radiotherapy.

    PubMed

    Gu, Changzhan; Li, Ruijiang; Zhang, Hualiang; Fung, Albert Y C; Torres, Carlos; Jiang, Steve B; Li, Changzhi

    2012-11-01

    Accurate respiration measurement is crucial in motion-adaptive cancer radiotherapy. Conventional methods for respiration measurement are undesirable because they are either invasive to the patient or do not have sufficient accuracy. In addition, measurement of external respiration signal based on conventional approaches requires close patient contact to the physical device which often causes patient discomfort and undesirable motion during radiation dose delivery. In this paper, a dc-coupled continuous-wave radar sensor was presented to provide a noncontact and noninvasive approach for respiration measurement. The radar sensor was designed with dc-coupled adaptive tuning architectures that include RF coarse-tuning and baseband fine-tuning, which allows the radar sensor to precisely measure movement with stationary moment and always work with the maximum dynamic range. The accuracy of respiration measurement with the proposed radar sensor was experimentally evaluated using a physical phantom, human subject, and moving plate in a radiotherapy environment. It was shown that respiration measurement with radar sensor while the radiation beam is on is feasible and the measurement has a submillimeter accuracy when compared with a commercial respiration monitoring system which requires patient contact. The proposed radar sensor provides accurate, noninvasive, and noncontact respiration measurement and therefore has a great potential in motion-adaptive radiotherapy.

  13. Science-society collaboration for robust adaptation planning in water management - The Maipo River Basin in Chile

    NASA Astrophysics Data System (ADS)

    Ocampo Melgar, Anahí; Vicuña, Sebastián; Gironás, Jorge

    2015-04-01

    The Metropolitan Region (M.R.) in Chile is populated by over 6 million people and supplied by the Maipo River and its large number of irrigation channels. Potential environmental alterations caused by global change will extremely affect managers and users of water resources in this semi-arid basin. These hydro-climatological impacts combined with demographic and economic changes will be particularly complex in the city of Santiago, due to the diverse, counterpoised and equally important existing activities and demands. These challenges and complexities request the implementation of flexible plans and actions to adapt policies, institutions, infrastructure and behaviors to a new future with climate change. Due to the inherent uncertainties in the future, a recent research project entitled MAPA (Maipo Adaptation Plan for its initials in Spanish) has formed a collaborative science-society platform to generate insights into the vulnerabilities, challenges and possible mitigation measures that would be necessary to deal with the potential changes in the M.R. This large stakeholder platform conformed by around 30 public, private and civil society organizations, both at the local and regional level and guided by a Robust Decision Making Framework (RDMF) has identified vulnerabilities, future scenarios, performance indicators and mitigation measures for the Maipo River basin. The RDMF used in this project is the XLRM framework (Lempert et al. 2006) that incorporates policy levers (L), exogenous uncertainties (X), measures of performance standards (M) and relationships (R) in an interlinked process. Both stakeholders' expertise and computational capabilities have been used to create hydrological models for the urban, rural and highland sectors supported also by the Water Evaluation and Planning system software (WEAP). The identification of uncertainties and land use transition trends was used to develop future development scenarios to explore possible water management

  14. An Adaptive Neural Mechanism for Acoustic Motion Perception with Varying Sparsity

    PubMed Central

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    Biological motion-sensitive neural circuits are quite adept in perceiving the relative motion of a relevant stimulus. Motion perception is a fundamental ability in neural sensory processing and crucial in target tracking tasks. Tracking a stimulus entails the ability to perceive its motion, i.e., extracting information about its direction and velocity. Here we focus on auditory motion perception of sound stimuli, which is poorly understood as compared to its visual counterpart. In earlier work we have developed a bio-inspired neural learning mechanism for acoustic motion perception. The mechanism extracts directional information via a model of the peripheral auditory system of lizards. The mechanism uses only this directional information obtained via specific motor behaviour to learn the angular velocity of unoccluded sound stimuli in motion. In nature however the stimulus being tracked may be occluded by artefacts in the environment, such as an escaping prey momentarily disappearing behind a cover of trees. This article extends the earlier work by presenting a comparative investigation of auditory motion perception for unoccluded and occluded tonal sound stimuli with a frequency of 2.2 kHz in both simulation and practice. Three instances of each stimulus are employed, differing in their movement velocities–0.5°/time step, 1.0°/time step and 1.5°/time step. To validate the approach in practice, we implement the proposed neural mechanism on a wheeled mobile robot and evaluate its performance in auditory tracking. PMID:28337137

  15. An Adaptive Neural Mechanism for Acoustic Motion Perception with Varying Sparsity.

    PubMed

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    Biological motion-sensitive neural circuits are quite adept in perceiving the relative motion of a relevant stimulus. Motion perception is a fundamental ability in neural sensory processing and crucial in target tracking tasks. Tracking a stimulus entails the ability to perceive its motion, i.e., extracting information about its direction and velocity. Here we focus on auditory motion perception of sound stimuli, which is poorly understood as compared to its visual counterpart. In earlier work we have developed a bio-inspired neural learning mechanism for acoustic motion perception. The mechanism extracts directional information via a model of the peripheral auditory system of lizards. The mechanism uses only this directional information obtained via specific motor behaviour to learn the angular velocity of unoccluded sound stimuli in motion. In nature however the stimulus being tracked may be occluded by artefacts in the environment, such as an escaping prey momentarily disappearing behind a cover of trees. This article extends the earlier work by presenting a comparative investigation of auditory motion perception for unoccluded and occluded tonal sound stimuli with a frequency of 2.2 kHz in both simulation and practice. Three instances of each stimulus are employed, differing in their movement velocities-0.5°/time step, 1.0°/time step and 1.5°/time step. To validate the approach in practice, we implement the proposed neural mechanism on a wheeled mobile robot and evaluate its performance in auditory tracking.

  16. Insect-Inspired Self-Motion Estimation with Dense Flow Fields--An Adaptive Matched Filter Approach.

    PubMed

    Strübbe, Simon; Stürzl, Wolfgang; Egelhaaf, Martin

    2015-01-01

    The control of self-motion is a basic, but complex task for both technical and biological systems. Various algorithms have been proposed that allow the estimation of self-motion from the optic flow on the eyes. We show that two apparently very different approaches to solve this task, one technically and one biologically inspired, can be transformed into each other under certain conditions. One estimator of self-motion is based on a matched filter approach; it has been developed to describe the function of motion sensitive cells in the fly brain. The other estimator, the Koenderink and van Doorn (KvD) algorithm, was derived analytically with a technical background. If the distances to the objects in the environment can be assumed to be known, the two estimators are linear and equivalent, but are expressed in different mathematical forms. However, for most situations it is unrealistic to assume that the distances are known. Therefore, the depth structure of the environment needs to be determined in parallel to the self-motion parameters and leads to a non-linear problem. It is shown that the standard least mean square approach that is used by the KvD algorithm leads to a biased estimator. We derive a modification of this algorithm in order to remove the bias and demonstrate its improved performance by means of numerical simulations. For self-motion estimation it is beneficial to have a spherical visual field, similar to many flying insects. We show that in this case the representation of the depth structure of the environment derived from the optic flow can be simplified. Based on this result, we develop an adaptive matched filter approach for systems with a nearly spherical visual field. Then only eight parameters about the environment have to be memorized and updated during self-motion.

  17. Insect-Inspired Self-Motion Estimation with Dense Flow Fields—An Adaptive Matched Filter Approach

    PubMed Central

    Strübbe, Simon; Stürzl, Wolfgang; Egelhaaf, Martin

    2015-01-01

    The control of self-motion is a basic, but complex task for both technical and biological systems. Various algorithms have been proposed that allow the estimation of self-motion from the optic flow on the eyes. We show that two apparently very different approaches to solve this task, one technically and one biologically inspired, can be transformed into each other under certain conditions. One estimator of self-motion is based on a matched filter approach; it has been developed to describe the function of motion sensitive cells in the fly brain. The other estimator, the Koenderink and van Doorn (KvD) algorithm, was derived analytically with a technical background. If the distances to the objects in the environment can be assumed to be known, the two estimators are linear and equivalent, but are expressed in different mathematical forms. However, for most situations it is unrealistic to assume that the distances are known. Therefore, the depth structure of the environment needs to be determined in parallel to the self-motion parameters and leads to a non-linear problem. It is shown that the standard least mean square approach that is used by the KvD algorithm leads to a biased estimator. We derive a modification of this algorithm in order to remove the bias and demonstrate its improved performance by means of numerical simulations. For self-motion estimation it is beneficial to have a spherical visual field, similar to many flying insects. We show that in this case the representation of the depth structure of the environment derived from the optic flow can be simplified. Based on this result, we develop an adaptive matched filter approach for systems with a nearly spherical visual field. Then only eight parameters about the environment have to be memorized and updated during self-motion. PMID:26308839

  18. SU-E-J-57: First Development of Adapting to Intrafraction Relative Motion Between Prostate and Pelvic Lymph Nodes Targets

    SciTech Connect

    Ge, Y; Colvill, E; O’Brien, R; Keall, P; Booth, J

    2015-06-15

    Purpose Large intrafraction relative motion of multiple targets is common in advanced head and neck, lung, abdominal, gynaecological and urological cancer, jeopardizing the treatment outcomes. The objective of this study is to develop a real-time adaptation strategy, for the first time, to accurately correct for the relative motion of multiple targets by reshaping the treatment field using the multi-leaf collimator (MLC). Methods The principle of tracking the simultaneously treated but differentially moving tumor targets is to determine the new aperture shape that conforms to the shifted targets. Three dimensional volumes representing the individual targets are projected to the beam’s eye view. The leaf openings falling inside each 2D projection will be shifted according to the measured motion of each target to form the new aperture shape. Based on the updated beam shape, new leaf positions will be determined with optimized trade-off between the target underdose and healthy tissue overdose, and considerations of the physical constraints of the MLC. Taking a prostate cancer patient with pelvic lymph node involvement as an example, a preliminary dosimetric study was conducted to demonstrate the potential treatment improvement compared to the state-of- art adaptation technique which shifts the whole beam to track only one target. Results The world-first intrafraction adaptation system capable of reshaping the beam to correct for the relative motion of multiple targets has been developed. The dose in the static nodes and small bowel are closer to the planned distribution and the V45 of small bowel is decreased from 110cc to 75cc, corresponding to a 30% reduction by this technique compared to the state-of-art adaptation technique. Conclusion The developed adaptation system to correct for intrafraction relative motion of multiple targets will guarantee the tumour coverage and thus enable PTV margin reduction to minimize the high target dose to the adjacent organs

  19. Effects of visual reference on adaptation to motion sickness and subjective responses evoked by graded cross-coupled angular accelerations. [vestibular oculogravic effect in human acceleration adaptation

    NASA Technical Reports Server (NTRS)

    Reason, J. T.; Diaz, E.

    1973-01-01

    Three groups of 10 subjects each were exposed to stepwise increments of cross coupled angular accelerations in three visual modes: internal visual reference (IVR), external visual reference (EVR), and vision absent (VA). The subjects in the IVR condition required significantly greater amounts of stimulus exposure to neutralize their illusory subjective reactions. They also suffered a greater loss of well-being and a more marked incidence of motion sickness than did subjects in the EVR and VA conditions. The same 30 subjects were reexposed to the same graded cross coupled stimulation 1 week later. This time, however, all the subjects were tested under only the IVR condition. All three groups showed some positive transfer of adaptation, but only the IVR-IVR combination required significantly fewer head motions to achieve the same level of adaptation on the second occasion. Taken overall, however, the most efficient and least disturbing route to adaptation at the completion of the second test was via the VA-IVR combination.

  20. MagicPlate-512: A 2D silicon detector array for quality assurance of stereotactic motion adaptive radiotherapy

    SciTech Connect

    Petasecca, M. Newall, M. K.; Aldosari, A. H.; Fuduli, I.; Espinoza, A. A.; Porumb, C. S.; Guatelli, S.; Metcalfe, P.; Lerch, M. L. F.; Rosenfeld, A. B.; Booth, J. T.; Colvill, E.; Duncan, M.; Cammarano, D.; Carolan, M.; Oborn, B.; Perevertaylo, V.; Keall, P. J.

    2015-06-15

    Purpose: Spatial and temporal resolutions are two of the most important features for quality assurance instrumentation of motion adaptive radiotherapy modalities. The goal of this work is to characterize the performance of the 2D high spatial resolution monolithic silicon diode array named “MagicPlate-512” for quality assurance of stereotactic body radiation therapy (SBRT) and stereotactic radiosurgery (SRS) combined with a dynamic multileaf collimator (MLC) tracking technique for motion compensation. Methods: MagicPlate-512 is used in combination with the movable platform HexaMotion and a research version of radiofrequency tracking system Calypso driving MLC tracking software. The authors reconstruct 2D dose distributions of small field square beams in three modalities: in static conditions, mimicking the temporal movement pattern of a lung tumor and tracking the moving target while the MLC compensates almost instantaneously for the tumor displacement. Use of Calypso in combination with MagicPlate-512 requires a proper radiofrequency interference shielding. Impact of the shielding on dosimetry has been simulated by GEANT4 and verified experimentally. Temporal and spatial resolutions of the dosimetry system allow also for accurate verification of segments of complex stereotactic radiotherapy plans with identification of the instant and location where a certain dose is delivered. This feature allows for retrospective temporal reconstruction of the delivery process and easy identification of error in the tracking or the multileaf collimator driving systems. A sliding MLC wedge combined with the lung motion pattern has been measured. The ability of the MagicPlate-512 (MP512) in 2D dose mapping in all three modes of operation was benchmarked by EBT3 film. Results: Full width at half maximum and penumbra of the moving and stationary dose profiles measured by EBT3 film and MagicPlate-512 confirm that motion has a significant impact on the dose distribution. Motion

  1. Ultra-Precision Measurement and Control of Angle Motion in Piezo-Based Platforms Using Strain Gauge Sensors and a Robust Composite Controller

    PubMed Central

    Liu, Lei; Bai, Yu-Guang; Zhang, Da-Li; Wu, Zhi-Gang

    2013-01-01

    The measurement and control strategy of a piezo-based platform by using strain gauge sensors (SGS) and a robust composite controller is investigated in this paper. First, the experimental setup is constructed by using a piezo-based platform, SGS sensors, an AD5435 platform and two voltage amplifiers. Then, the measurement strategy to measure the tip/tilt angles accurately in the order of sub-μrad is presented. A comprehensive composite control strategy design to enhance the tracking accuracy with a novel driving principle is also proposed. Finally, an experiment is presented to validate the measurement and control strategy. The experimental results demonstrate that the proposed measurement and control strategy provides accurate angle motion with a root mean square (RMS) error of 0.21 μrad, which is approximately equal to the noise level. PMID:23860316

  2. A model of the effects of authority on consensus formation in adaptive networks: Impact on network topology and robustness

    NASA Astrophysics Data System (ADS)

    Prettejohn, Brenton J.; Berryman, Matthew J.; McDonnell, Mark D.

    2013-02-01

    Opinions of individuals in real social networks are arguably strongly influenced by external determinants, such as the opinions of those perceived to have the highest levels of authority. In order to model this, we have extended an existing model of consensus formation in an adaptive network by the introduction of a parameter representing each agent’s level of ‘authority’, based on their opinion relative to the overall opinion distribution. We found that introducing this model, along with a randomly varying opinion convergence factor, significantly impacts the final state of converged opinions and the number of interactions required to reach that state. We also determined the relationship between initial and final network topologies for this model, and whether the final topology is robust to node removals. Our results indicate firstly that the process of consensus formation with a model of authority consistently transforms the network from an arbitrary initial topology to one with distinct measurements in mean shortest path, clustering coefficient, and degree distribution. Secondly, we found that subsequent to the consensus formation process, the mean shortest path and clustering coefficient are less affected by both random and targeted node disconnection. Speculation on the relevance of these results to real world applications is provided.

  3. Energy Landscape Reveals That the Budding Yeast Cell Cycle Is a Robust and Adaptive Multi-stage Process

    PubMed Central

    Lv, Cheng; Li, Xiaoguang; Li, Fangting; Li, Tiejun

    2015-01-01

    Quantitatively understanding the robustness, adaptivity and efficiency of cell cycle dynamics under the influence of noise is a fundamental but difficult question to answer for most eukaryotic organisms. Using a simplified budding yeast cell cycle model perturbed by intrinsic noise, we systematically explore these issues from an energy landscape point of view by constructing an energy landscape for the considered system based on large deviation theory. Analysis shows that the cell cycle trajectory is sharply confined by the ambient energy barrier, and the landscape along this trajectory exhibits a generally flat shape. We explain the evolution of the system on this flat path by incorporating its non-gradient nature. Furthermore, we illustrate how this global landscape changes in response to external signals, observing a nice transformation of the landscapes as the excitable system approaches a limit cycle system when nutrients are sufficient, as well as the formation of additional energy wells when the DNA replication checkpoint is activated. By taking into account the finite volume effect, we find additional pits along the flat cycle path in the landscape associated with the checkpoint mechanism of the cell cycle. The difference between the landscapes induced by intrinsic and extrinsic noise is also discussed. In our opinion, this meticulous structure of the energy landscape for our simplified model is of general interest to other cell cycle dynamics, and the proposed methods can be applied to study similar biological systems. PMID:25794282

  4. Image copy-move forgery detection based on sped-up robust features descriptor and adaptive minimal-maximal suppression

    NASA Astrophysics Data System (ADS)

    Yang, Bin; Sun, Xingming; Xin, Xiangyang; Hu, Weifeng; Wu, Youxin

    2015-11-01

    Region duplication is a simple and effective operation to create digital image forgeries, where a continuous portion of pixels in an image is copied and pasted to a different location in the same image. Many prior copy-move forgery detection methods suffer from their inability to detect the duplicated region, which is subjected to various geometric transformations. A keypoint-based approach is proposed to detect the copy-move forgery in an image. Our method starts by extracting the keypoints through a fast Hessian detector. Then the adaptive minimal-maximal suppression (AMMS) strategy is developed for distributing the keypoints evenly throughout an image. By using AMMS and a sped-up robust feature descriptor, the proposed method is able to deal with the problem of insufficient keypoints in the almost uniform area. Finally, the geometric transformation performed in cloning is recovered by using the maximum likelihood estimation of the homography. Experimental results show the efficacy of this technique in detecting copy-move forgeries and estimating the geometric transformation parameters. Compared with the state of the art, our approach obtains a higher true positive rate and a lower false positive rate.

  5. Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique.

    PubMed

    Chen, Wen; Chowdhury, Fahmida N; Djuric, Ana; Yeh, Chih-Ping

    2014-09-01

    This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy.

  6. Histograms of Oriented 3D Gradients for Fully Automated Fetal Brain Localization and Robust Motion Correction in 3 T Magnetic Resonance Images

    PubMed Central

    Macnaught, Gillian; Denison, Fiona C.; Reynolds, Rebecca M.; Semple, Scott I.; Boardman, James P.

    2017-01-01

    Fetal brain magnetic resonance imaging (MRI) is a rapidly emerging diagnostic imaging tool. However, automated fetal brain localization is one of the biggest obstacles in expediting and fully automating large-scale fetal MRI processing. We propose a method for automatic localization of fetal brain in 3 T MRI when the images are acquired as a stack of 2D slices that are misaligned due to fetal motion. First, the Histogram of Oriented Gradients (HOG) feature descriptor is extended from 2D to 3D images. Then, a sliding window is used to assign a score to all possible windows in an image, depending on the likelihood of it containing a brain, and the window with the highest score is selected. In our evaluation experiments using a leave-one-out cross-validation strategy, we achieved 96% of complete brain localization using a database of 104 MRI scans at gestational ages between 34 and 38 weeks. We carried out comparisons against template matching and random forest based regression methods and the proposed method showed superior performance. We also showed the application of the proposed method in the optimization of fetal motion correction and how it is essential for the reconstruction process. The method is robust and does not rely on any prior knowledge of fetal brain development. PMID:28251155

  7. Robust Adaptive Control.

    DTIC Science & Technology

    1985-09-19

    C conltrolliN toI e iibit si -, nil t pCi Isil - CI’S!’’. , l0 i5 dh I ’.,I hJ1Cd On1 lk the .f L Sn: IOf it fitted manx e vi~adion an-Isa lI\\ 11.\\Jh M...8217t C\\1CI. LtlI\\ 111iC SI S( C.i’l- %%ill he r ~[ ( considel ed hCi C t0 redukc the coflple\\tat of the (I.% 0 G=k 1 01 1𔃻 7a I deC11114-1 el kie and... sis the oupen-Iu" p interconneionwf mtatrix %%hose element-, are proper rational functions. (To eCt) = H,(%0) i~r). (19) simplif\\ notation Ae %iill

  8. Adaptive momentum-based motion detection approach and its application on handoff in wireless networks.

    PubMed

    Chung, Tein-Yaw; Chen, Yung-Mu; Hsu, Chih-Hung

    2009-01-01

    Positioning and tracking technologies can detect the location and the movement of mobile nodes (MNs), such as cellular phone, vehicular and mobile sensor, to predict potential handoffs. However, most motion detection mechanisms require additional hardware (e.g., GPS and directed antenna), costs (e.g., power consumption and monetary cost) and supply systems (e.g., network fingerprint server). This paper proposes a Momentum of Received Signal Strength (MRSS) based motion detection method and its application on handoff. MRSS uses the exponentially weighted moving average filter with multiple moving average window size to analyze the received radio signal. With MRSS, an MN can predict its motion state and make a handoff trigger at the right time without any assistance from positioning systems. Moreover, a novel motion state dependent MRSS scheme called Dynamic MRSS (DMRSS) algorithm is proposed to adjust the motion detection sensitivity. In our simulation, the MRSS- and DMRSS-based handoff algorithms can reduce the number of unnecessary handoffs up to 44% and save battery power up to 75%.

  9. Adaptive Momentum-Based Motion Detection Approach and Its Application on Handoff in Wireless Networks

    PubMed Central

    Chung, Tein-Yaw; Chen, Yung-Mu; Hsu, Chih-Hung

    2009-01-01

    Positioning and tracking technologies can detect the location and the movement of mobile nodes (MNs), such as cellular phone, vehicular and mobile sensor, to predict potential handoffs. However, most motion detection mechanisms require additional hardware (e.g., GPS and directed antenna), costs (e.g., power consumption and monetary cost) and supply systems (e.g., network fingerprint server). This paper proposes a Momentum of Received Signal Strength (MRSS) based motion detection method and its application on handoff. MRSS uses the exponentially weighted moving average filter with multiple moving average window size to analyze the received radio signal. With MRSS, an MN can predict its motion state and make a handoff trigger at the right time without any assistance from positioning systems. Moreover, a novel motion state dependent MRSS scheme called Dynamic MRSS (DMRSS) algorithm is proposed to adjust the motion detection sensitivity. In our simulation, the MRSS- and DMRSS-based handoff algorithms can reduce the number of unnecessary handoffs up to 44% and save battery power up to 75%. PMID:22346724

  10. TH-A-BRF-12: Assessment of 4D-MRI for Robust Motion and Volume Characterization

    SciTech Connect

    Glide-Hurst, C; Kim, J; Wen, N; Chetty, I; Hu, Y; Mutic, S

    2014-06-15

    Purpose: Precise radiation therapy for abdominal lesions is complicated by respiratory motion and poor soft tissue contrast from 4DCT whereas 4DMRI provides superior tissue discrimination. We evaluated a novel 4D-MRI algorithm for MR-SIM motion management. Methods: Respiratory-triggered, T2-weighted single-shot Turbo Spin Echo 4D-MRI was evaluated for open high-field 1.0T MR-SIM. A programmable platform pulled objects on a trolley ∼2 cm superior-inferior (S-I) for “regular” (sinusoidal, (1-cos{sup 2}), 3-5 second periods) and “irregular” breathing patterns (exaggerated (1-cos{sup 2}) and patient curves), while a respiratory waveform was generated via a pressure sensor device. Coronal 4D-MRIs (2–12;10 phases, TE/TR/α = 35−61/6100 ms/90°, voxel=1×1×4 mm{sup 3}) were acquired for 54 unique phantom cases. Abdominal 4D−MRIs were evaluated for 5 healthy volunteers and 1 liver cancer patient (6–10 phases, TE/TR/α = 30−96/4500−6100 ms/90°, voxel=1×1×5–10 mm{sup 3}) on an IRB-approved protocol. Duty cycle, scan time, and excursion were evaluated between phase acquisitions and compared to coronal cine-MRI (∼1 frame/sec). Maximum intensity projections (MIPs) were analyzed. Results: In phantom, average duty cycle was 42.6 ± 11.4% (range: 23.6–69.1%). Regular, periodic breathing (sinusoidal, (1-cos{sup 2})) yielded higher duty cycles than irregular (48.5% and 35.9%, respectively, p<0.001) and fast periods had higher duty cycles than slow (50.4% for 3s and 39.4% for 5s, p<0.001). ∼4-fold acquisition time increase was measured for 10-phase versus 2-phase. MIP renderings revealed that SI object extent was underestimated a maximum of 4% (3mm) and 8% (6mm) for cine and 2-phase 4D-MRI, respectively, with respect to 10-phases. However, this was waveform dependent. A highly irregular breathing volunteer yielded lowest duty cycle (23%) and longest 10-phase scan time (∼14 minutes), although 6-phase acquisition for a liver cancer patient was

  11. Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles

    NASA Astrophysics Data System (ADS)

    Kobravi, Hamid-Reza; Erfanian, Abbas

    2009-08-01

    A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

  12. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    SciTech Connect

    Pin, Grancois G.

    2004-06-01

    Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives, and modular configuration.

  13. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    SciTech Connect

    Pin, Francois G.

    2003-06-01

    Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives and modular configuration.

  14. Evaluating the need for integrated land use and land cover analysis for robust assessment of climate adaptation and mitigation strategies

    NASA Astrophysics Data System (ADS)

    Di Vittorio, Alan; Mao, Jiafu; Shi, Xiaoying

    2016-04-01

    LULCC scenarios in earth system simulations to provide robust historical and future projections of carbon and climate, especially when incorporating climate feedbacks on human and environmental systems. More accurate LULCC scenarios will also improve impact and resource sustainability analyses in the context of climate adaptation and mitigation strategies. These new scenarios will need to be developed and implemented as an integrated process with interdependent land use and land cover to adequately incorporate human and environmental drivers of LULCC.

  15. Complexity reduction in the H.264/AVC using highly adaptive fast mode decision based on macroblock motion activity

    NASA Astrophysics Data System (ADS)

    Abdellah, Skoudarli; Mokhtar, Nibouche; Amina, Serir

    2015-11-01

    The H.264/AVC video coding standard is used in a wide range of applications from video conferencing to high-definition television according to its high compression efficiency. This efficiency is mainly acquired from the newly allowed prediction schemes including variable block modes. However, these schemes require a high complexity to select the optimal mode. Consequently, complexity reduction in the H.264/AVC encoder has recently become a very challenging task in the video compression domain, especially when implementing the encoder in real-time applications. Fast mode decision algorithms play an important role in reducing the overall complexity of the encoder. In this paper, we propose an adaptive fast intermode algorithm based on motion activity, temporal stationarity, and spatial homogeneity. This algorithm predicts the motion activity of the current macroblock from its neighboring blocks and identifies temporal stationary regions and spatially homogeneous regions using adaptive threshold values based on content video features. Extensive experimental work has been done in high profile, and results show that the proposed source-coding algorithm effectively reduces the computational complexity by 53.18% on average compared with the reference software encoder, while maintaining the high-coding efficiency of H.264/AVC by incurring only 0.097 dB in total peak signal-to-noise ratio and 0.228% increment on the total bit rate.

  16. Spiders in Motion: Demonstrating Adaptation, Structure-Function Relationships, and Trade-Offs in Invertebrates

    ERIC Educational Resources Information Center

    Bowlin, Melissa S.; McLeer, Dorothy F.; Danielson-Francois, Anne M.

    2014-01-01

    Evolutionary history and structural considerations constrain all aspects of animal physiology. Constraints on invertebrate locomotion are especially straightforward for students to observe and understand. In this exercise, students use spiders to investigate the concepts of adaptation, structure-function relationships, and trade-offs. Students…

  17. Visually induced self-motion sensation adapts rapidly to left-right visual reversal

    NASA Technical Reports Server (NTRS)

    Oman, C. M.; Bock, O. L.; Huang, J.-K.

    1980-01-01

    The experimental demonstration of a reversal of the circularvection (CV) phenomenon is reported. After one to three hours of active movement while wearing vision-reversing goggles, 9 of 12 stationary human subjects viewing a moving stripe display experienced a self-rotation illusion in the same direction as the seen stripe motion. In addition, the subjects showed a 17% reduction in vestibulo-ocular reflex slow phase gain over their brief exposure period. It is noted that whether a subject demonstrated reversed CV within the allowed exposure period appeared to be correlated with CV strength produced with a narrow field stimulus.

  18. Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

    NASA Astrophysics Data System (ADS)

    Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

    2016-04-01

    Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing

  19. The motion after-effect reloaded

    PubMed Central

    Mather, George; Pavan, Andrea; Campana, Gianluca; Casco, Clara

    2011-01-01

    The motion after-effect is a robust illusion of visual motion resulting from exposure to a moving pattern. There is a widely accepted explanation of it in terms of changes in the response of cortical direction-selective neurons. Research has distinguished several variants of the effect. Converging recent evidence from different experimental techniques (psychophysics, single-unit recording, brain imaging, transcranial magnetic stimulation, and evoked potentials) reveals that adaptation is not confined to one or even two cortical areas, but involves up to five different sites, reflecting the multiple levels of processing involved in visual motion analysis. A tentative motion processing framework is described, based on motion after-effect research. Recent ideas on the function of adaptation see it as a form of gain control that maximises the efficiency of information transmission. PMID:18951829

  20. Minimal model of a cell connecting amoebic motion and adaptive transport networks.

    PubMed

    Gunji, Yukio-Pegio; Shirakawa, Tomohiro; Niizato, Takayuki; Haruna, Taichi

    2008-08-21

    A cell is a minimal self-sustaining system that can move and compute. Previous work has shown that a unicellular slime mold, Physarum, can be utilized as a biological computer based on cytoplasmic flow encapsulated by a membrane. Although the interplay between the modification of the boundary of a cell and the cytoplasmic flow surrounded by the boundary plays a key role in Physarum computing, no model of a cell has been developed to describe this interplay. Here we propose a toy model of a cell that shows amoebic motion and can solve a maze, Steiner minimum tree problem and a spanning tree problem. Only by assuming that cytoplasm is hardened after passing external matter (or softened part) through a cell, the shape of the cell and the cytoplasmic flow can be changed. Without cytoplasm hardening, a cell is easily destroyed. This suggests that cytoplasmic hardening and/or sol-gel transformation caused by external perturbation can keep a cell in a critical state leading to a wide variety of shapes and motion.

  1. Motion adaptive patch-based low-rank approach for compressed sensing cardiac cine MRI.

    PubMed

    Yoon, Huisu; Kim, Kyung Sang; Kim, Daniel; Bresler, Yoram; Ye, Jong Chul

    2014-11-01

    One of the technical challenges in cine magnetic resonance imaging (MRI) is to reduce the acquisition time to enable the high spatio-temporal resolution imaging of a cardiac volume within a short scan time. Recently, compressed sensing approaches have been investigated extensively for highly accelerated cine MRI by exploiting transform domain sparsity using linear transforms such as wavelets, and Fourier. However, in cardiac cine imaging, the cardiac volume changes significantly between frames, and there often exist abrupt pixel value changes along time. In order to effectively sparsify such temporal variations, it is necessary to exploit temporal redundancy along motion trajectories. This paper introduces a novel patch-based reconstruction method to exploit geometric similarities in the spatio-temporal domain. In particular, we use a low rank constraint for similar patches along motion, based on the observation that rank structures are relatively less sensitive to global intensity changes, but make it easier to capture moving edges. A Nash equilibrium formulation with relaxation is employed to guarantee convergence. Experimental results show that the proposed algorithm clearly reconstructs important anatomical structures in cardiac cine image and provides improved image quality compared to existing state-of-the-art methods such as k-t FOCUSS, k-t SLR, and MASTeR.

  2. An optimized DSP implementation of adaptive filtering and ICA for motion artifact reduction in ambulatory ECG monitoring.

    PubMed

    Berset, Torfinn; Geng, Di; Romero, Iñaki

    2012-01-01

    Noise from motion artifacts is currently one of the main challenges in the field of ambulatory ECG recording. To address this problem, we propose the use of two different approaches. First, an adaptive filter with electrode-skin impedance as a reference signal is described. Secondly, a multi-channel ECG algorithm based on Independent Component Analysis is introduced. Both algorithms have been designed and further optimized for real-time work embedded in a dedicated Digital Signal Processor. We show that both algorithms improve the performance of a beat detection algorithm when applied in high noise conditions. In addition, an efficient way of choosing this methods is suggested with the aim of reduce the overall total system power consumption.

  3. A Motion Control Method of Multi-joint Robots Utilizing Stiffness Adaptation for Energy Saving

    NASA Astrophysics Data System (ADS)

    Uemura, Mitsunori; Kawamura, Sadao

    This paper investigates a new motion control method of multi-joint robots utilizing stiffness adjustment of mechanical elastic elements for the purpose of energy saving. This control method is designed to realize a condition similar to resonance of linear systems by the stiffness adjustment, even though the controlled systems have nonlinear dynamics and multi degree-of-freedom. The control method has two control objectives. One is to realize trajectory tracking control. The other is to reduce actuator torque as much as possible by the stiffness adjustment. This controller does not require exact parameter values of the controlled systems. Some fundamental parts of stability analysis and an energy saving effect are discussed mathematically. Some simulation results demonstrate the effectiveness of the proposed control method.

  4. Content-adaptive thresholding early termination scheme on directional gradient descent searches for fast block motion estimation

    NASA Astrophysics Data System (ADS)

    Chen, Hung-Ming; Chen, Po-Hung; Lin, Cheng-Tso; Liu, Ching-Chung

    2012-11-01

    An efficient algorithm named modified directional gradient descent searches to enhance the directional gradient descent search (DGDS) algorithm is presented to reduce computations. A modified search pattern with an adaptive threshold for early termination is applied to DGDS to avoid meaningless calculation after the searching point is good enough. A statistical analysis of best motion vector distribution is analyzed to decide the modified search pattern. Then a statistical model based on the characteristics of the block distortion information of the previous coded frame helps the early termination parameters selection, and a trade-off between the video quality and the computational complexity can be obtained. The simulation results show the proposed algorithm provides significant improvement in reducing the motion estimation (ME) by 17.81% of the average search points and 20% of ME time saving compared to the fast DGDS algorithm implemented in H.264/AVC JM 18.2 reference software according to different types of sequences, while maintaining a similar bit rate without losing picture quality.

  5. Flow motion dynamics of microvascular blood flow and oxygenation: Evidence of adaptive changes in obesity and type 2 diabetes mellitus/insulin resistance.

    PubMed

    Clough, Geraldine F; Kuliga, Katarzyna Z; Chipperfield, Andrew J

    2017-02-01

    An altered spatial heterogeneity and temporal stability of network perfusion can give rise to a limited adaptive ability to meet metabolic demands. Derangement of local flow motion activity is associated with reduced microvascular blood flow and tissue oxygenation, and it has been suggested that changes in flow motion activity may provide an early indicator of declining, endothelial, neurogenic, and myogenic regulatory mechanisms and signal the onset and progression of microvascular pathophysiology. This short conference review article explores some of the evidence for altered flow motion dynamics of blood flux signals acquired using laser Doppler fluximetry in the skin in individuals at risk of developing or with cardiometabolic disease.

  6. Adaptive Changes in Sensorimotor Coordination and Motion Sickness Following Repeated Exposures to Virtual Environments

    NASA Technical Reports Server (NTRS)

    Harm, D. L.; Taylor, L. C.; Bloomberg, J. J.

    2007-01-01

    Virtual environments offer unique training opportunities, particularly for training astronauts and preadapting them to the novel sensory conditions of microgravity. Two unresolved human factors issues in virtual reality (VR) systems are: 1) potential "cybersickness", and 2) maladaptive sensorimotor performance following exposure to VR systems. Interestingly, these aftereffects are often quite similar to adaptive sensorimotor responses observed in astronauts during and/or following space flight. Initial interpretation of novel sensory information may be inappropriate and result in perceptual errors. Active exploratory behavior in a new environment, with resulting feedback and the formation of new associations between sensory inputs and response outputs, promotes appropriate perception and motor control in the new environment. Thus, people adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, unilateral labyrinthectomy and experimentally produced stimulus rearrangements. The purpose of this research was to compare disturbances in sensorimotor coordination produced by dome and head-mounted virtual environment displays and to examine the effects of exposure duration, and repeated exposures to VR systems. The first study examined disturbances in balance control, and the second study examined disturbances in eye-head-hand (EHH) and eye-head coordination.

  7. Spiders in motion: demonstrating adaptation, structure-function relationships, and trade-offs in invertebrates.

    PubMed

    Bowlin, Melissa S; McLeer, Dorothy F; Danielson-Francois, Anne M

    2014-03-01

    Evolutionary history and structural considerations constrain all aspects of animal physiology. Constraints on invertebrate locomotion are especially straightforward for students to observe and understand. In this exercise, students use spiders to investigate the concepts of adaptation, structure-function relationships, and trade-offs. Students measure burst and endurance performance in several taxonomic families of spiders whose ecological niches have led to different locomotory adaptations. Based on observations of spiders in their natural habitat and prior background information, students make predictions about spider performance. Students then construct their own knowledge by performing a hands-on, inquiry-based scientific experiment where the results are not necessarily known. Depending on the specific families chosen, students can observe that web-dwelling spiders have more difficulty navigating complex terrestrial terrain than ground-dwelling spiders and that there is a trade-off between burst performance and endurance performance in spiders. Our inexpensive runway design allows for countless variations on this basic experiment; for example, we have successfully used runways to show students how the performance of heterothermic ectotherms varies with temperature. High levels of intra- and interindividual variation in performance underscore the importance of using multiple trials and statistical tests. Finally, this laboratory activity can be completely student driven or standardized, depending on the instructor's preference.

  8. Robust motion correction and outlier rejection of in vivo functional MR images of the fetal brain and placenta during maternal hyperoxia

    NASA Astrophysics Data System (ADS)

    You, Wonsang; Serag, Ahmed; Evangelou, Iordanis E.; Andescavage, Nickie; Limperopoulos, Catherine

    2015-03-01

    Subject motion is a major challenge in functional magnetic resonance imaging studies (fMRI) of the fetal brain and placenta during maternal hyperoxia. We propose a motion correction and volume outlier rejection method for the correction of severe motion artifacts in both fetal brain and placenta. The method is optimized to the experimental design by processing different phases of acquisition separately. It also automatically excludes high-motion volumes and all the missing data are regressed from ROI-averaged signals. The results demonstrate that the proposed method is effective in enhancing motion correction in fetal fMRI without large data loss, compared to traditional motion correction methods.

  9. Constraints on the Source of Short-Term Motion Adaptation in Macaque Area MT. I. The Role of Input and Intrinsic Mechanisms

    PubMed Central

    PRIEBE, NICHOLAS J.; CHURCHLAND, MARK M.; LISBERGER, STEPHEN G.

    2008-01-01

    Neurons in area MT, a motion-sensitive area of extrastriate cortex, respond to a step of target velocity with a transient-sustained firing pattern. The transition from a high initial firing rate to a lower sustained rate occurs over a time course of 20–80 ms and is considered a form of short-term adaptation. The present paper asks whether adaptation is due to input-specific mechanisms such as short-term synaptic depression or if it results from intrinsic cellular mechanisms such as spike-rate adaptation. We assessed the contribution of input-specific mechanisms by using a condition/test paradigm to measure the spatial scale of adaptation. Conditioning and test stimuli were placed within MT receptive fields but were spatially segregated so that the two stimuli would activate different populations of inputs from the primary visual cortex (V1). Conditioning motion at one visual location caused a reduction of the transient firing to subsequent test motion at a second location. The adaptation field, estimated as the region of visual space where conditioning motion caused adaptation, was always larger than the MT receptive field. Use of the same stimulus configuration while recording from direction-selective neurons in V1 failed to demonstrate either adaptation or the transient-sustained response pattern that is the signature of short-term adaptation in MT. We conclude that the shift from transient to sustained firing in MT cells does not result from an input-specific mechanism applied to inputs from V1 because it operates over a wider range of the visual field than is covered by receptive fields of V1 neurons. We used a direct analysis of MT neuron spike trains for many repetitions of the same motion stimulus to assess the contribution to adaptation of intrinsic cellular mechanisms related to spiking. On a trial-by-trial basis, there was no correlation between number of spikes in the transient interval and the interval immediately after the transient period. This is

  10. Trypanosome Motion Represents an Adaptation to the Crowded Environment of the Vertebrate Bloodstream

    PubMed Central

    Heddergott, Niko; Krüger, Timothy; Babu, Sujin B.; Wei, Ai; Stellamanns, Erik; Uppaluri, Sravanti; Pfohl, Thomas; Stark, Holger; Engstler, Markus

    2012-01-01

    Blood is a remarkable habitat: it is highly viscous, contains a dense packaging of cells and perpetually flows at velocities varying over three orders of magnitude. Only few pathogens endure the harsh physical conditions within the vertebrate bloodstream and prosper despite being constantly attacked by host antibodies. African trypanosomes are strictly extracellular blood parasites, which evade the immune response through a system of antigenic variation and incessant motility. How the flagellates actually swim in blood remains to be elucidated. Here, we show that the mode and dynamics of trypanosome locomotion are a trait of life within a crowded environment. Using high-speed fluorescence microscopy and ordered micro-pillar arrays we show that the parasites mode of motility is adapted to the density of cells in blood. Trypanosomes are pulled forward by the planar beat of the single flagellum. Hydrodynamic flow across the asymmetrically shaped cell body translates into its rotational movement. Importantly, the presence of particles with the shape, size and spacing of blood cells is required and sufficient for trypanosomes to reach maximum forward velocity. If the density of obstacles, however, is further increased to resemble collagen networks or tissue spaces, the parasites reverse their flagellar beat and consequently swim backwards, in this way avoiding getting trapped. In the absence of obstacles, this flagellar beat reversal occurs randomly resulting in irregular waveforms and apparent cell tumbling. Thus, the swimming behavior of trypanosomes is a surprising example of micro-adaptation to life at low Reynolds numbers. For a precise physical interpretation, we compare our high-resolution microscopic data to results from a simulation technique that combines the method of multi-particle collision dynamics with a triangulated surface model. The simulation produces a rotating cell body and a helical swimming path, providing a functioning simulation method for a

  11. An Adaptive Flow Solver for Air-Borne Vehicles Undergoing Time-Dependent Motions/Deformations

    NASA Technical Reports Server (NTRS)

    Singh, Jatinder; Taylor, Stephen

    1997-01-01

    This report describes a concurrent Euler flow solver for flows around complex 3-D bodies. The solver is based on a cell-centered finite volume methodology on 3-D unstructured tetrahedral grids. In this algorithm, spatial discretization for the inviscid convective term is accomplished using an upwind scheme. A localized reconstruction is done for flow variables which is second order accurate. Evolution in time is accomplished using an explicit three-stage Runge-Kutta method which has second order temporal accuracy. This is adapted for concurrent execution using another proven methodology based on concurrent graph abstraction. This solver operates on heterogeneous network architectures. These architectures may include a broad variety of UNIX workstations and PCs running Windows NT, symmetric multiprocessors and distributed-memory multi-computers. The unstructured grid is generated using commercial grid generation tools. The grid is automatically partitioned using a concurrent algorithm based on heat diffusion. This results in memory requirements that are inversely proportional to the number of processors. The solver uses automatic granularity control and resource management techniques both to balance load and communication requirements, and deal with differing memory constraints. These ideas are again based on heat diffusion. Results are subsequently combined for visualization and analysis using commercial CFD tools. Flow simulation results are demonstrated for a constant section wing at subsonic, transonic, and a supersonic case. These results are compared with experimental data and numerical results of other researchers. Performance results are under way for a variety of network topologies.

  12. Principal component analysis-based anatomical motion models for use in adaptive radiation therapy of head and neck cancer patients

    NASA Astrophysics Data System (ADS)

    Chetvertkov, Mikhail A.

    Purpose: To develop standard and regularized principal component analysis (PCA) models of anatomical changes from daily cone beam CTs (CBCTs) of head and neck (H&N) patients, assess their potential use in adaptive radiation therapy (ART), and to extract quantitative information for treatment response assessment. Methods: Planning CT (pCT) images of H&N patients were artificially deformed to create "digital phantom" images, which modeled systematic anatomical changes during Radiation Therapy (RT). Artificial deformations closely mirrored patients' actual deformations, and were interpolated to generate 35 synthetic CBCTs, representing evolving anatomy over 35 fractions. Deformation vector fields (DVFs) were acquired between pCT and synthetic CBCTs (i.e., digital phantoms), and between pCT and clinical CBCTs. Patient-specific standard PCA (SPCA) and regularized PCA (RPCA) models were built from these synthetic and clinical DVF sets. Eigenvectors, or eigenDVFs (EDVFs), having the largest eigenvalues were hypothesized to capture the major anatomical deformations during treatment. Modeled anatomies were used to assess the dose deviations with respect to the planned dose distribution. Results: PCA models achieve variable results, depending on the size and location of anatomical change. Random changes prevent or degrade SPCA's ability to detect underlying systematic change. RPCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes, and is therefore more successful than SPCA at capturing systematic changes early in treatment. SPCA models were less successful at modeling systematic changes in clinical patient images, which contain a wider range of random motion than synthetic CBCTs, while the regularized approach was able to extract major modes of motion. For dose assessment it has been shown that the modeled dose distribution was different from the planned dose for the parotid glands due to their shrinkage and shift into

  13. Motion-artifact-robust, polarization-resolved second-harmonic-generation microscopy based on rapid polarization switching with electro-optic Pockells cell and its application to in vivo visualization of collagen fiber orientation in human facial skin.

    PubMed

    Tanaka, Yuji; Hase, Eiji; Fukushima, Shuichiro; Ogura, Yuki; Yamashita, Toyonobu; Hirao, Tetsuji; Araki, Tsutomu; Yasui, Takeshi

    2014-04-01

    Polarization-resolved second-harmonic-generation (PR-SHG) microscopy is a powerful tool for investigating collagen fiber orientation quantitatively with low invasiveness. However, the waiting time for the mechanical polarization rotation makes it too sensitive to motion artifacts and hence has hampered its use in various applications in vivo. In the work described in this article, we constructed a motion-artifact-robust, PR-SHG microscope based on rapid polarization switching at every pixel with an electro-optic Pockells cell (PC) in synchronization with step-wise raster scanning of the focus spot and alternate data acquisition of a vertical-polarization-resolved SHG signal and a horizontal-polarization-resolved one. The constructed PC-based PR-SHG microscope enabled us to visualize orientation mapping of dermal collagen fiber in human facial skin in vivo without the influence of motion artifacts. Furthermore, it implied the location and/or age dependence of the collagen fiber orientation in human facial skin. The robustness to motion artifacts in the collagen orientation measurement will expand the application scope of SHG microscopy in dermatology and collagen-related fields.

  14. (Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

    PubMed Central

    2013-01-01

    Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and

  15. Adaptive marker-free registration using a multiple point strategy for real-time and robust endoscope electromagnetic navigation.

    PubMed

    Luo, Xiongbiao; Wan, Ying; He, Xiangjian; Mori, Kensaku

    2015-02-01

    Registration of pre-clinical images to physical space is indispensable for computer-assisted endoscopic interventions in operating rooms. Electromagnetically navigated endoscopic interventions are increasingly performed at current diagnoses and treatments. Such interventions use an electromagnetic tracker with a miniature sensor that is usually attached at an endoscope distal tip to real time track endoscope movements in a pre-clinical image space. Spatial alignment between the electromagnetic tracker (or sensor) and pre-clinical images must be performed to navigate the endoscope to target regions. This paper proposes an adaptive marker-free registration method that uses a multiple point selection strategy. This method seeks to address an assumption that the endoscope is operated along the centerline of an intraluminal organ which is easily violated during interventions. We introduce an adaptive strategy that generates multiple points in terms of sensor measurements and endoscope tip center calibration. From these generated points, we adaptively choose the optimal point, which is the closest to its assigned the centerline of the hollow organ, to perform registration. The experimental results demonstrate that our proposed adaptive strategy significantly reduced the target registration error from 5.32 to 2.59 mm in static phantoms validation, as well as from at least 7.58 mm to 4.71 mm in dynamic phantom validation compared to current available methods.

  16. Progress on Developing Adaptive Optics–Optical Coherence Tomography for In Vivo Retinal Imaging: Monitoring and Correction of Eye Motion Artifacts

    PubMed Central

    Zawadzki, Robert J.; Capps, Arlie G.; Kim, Dae Yu; Panorgias, Athanasios; Stevenson, Scott B.; Hamann, Bernd; Werner, John S.

    2014-01-01

    Recent progress in retinal image acquisition techniques, including optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO), combined with improved performance of adaptive optics (AO) instrumentation, has resulted in improvement in the quality of in vivo images of cellular structures in the human retina. Here, we present a short review of progress on developing AO-OCT instruments. Despite significant progress in imaging speed and resolution, eye movements present during acquisition of a retinal image with OCT introduce motion artifacts into the image, complicating analysis and registration. This effect is especially pronounced in high-resolution datasets acquired with AO-OCT instruments. Several retinal tracking systems have been introduced to correct retinal motion during data acquisition. We present a method for correcting motion artifacts in AO-OCT volume data after acquisition using simultaneously captured adaptive optics-scanning laser ophthalmoscope (AO-SLO) images. We extract transverse eye motion data from the AO-SLO images, assign a motion adjustment vector to each AO-OCT A-scan, and re-sample from the scattered data back onto a regular grid. The corrected volume data improve the accuracy of quantitative analyses of microscopic structures. PMID:25544826

  17. Progress on Developing Adaptive Optics-Optical Coherence Tomography for In Vivo Retinal Imaging: Monitoring and Correction of Eye Motion Artifacts.

    PubMed

    Zawadzki, Robert J; Capps, Arlie G; Kim, Dae Yu; Panorgias, Athanasios; Stevenson, Scott B; Hamann, Bernd; Werner, John S

    2014-03-01

    Recent progress in retinal image acquisition techniques, including optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO), combined with improved performance of adaptive optics (AO) instrumentation, has resulted in improvement in the quality of in vivo images of cellular structures in the human retina. Here, we present a short review of progress on developing AO-OCT instruments. Despite significant progress in imaging speed and resolution, eye movements present during acquisition of a retinal image with OCT introduce motion artifacts into the image, complicating analysis and registration. This effect is especially pronounced in high-resolution datasets acquired with AO-OCT instruments. Several retinal tracking systems have been introduced to correct retinal motion during data acquisition. We present a method for correcting motion artifacts in AO-OCT volume data after acquisition using simultaneously captured adaptive optics-scanning laser ophthalmoscope (AO-SLO) images. We extract transverse eye motion data from the AO-SLO images, assign a motion adjustment vector to each AO-OCT A-scan, and re-sample from the scattered data back onto a regular grid. The corrected volume data improve the accuracy of quantitative analyses of microscopic structures.

  18. Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

    PubMed

    Bagheri, Pedram; Sun, Qiao

    2016-07-01

    In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers.

  19. Noise-Robust Spectral Signature Classification in Non-resolved Object Detection using Feedback Controlled Adaptive Learning

    NASA Astrophysics Data System (ADS)

    Schmalz, M.; Key, G.

    2012-09-01

    Accurate spectral signature classification is key to reliable nonresolved detection and recognition of spaceborne objects. In classical signature-based recognition applications, classification accuracy has been shown to depend on accurate spectral endmember discrimination. Unfortunately, signatures are corrupted by noise and clutter that can be nonergodic in astronomical imaging practice. In previous work, we have shown that object class separation and classifier refinement results can be severely corrupted by input noise, leading to suboptimal classification. We have also shown that computed pattern recognition, like its human counterpart, can benefit from processes such as learning or forgetting, which in spectral signature classification can support adaptive tracking of input nonergodicities. In this paper, we model learning as the acquisition or insertion of a new pattern into a classifier's knowledge base. For example, in neural nets (NNs), this insertion process could correspond to the superposition of a new pattern onto the NN weight matrix. Similarly, we model forgetting as the deletion of a pattern currently stored in the classifier knowledge base, for example, as a pattern deletion operation on the NN weight matrix, which is a difficult goal with classical neural nets (CNNs). In particular, this paper discusses the implementation of feedback control for pattern insertion and deletion in lattice associative memories (LAMs) and dynamically adaptive statistical data fusion (DASDAF) paradigms, in support of signature classification. It is shown that adaptive classifiers based on LNN or DASDAF technology can achieve accurate signature classification in the presence of nonergodic Gaussian and non-Gaussian noise, at low signal-to-noise ratio (SNR). Demonstration involves classification of multiple closely spaced, noise corrupted signatures from a NASA database of space material signatures at SNR > 0.1:1.

  20. The AFIT gross motion control project

    NASA Technical Reports Server (NTRS)

    Leahy, M. B., Jr.

    1991-01-01

    The objective of the Gross Motion Control project is to study alternative control approaches that will provide payload invariant high speed trajectory tracking for nonrepetitive motions in free space. The research has concentrated on modifications to the model-based control structure. Development and evaluation is being actively pursued of both adaptive primary (inner loop) and robust secondary (output loop) controllers. In-house developments are compared and contrasted to the techniques proposed by other researchers. The case study for the evaluation is the first three links of a PUMA-560. Incorporating the principals of multiple model adaptive estimation, artificial neural networks, and Lyapunov theory into the model based paradigm has shown the potential for enhanced tracking. Secondary controllers based on Quantitative Feedback Theory, or augmented with auxiliary inputs, significantly improve the robustness to payload variations and unmodeled drive system dynamics. An overview is presented of the different concepts under investigation and a sample is provided of the latest experimental results.

  1. Robustness and strategies of adaptation among farmer varieties of African Rice (Oryza glaberrima) and Asian Rice (Oryza sativa) across West Africa.

    PubMed

    Mokuwa, Alfred; Nuijten, Edwin; Okry, Florent; Teeken, Béla; Maat, Harro; Richards, Paul; Struik, Paul C

    2013-01-01

    This study offers evidence of the robustness of farmer rice varieties (Oryza glaberrima and O. sativa) in West Africa. Our experiments in five West African countries showed that farmer varieties were tolerant of sub-optimal conditions, but employed a range of strategies to cope with stress. Varieties belonging to the species Oryza glaberrima - solely the product of farmer agency - were the most successful in adapting to a range of adverse conditions. Some of the farmer selections from within the indica and japonica subspecies of O. sativa also performed well in a range of conditions, but other farmer selections from within these two subspecies were mainly limited to more specific niches. The results contradict the rather common belief that farmer varieties are only of local value. Farmer varieties should be considered by breeding programmes and used (alongside improved varieties) in dissemination projects for rural food security.

  2. A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

    NASA Astrophysics Data System (ADS)

    Ushaq, Muhammad; Fang, Jiancheng

    2013-10-01

    Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be

  3. Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

    PubMed

    Bagherpoor, H M; Salmasi, Farzad R

    2015-07-01

    In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance.

  4. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  5. Carotid artery wall motion analysis from B-mode ultrasound using adaptive block matching: in silico evaluation and in vivo application

    NASA Astrophysics Data System (ADS)

    Gastounioti, A.; Golemati, S.; Stoitsis, J. S.; Nikita, K. S.

    2013-12-01

    Valid risk stratification for carotid atherosclerotic plaques represents a crucial public health issue toward preventing fatal cerebrovascular events. Although motion analysis (MA) provides useful information about arterial wall dynamics, the identification of motion-based risk markers remains a significant challenge. Considering that the ability of a motion estimator (ME) to handle changes in the appearance of motion targets has a major effect on accuracy in MA, we investigated the potential of adaptive block matching (ABM) MEs, which consider changes in image intensities over time. To assure the validity in MA, we optimized and evaluated the ABM MEs in the context of a specially designed in silico framework. ABMFIRF2, which takes advantage of the periodicity characterizing the arterial wall motion, was the most effective ABM algorithm, yielding a 47% accuracy increase with respect to the conventional block matching. The in vivo application of ABMFIRF2 revealed five potential risk markers: low movement amplitude of the normal part of the wall adjacent to the plaques in the radial (RMAPWL) and longitudinal (LMAPWL) directions, high radial motion amplitude of the plaque top surface (RMAPTS), and high relative movement, expressed in terms of radial strain (RSIPL) and longitudinal shear strain (LSSIPL), between plaque top and bottom surfaces. The in vivo results were reproduced by OFLK(WLS) and ABMKF-K2, MEs previously proposed by the authors and with remarkable in silico performances, thereby reinforcing the clinical values of the markers and the potential of those MEs. Future in vivo studies will elucidate with confidence the full potential of the markers.

  6. A vision-based system for measuring the displacements of large structures: Simultaneous adaptive calibration and full motion estimation

    NASA Astrophysics Data System (ADS)

    Santos, C. Almeida; Costa, C. Oliveira; Batista, J.

    2016-05-01

    The paper describes a kinematic model-based solution to estimate simultaneously the calibration parameters of the vision system and the full-motion (6-DOF) of large civil engineering structures, namely of long deck suspension bridges, from a sequence of stereo images captured by digital cameras. Using an arbitrary number of images and assuming a smooth structure motion, an Iterated Extended Kalman Filter is used to recursively estimate the projection matrices of the cameras and the structure full-motion (displacement and rotation) over time, helping to meet the structure health monitoring fulfilment. Results related to the performance evaluation, obtained by numerical simulation and with real experiments, are reported. The real experiments were carried out in indoor and outdoor environment using a reduced structure model to impose controlled motions. In both cases, the results obtained with a minimum setup comprising only two cameras and four non-coplanar tracking points, showed a high accuracy results for on-line camera calibration and structure full motion estimation.

  7. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  8. TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion

    SciTech Connect

    Wei, J; Yuan, A; Li, G

    2014-06-15

    Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, segment, register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung segmentation algorithm was designed and 4D lung segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is <±2% and the time saving is by 1–2 orders of magnitude. Conclusion: A framework of 4D toolkit has been developed to analyze thoracic 4DCT automatically or interactively, facilitating both investigational

  9. Robust model reference adaptive control for a two-dimensional piezo-driven micro-displacement scanning platform based on the asymmetrical Bouc-Wen model

    NASA Astrophysics Data System (ADS)

    Yang, Haigen; Zhu, Wei; Fu, Xiao

    2016-11-01

    The hysteresis characteristics resulted from piezoelectric actuators (PAs) and the residual vibration in the rapid positioning of a two-dimensional piezo-driven micro-displacement scanning platform (2D-PDMDSP) will greatly affect the positioning accuracy and speed. In this paper, in order to improve the accuracy and speed of the positioning and restrain the residual vibration of 2D-PDMDSP, firstly, Utilizing an online hysteresis observer based on the asymmetrical Bouc-Wen model, the PA with the hysteresis characteristics is feedforward linearized and can be used as a linear actuator; secondly, zero vibration and derivative shaping (ZVDS) technique is used to eliminate the residual vibration of the 2D-PDMDSP; lastly, the robust model reference adaptive (RMRA) control for the 2D-PDMDSP is proposed and explored. The rapid control prototype of the RMRA controller combining the proposed feedforward linearization and ZVDS control for the 2D-PDMDSP with rapid control prototyping technique based on the real-time simulation system is established and experimentally tested, and the corresponding controlled results are compared with those by the PID control method. The experimental results show that the proposed RMRA control method can significantly improve the accuracy and speed of the positioning and restrain the residual vibration of 2D-PDMDSP.

  10. The Balance Super Learner: A robust adaptation of the Super Learner to improve estimation of the average treatment effect in the treated based on propensity score matching.

    PubMed

    Pirracchio, Romain; Carone, Marco

    2016-01-01

    Consistency of the propensity score estimators rely on correct specification of the propensity score model. The propensity score is frequently estimated using a main effect logistic regression. It has recently been shown that the use of ensemble machine learning algorithms, such as the Super Learner, could improve covariate balance and reduce bias in a meaningful manner in the case of serious model misspecification for treatment assignment. However, the loss functions normally used by the Super Learner may not be appropriate for propensity score estimation since the goal in this problem is not to optimize propensity score prediction but rather to achieve the best possible balance in the covariate distribution between treatment groups. In a simulation study, we evaluated the benefit of a modification of the Super Learner by propensity score estimation geared toward achieving covariate balance between the treated and untreated after matching on the propensity score. Our simulation study included six different scenarios characterized by various degrees of deviation from the usual main term logistic model for the true propensity score and outcome as well as the presence (or not) of instrumental variables. Our results suggest that the use of this adapted Super Learner to estimate the propensity score can further improve the robustness of propensity score matching estimators.

  11. Robust dynamic myocardial perfusion CT deconvolution for accurate residue function estimation via adaptive-weighted tensor total variation regularization: a preclinical study

    NASA Astrophysics Data System (ADS)

    Zeng, Dong; Gong, Changfei; Bian, Zhaoying; Huang, Jing; Zhang, Xinyu; Zhang, Hua; Lu, Lijun; Niu, Shanzhou; Zhang, Zhang; Liang, Zhengrong; Feng, Qianjin; Chen, Wufan; Ma, Jianhua

    2016-11-01

    Dynamic myocardial perfusion computed tomography (MPCT) is a promising technique for quick diagnosis and risk stratification of coronary artery disease. However, one major drawback of dynamic MPCT imaging is the heavy radiation dose to patients due to its dynamic image acquisition protocol. In this work, to address this issue, we present a robust dynamic MPCT deconvolution algorithm via adaptive-weighted tensor total variation (AwTTV) regularization for accurate residue function estimation with low-mA s data acquisitions. For simplicity, the presented method is termed ‘MPD-AwTTV’. More specifically, the gains of the AwTTV regularization over the original tensor total variation regularization are from the anisotropic edge property of the sequential MPCT images. To minimize the associative objective function we propose an efficient iterative optimization strategy with fast convergence rate in the framework of an iterative shrinkage/thresholding algorithm. We validate and evaluate the presented algorithm using both digital XCAT phantom and preclinical porcine data. The preliminary experimental results have demonstrated that the presented MPD-AwTTV deconvolution algorithm can achieve remarkable gains in noise-induced artifact suppression, edge detail preservation, and accurate flow-scaled residue function and MPHM estimation as compared with the other existing deconvolution algorithms in digital phantom studies, and similar gains can be obtained in the porcine data experiment.

  12. Ambiguous Tilt and Translation Motion Cues after Space Flight and Otolith Assessment during Post-Flight Re-Adaptation

    NASA Technical Reports Server (NTRS)

    Wood, Scott J.; Clarke, A. H.; Harm, D. L.; Rupert, A. H.; Clement, G. R.

    2009-01-01

    Adaptive changes during space flight in how the brain integrates vestibular cues with other sensory information can lead to impaired movement coordination, vertigo, spatial disorientation and perceptual illusions following Gtransitions. These studies are designed to examine both the physiological basis and operational implications for disorientation and tilt-translation disturbances following short duration space flights.

  13. MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

    SciTech Connect

    Liu, F; Tai, A; Ahunbay, E; Gore, E; Johnstone, C; Li, X

    2014-06-15

    Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method.

  14. A fast Adaptive-Gain Orientation Filter of inertial/magnetic data for human motion tracking in free-living environments.

    PubMed

    Tian, Ya; Tan, Jindong

    2012-01-01

    High-resolution, real-time data obtained by human motion tracking systems can be used for gait analysis, which helps better understanding the cause of many diseases for more effective treatments, such as rehabilitation for outpatients or recovery from lost motor functions after a stroke. This paper presents an analytically derived method for an adaptive-gain complementary filter based on the convergence rate from the Gauss-Newton optimization algorithm (GNA) and the divergence rate from the gyroscope, which is referred as Adaptive-Gain Orientation Filter (AGOF) in this paper. The AGOF has the advantages of one iteration calculation to reduce the computing load and accurate estimation of gyroscope measurement error. Moreover, for handling magnetic distortions especially in indoor environments and movements with excessive acceleration, adaptive measurement vectors and a reference vector for Earth's magnetic field selection schemes are introduced to help the GNA find more accurate direction of gyroscope error. Experimental results are presented to verify the performance of the proposed method, which shows better accuracy of orientation estimation than several well-known methods.

  15. Kinematics and Dynamics of Motion Control Based on Acceleration Control

    NASA Astrophysics Data System (ADS)

    Ohishi, Kiyoshi; Ohba, Yuzuru; Katsura, Seiichiro

    The first IEEE International Workshop on Advanced Motion Control was held in 1990 pointed out the importance of physical interpretation of motion control. The software servoing technology is now common in machine tools, robotics, and mechatronics. It has been intensively developed for the numerical control (NC) machines. Recently, motion control in unknown environment will be more and more important. Conventional motion control is not always suitable due to the lack of adaptive capability to the environment. A more sophisticated ability in motion control is necessary for compliant contact with environment. Acceleration control is the key technology of motion control in unknown environment. The acceleration control can make a motion system to be a zero control stiffness system without losing the robustness. Furthermore, a realization of multi-degree-of-freedom motion is necessary for future human assistance. A human assistant motion will require various control stiffness corresponding to the task. The review paper focuses on the modal coordinate system to integrate the various control stiffness in the virtual axes. A bilateral teleoperation is a good candidate to consider the future human assistant motion and integration of decentralized systems. Thus the paper reviews and discusses the bilateral teleoperation from the control stiffness and the modal control design points of view.

  16. From Monotonous Hop-and-Sink Swimming to Constant Gliding via Chaotic Motions in 3D: Is There Adaptive Behavior in Planktonic Micro-Crustaceans?

    NASA Astrophysics Data System (ADS)

    Strickler, J. R.

    2007-12-01

    Planktonic micro-crustaceans, such as Daphnia, Copepod, and Cyclops, swim in the 3D environment of water and feed on suspended material, mostly algae and bacteria. Their mechanisms for swimming differ; some use their swimming legs to produce one hop per second resulting in a speed of one body-length per second, while others scan water volumes with their mouthparts and glide through the water column at 1 to 10 body-lengths per second. However, our observations show that these speeds are modulated. The question to be discussed will be whether or not these modulations show adaptive behavior taking food quality and food abundance as criteria for the swimming performances. Additionally, we investigated the degree these temporal motion patterns are dependant on the sizes, and therefore, on the Reynolds number of the animals.

  17. The adaptive drop foot stimulator - Multivariable learning control of foot pitch and roll motion in paretic gait.

    PubMed

    Seel, Thomas; Werner, Cordula; Schauer, Thomas

    2016-11-01

    Many stroke patients suffer from the drop foot syndrome, which is characterized by a limited ability to lift (the lateral and/or medial edge of) the foot and leads to a pathological gait. In this contribution, we consider the treatment of this syndrome via functional electrical stimulation (FES) of the peroneal nerve during the swing phase of the paretic foot. A novel three-electrodes setup allows us to manipulate the recruitment of m. tibialis anterior and m. fibularis longus via two independent FES channels without violating the zero-net-current requirement of FES. We characterize the domain of admissible stimulation intensities that results from the nonlinearities in patients' stimulation intensity tolerance. To compensate most of the cross-couplings between the FES intensities and the foot motion, we apply a nonlinear controller output mapping. Gait phase transitions as well as foot pitch and roll angles are assessed in realtime by means of an Inertial Measurement Unit (IMU). A decentralized Iterative Learning Control (ILC) scheme is used to adjust the stimulation to the current needs of the individual patient. We evaluate the effectiveness of this approach in experimental trials with drop foot patients walking on a treadmill and on level ground. Starting from conventional stimulation parameters, the controller automatically determines individual stimulation parameters and thus achieves physiological foot pitch and roll angle trajectories within at most two strides.

  18. Engineering robust intelligent robots

    NASA Astrophysics Data System (ADS)

    Hall, E. L.; Ali, S. M. Alhaj; Ghaffari, M.; Liao, X.; Cao, M.

    2010-01-01

    The purpose of this paper is to discuss the challenge of engineering robust intelligent robots. Robust intelligent robots may be considered as ones that not only work in one environment but rather in all types of situations and conditions. Our past work has described sensors for intelligent robots that permit adaptation to changes in the environment. We have also described the combination of these sensors with a "creative controller" that permits adaptive critic, neural network learning, and a dynamic database that permits task selection and criteria adjustment. However, the emphasis of this paper is on engineering solutions which are designed for robust operations and worst case situations such as day night cameras or rain and snow solutions. This ideal model may be compared to various approaches that have been implemented on "production vehicles and equipment" using Ethernet, CAN Bus and JAUS architectures and to modern, embedded, mobile computing architectures. Many prototype intelligent robots have been developed and demonstrated in terms of scientific feasibility but few have reached the stage of a robust engineering solution. Continual innovation and improvement are still required. The significance of this comparison is that it provides some insights that may be useful in designing future robots for various manufacturing, medical, and defense applications where robust and reliable performance is essential.

  19. Robustness in bacterial chemotaxis

    NASA Astrophysics Data System (ADS)

    Alon, U.; Surette, M. G.; Barkai, N.; Leibler, S.

    1999-01-01

    Networks of interacting proteins orchestrate the responses of living cells to a variety of external stimuli, but how sensitive is the functioning of these protein networks to variations in theirbiochemical parameters? One possibility is that to achieve appropriate function, the reaction rate constants and enzyme concentrations need to be adjusted in a precise manner, and any deviation from these `fine-tuned' values ruins the network's performance. An alternative possibility is that key properties of biochemical networks are robust; that is, they are insensitive to the precise values of the biochemical parameters. Here we address this issue in experiments using chemotaxis of Escherichia coli, one of the best-characterized sensory systems,. We focus on how response and adaptation to attractant signals vary with systematic changes in the intracellular concentration of the components of the chemotaxis network. We find that some properties, such as steady-state behaviour and adaptation time, show strong variations in response to varying protein concentrations. In contrast, the precision of adaptation is robust and does not vary with the protein concentrations. This is consistent with a recently proposed molecular mechanism for exact adaptation, where robustness is a direct consequence of the network's architecture.

  20. Control of joint motion simulators for biomechanical research

    NASA Technical Reports Server (NTRS)

    Colbaugh, R.; Glass, K.

    1992-01-01

    The authors present a hierarchical adaptive algorithm for controlling upper extremity human joint motion simulators. A joint motion simulator is a computer-controlled, electromechanical system which permits the application of forces to the tendons of a human cadaver specimen in such a way that the cadaver joint under study achieves a desired motion in a physiologic manner. The proposed control scheme does not require knowledge of the cadaver specimen dynamic model, and solves on-line the indeterminate problem which arises because human joints typically possess more actuators than degrees of freedom. Computer simulation results are given for an elbow/forearm system and wrist/hand system under hierarchical control. The results demonstrate that any desired normal joint motion can be accurately tracked with the proposed algorithm. These simulation results indicate that the controller resolved the indeterminate problem redundancy in a physiologic manner, and show that the control scheme was robust to parameter uncertainty and to sensor noise.

  1. Experimental evaluation of a robust optimization method for IMRT of moving targets

    NASA Astrophysics Data System (ADS)

    Vrančić, Christian; Trofimov, Alexei; Chan, Timothy C. Y.; Sharp, Gregory C.; Bortfeld, Thomas

    2009-05-01

    Internal organ motion during radiation therapy, if not considered appropriately in the planning process, has been shown to reduce target coverage and increase the dose to healthy tissues. Standard planning approaches, which use safety margins to handle intrafractional movement of the tumor, are typically designed based on the maximum amplitude of motion, and are often overly conservative. Comparable coverage and reduced dose to healthy organs appear achievable with robust motion-adaptive treatment planning, which considers the expected probability distribution of the average target position and the uncertainty of its realization during treatment delivery. A dosimetric test of a robust optimization method for IMRT was performed, using patient breathing data. External marker motion data acquired from respiratory-gated radiotherapy patients were used to build and test the framework for robust optimization. The motion trajectories recorded during radiation treatment itself are not strictly necessary to generate the initial version of a robust treatment plan, but can be used to adapt the plan during the course of treatment. Single-field IMRT plans were optimized to deliver a uniform dose to a rectangular area. During delivery on a linear accelerator, a computer-driven motion phantom reproduced the patients' breathing patterns and a two-dimensional ionization detector array measured the dose delivered. The dose distributions from robust-optimized plans were compared to those from standard plans, which used a margin expansion. Dosimetric tests confirmed the improved sparing of the non-target area with robust planning, which was achieved without compromising the target coverage. The maximum dose in robust plans did not exceed 110% of the prescription, while the minimum target doses were comparable in standard and robust plans. In test courses, optimized for a simplified target geometry, and delivered to a phantom that moved in one dimension with an average amplitude of 17

  2. Psychrobacter arcticus 273-4 Uses Resource Efficiency and Molecular Motion Adaptations for Subzero Temperature Growth▿ †

    PubMed Central

    Bergholz, Peter W.; Bakermans , Corien; Tiedje, James M.

    2009-01-01

    Permafrost soils are extreme environments that exert low-temperature, desiccation, and starvation stress on bacteria over thousands to millions of years. To understand how Psychrobacter arcticus 273-4 survived for >20,000 years in permafrost, transcriptome analysis was performed during growth at 22°C, 17°C, 0°C, and −6°C using a mixed-effects analysis of variance model. Genes for transcription, translation, energy production, and most biosynthetic pathways were downregulated at low temperatures. Evidence of isozyme exchange was detected over temperature for d-alanyl-d-alanine carboxypeptidases (dac1 and dac2), DEAD-box RNA helicases (csdA and Psyc_0943), and energy-efficient substrate incorporation pathways for ammonium and acetate. Specific functions were compensated by upregulation of genes at low temperature, including genes for the biosynthesis of proline, tryptophan, and methionine. RNases and peptidases were generally upregulated at low temperatures. Changes in energy metabolism, amino acid metabolism, and RNase gene expression were consistent with induction of a resource efficiency response. In contrast to results observed for other psychrophiles and mesophiles, only clpB and hsp33 were upregulated at low temperature, and there was no upregulation of other chaperones and peptidyl-prolyl isomerases. relA, csdA, and dac2 knockout mutants grew more slowly at low temperature, but a dac1 mutant grew more slowly at 17°C. The combined data suggest that the basal biological machinery, including translation, transcription, and energy metabolism, is well adapted to function across the growth range of P. arcticus from −6°C to 22°C, and temperature compensation by gene expression was employed to address specific challenges to low-temperature growth. PMID:19168616

  3. A robust H.264/AVC video watermarking scheme with drift compensation.

    PubMed

    Jiang, Xinghao; Sun, Tanfeng; Zhou, Yue; Wang, Wan; Shi, Yun-Qing

    2014-01-01

    A robust H.264/AVC video watermarking scheme for copyright protection with self-adaptive drift compensation is proposed. In our scheme, motion vector residuals of macroblocks with the smallest partition size are selected to hide copyright information in order to hold visual impact and distortion drift to a minimum. Drift compensation is also implemented to reduce the influence of watermark to the most extent. Besides, discrete cosine transform (DCT) with energy compact property is applied to the motion vector residual group, which can ensure robustness against intentional attacks. According to the experimental results, this scheme gains excellent imperceptibility and low bit-rate increase. Malicious attacks with different quantization parameters (QPs) or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression.

  4. A Robust H.264/AVC Video Watermarking Scheme with Drift Compensation

    PubMed Central

    Sun, Tanfeng; Zhou, Yue; Shi, Yun-Qing

    2014-01-01

    A robust H.264/AVC video watermarking scheme for copyright protection with self-adaptive drift compensation is proposed. In our scheme, motion vector residuals of macroblocks with the smallest partition size are selected to hide copyright information in order to hold visual impact and distortion drift to a minimum. Drift compensation is also implemented to reduce the influence of watermark to the most extent. Besides, discrete cosine transform (DCT) with energy compact property is applied to the motion vector residual group, which can ensure robustness against intentional attacks. According to the experimental results, this scheme gains excellent imperceptibility and low bit-rate increase. Malicious attacks with different quantization parameters (QPs) or motion estimation algorithms can be resisted efficiently, with 80% accuracy on average after lossy compression. PMID:24672376

  5. Robust Motion Processing in the Visual Cortex

    NASA Astrophysics Data System (ADS)

    Sederberg, Audrey; Liu, Julia; Kaschube, Matthias

    2009-03-01

    Direction selectivity is an important model system for studying cortical processing. The role of inhibition in models of direction selectivity in the visual cortex is not well understood. We probe the selectivity of an integrate-and-fire neuron with a noisy background on top of a deterministic input current determined by a temporal-lag model for selectivity, including first only excitatory inputs and later both excitatory and inhibitory input. In this model, postsynaptic potentials are fully synchronous for the preferred direction and maximally dispersed in time for the null direction. Further, any inhibitory inputs lag excitatory inputs, as Priebe and Ferster have observed (2005). At any level of input strength, the selectivity is weak when only excitatory inputs are considered. The inclusion of inhibition significantly strengthens selectivity, and this selectivity is preserved over a wide range of background noise levels and for short stimulus durations. We conclude that inhibition likely plays an essential role in the mechanism underlying direction selectivity.

  6. Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

    PubMed Central

    Boutemedjet, Ayoub; Deng, Chenwei; Zhao, Baojun

    2016-01-01

    In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above. PMID:27834893

  7. Motion-based morphological segmentation of wildlife video

    NASA Astrophysics Data System (ADS)

    Thomas, Naveen M.; Canagarajah, Nishan

    2005-03-01

    Segmentation of objects in a video sequence is a key stage in most content-based retrieval systems. By further analysing the behaviour of these objects, it is possible to extract semantic information suitable for higher level content analysis. Since interesting content in a video is usually provided by moving objects, motion is a key feature to be used for pre content analysis segmentation. A motion based segmentation algorithm is presented in this paper that is both efficient and robust. The algorithm is also robust to the type of camera motion. The framework presented consists of three stages. These are the motion estimation stage, foreground detection stage and the refinement stage. An iteration of the first two stages, adaptively altering the motion estimation parameters each time, results in a joint segmentation and motion estimation approach that is extremely fast and accurate. Two dimensional histograms are used as a tool to carry out the foreground detection. The last stage uses morphological approaches as well as a prediction of foreground regions in future frames to further refine the segmentation. In this paper, results obtained from traditional approaches are compared with that of the proposed framework in the wildlife domain.

  8. PROPER MOTIONS OF THE ARCHES CLUSTER WITH KECK LASER GUIDE STAR ADAPTIVE OPTICS: THE FIRST KINEMATIC MASS MEASUREMENT OF THE ARCHES

    SciTech Connect

    Clarkson, W. I.; Ghez, A. M.; Morris, M. R.; Yelda, S.; Lu, J. R.; Stolte, A.; McCrady, N.; Do, T.

    2012-06-01

    We report the first detection of the intrinsic velocity dispersion of the Arches cluster-a young ({approx}2 Myr), massive (10{sup 4} M{sub Sun }) starburst cluster located only 26 pc in projection from the Galactic center. This was accomplished using proper motion measurements within the central 10'' Multiplication-Sign 10'' of the cluster, obtained with the laser guide star adaptive optics system at Keck Observatory over a three-year time baseline (2006-2009). This uniform data set results in proper motion measurements that are improved by a factor {approx}5 over previous measurements from heterogeneous instruments. By careful, simultaneous accounting of the cluster and field contaminant distributions as well as the possible sources of measurement uncertainties, we estimate the internal velocity dispersion to be 0.15 {+-} 0.01 mas yr{sup -1}, which corresponds to 5.4 {+-} 0.4 km s{sup -1} at a distance of 8.4 kpc. Projecting a simple model for the cluster onto the sky to compare with our proper motion data set, in conjunction with surface density data, we estimate the total present-day mass of the cluster to be M(r < 1.0 pc) = 1.5{sup +0.74}{sub -0.60} Multiplication-Sign 10{sup 4} M{sub Sun }. The mass in stars observed within a cylinder of radius R (for comparison to photometric estimates) is found to be M(R < 0.4 pc) = 0.90{sup +0.40}{sub -0.35} Multiplication-Sign 10{sup 4} M{sub Sun} at formal 3{sigma} confidence. This mass measurement is free from assumptions about the mass function of the cluster, and thus may be used to check mass estimates from photometry and simulation. Photometric mass estimates assuming an initially Salpeter mass function ({Gamma}{sub 0} = 1.35, or {Gamma} {approx} 1.0 at present, where dN/d(log M){proportional_to}M{sup {Gamma}}) suggest a total cluster mass M{sub cl} {approx} (4-6) Multiplication-Sign 10{sup 4} M{sub Sun} and projected mass ({approx} 2 {<=} M(R < 0.4 pc) {<=} 3) Multiplication-Sign 10{sup 4} M{sub Sun }. Photometric

  9. Chaotic satellite attitude control by adaptive approach

    NASA Astrophysics Data System (ADS)

    Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping

    2014-06-01

    In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.

  10. Pixel-wise Motion Detection in Persistent Aerial Video Surveillance

    SciTech Connect

    Vesom, G

    2012-03-23

    In ground stabilized WAMI, stable objects with depth appear to have precessive motion due to sensor movement alongside objects undergoing true, independent motion in the scene. Computational objective is to disambiguate independent and structural motion in WAMI efficiently and robustly.

  11. Mechanisms of mutational robustness in transcriptional regulation

    PubMed Central

    Payne, Joshua L.; Wagner, Andreas

    2015-01-01

    Robustness is the invariance of a phenotype in the face of environmental or genetic change. The phenotypes produced by transcriptional regulatory circuits are gene expression patterns that are to some extent robust to mutations. Here we review several causes of this robustness. They include robustness of individual transcription factor binding sites, homotypic clusters of such sites, redundant enhancers, transcription factors, redundant transcription factors, and the wiring of transcriptional regulatory circuits. Such robustness can either be an adaptation by itself, a byproduct of other adaptations, or the result of biophysical principles and non-adaptive forces of genome evolution. The potential consequences of such robustness include complex regulatory network topologies that arise through neutral evolution, as well as cryptic variation, i.e., genotypic divergence without phenotypic divergence. On the longest evolutionary timescales, the robustness of transcriptional regulation has helped shape life as we know it, by facilitating evolutionary innovations that helped organisms such as flowering plants and vertebrates diversify. PMID:26579194

  12. Recursive architecture for large-scale adaptive system

    NASA Astrophysics Data System (ADS)

    Hanahara, Kazuyuki; Sugiyama, Yoshihiko

    1994-09-01

    'Large scale' is one of major trends in the research and development of recent engineering, especially in the field of aerospace structural system. This term expresses the large scale of an artifact in general, however, it also implies the large number of the components which make up the artifact in usual. Considering a large scale system which is especially used in remote space or deep-sea, such a system should be adaptive as well as robust by itself, because its control as well as maintenance by human operators are not easy due to the remoteness. An approach to realizing this large scale, adaptive and robust system is to build the system as an assemblage of components which are respectively adaptive by themselves. In this case, the robustness of the system can be achieved by using a large number of such components and suitable adaptation as well as maintenance strategies. Such a system gathers many research's interest and their studies such as decentralized motion control, configurating algorithm and characteristics of structural elements are reported. In this article, a recursive architecture concept is developed and discussed towards the realization of large scale system which consists of a number of uniform adaptive components. We propose an adaptation strategy based on the architecture and its implementation by means of hierarchically connected processing units. The robustness and the restoration from degeneration of the processing unit are also discussed. Two- and three-dimensional adaptive truss structures are conceptually designed based on the recursive architecture.

  13. Objects tracking with adaptive correlation filters and Kalman filtering

    NASA Astrophysics Data System (ADS)

    Ontiveros-Gallardo, Sergio E.; Kober, Vitaly

    2015-09-01

    Object tracking is commonly used for applications such as video surveillance, motion based recognition, and vehicle navigation. In this work, a tracking system using adaptive correlation filters and robust Kalman prediction of target locations is proposed. Tracking is performed by means of multiple object detections in reduced frame areas. A bank of filters is designed from multiple views of a target using synthetic discriminant functions. An adaptive approach is used to improve discrimination capability of the synthesized filters adapting them to multiple types of backgrounds. With the help of computer simulation, the performance of the proposed algorithm is evaluated in terms of detection efficiency and accuracy of object tracking.

  14. Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

    PubMed

    Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

    2014-09-01

    This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations.

  15. Segmentation based on motion: an incremental approach using temporal Kalman filtering

    NASA Astrophysics Data System (ADS)

    Germain, Florence; Baudois, Daniel

    1993-06-01

    There is an increasing interest for image motion analysis, driven by several application fields ranging from dynamic scene analysis, up to image encoding for transmission purposes. In the context of scene analysis, the image motion information is of crucial help for segmentation and qualitative interpretation. In the case of unstructured, inhomogeneous images, motion information is carried by the spatio-temporal variations of the light intensity function. The apparent distribution inferred from this information is a dense vector field, called optical flow. Assuming the spatial continuity of the field to be estimated, a local determination of optical flow is possible. The main difficulty lies in the handling of motion discontinuities. Usually, the localization of motion frontiers is handled as a binary problem, and thus leads to instabilities during the estimation process. We propose an incremental process, evaluating the optical flow from a sequence of images, using temporal Kalman filtering. Our approach is based on a continuous handling of motion frontiers. The evolution model acts as a temporal low band filter on the estimated field. To cope with motion discontinuities, the filter is continuously adapted according to local motion homogeneity, via the covariance of the model noise. The result is a progressive cancelation of temporal regularization in the neighborhood of motion frontiers, allowing a better convergence of the filter in case of such a discontinuity. Such a continuous handling of motion frontiers leads to a great robustness in the estimation process.

  16. Assessing the robustness of adaptation decisions in river flood defences to uncertainty in climate impact analysis: A case study on the River Suir, Ireland

    NASA Astrophysics Data System (ADS)

    Murphy, N.; Murphy, C.

    2009-12-01

    Climate change presents a challenging environment for policy makers and planners as future climate projections are fraught with uncertainty. From the formulation of emissions scenarios, through to the output from Global Climate Models to the regional and then the local scale, uncertainty propagates and increases leading to a cascade of uncertainty (Jones, 2001). The level of flood defences for rivers in Ireland has been built to withstand the 1 in 100 year event based on the historic record. However, stream flow due to climate change is likely to increase by 20% in winter by mid century. The Office of Public Works has therefore revised their projections by adding 20% to the 1 in 100 year event as a design feature of their new flood defences. This poster presents a sensitivity analysis of how various aspects of the climate impact assessment affect the revised level of the 1 in 100 year flood. The River Suir is used as a case study. This poster aims to quantify how different aspects of climate impact assessment uncertainty (GCM, Emissions scenario, impact model) affect the revised level of the 1 in 100 year flood and evaluates if the design of flood defences remains robust to the this uncertainty. Authors. Nuala Murphy Conor Murphy

  17. Real-time detection of small and dim moving objects in IR video sequences using a robust background estimator and a noise-adaptive double thresholding

    NASA Astrophysics Data System (ADS)

    Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

    2016-10-01

    We developed an algorithm for automatically detecting small and poorly contrasted (dim) moving objects in real-time, within video sequences acquired through a steady infrared camera. The algorithm is suitable for different situations since it is independent of the background characteristics and of changes in illumination. Unlike other solutions, small objects of any size (up to single-pixel), either hotter or colder than the background, can be successfully detected. The algorithm is based on accurately estimating the background at the pixel level and then rejecting it. A novel approach permits background estimation to be robust to changes in the scene illumination and to noise, and not to be biased by the transit of moving objects. Care was taken in avoiding computationally costly procedures, in order to ensure the real-time performance even using low-cost hardware. The algorithm was tested on a dataset of 12 video sequences acquired in different conditions, providing promising results in terms of detection rate and false alarm rate, independently of background and objects characteristics. In addition, the detection map was produced frame by frame in real-time, using cheap commercial hardware. The algorithm is particularly suitable for applications in the fields of video-surveillance and computer vision. Its reliability and speed permit it to be used also in critical situations, like in search and rescue, defence and disaster monitoring.

  18. Object localization using adaptive feature selection

    NASA Astrophysics Data System (ADS)

    Hwang, S. Youngkyoo; Kim, Jungbae; Lee, Seongdeok

    2009-01-01

    'Fast and robust' are the most beautiful keywords in computer vision. Unfortunately they are in trade-off relationship. We present a method to have one's cake and eat it using adaptive feature selections. Our chief insight is that it compares reference patterns to query patterns, so that it selects smartly more important and useful features to find target. The probabilities of pixels in the query to belong to the target are calculated from importancy of features. Our framework has three distinct advantages: 1 - It saves computational cost dramatically to the conventional approach. This framework makes it possible to find location of an object in real-time. 2 - It can smartly select robust features of a reference pattern as adapting to a query pattern. 3- It has high flexibility on any feature. It doesn't matter which feature you may use. Lots of color space, texture, motion features and other features can fit perfectly only if the features meet histogram criteria.

  19. On Motion Planning and Control of Multi-Link Lightweight Robotic Manipulators

    NASA Technical Reports Server (NTRS)

    Cetinkunt, Sabri

    1987-01-01

    A general gross and fine motion planning and control strategy is needed for lightweight robotic manipulator applications such as painting, welding, material handling, surface finishing, and spacecraft servicing. The control problem of lightweight manipulators is to perform fast, accurate, and robust motions despite the payload variations, structural flexibility, and other environmental disturbances. Performance of the rigid manipulator model based computed torque and decoupled joint control methods are determined and simulated for the counterpart flexible manipulators. A counterpart flexible manipulator is defined as a manipulator which has structural flexibility, in addition to having the same inertial, geometric, and actuation properties of a given rigid manipulator. An adaptive model following control (AMFC) algorithm is developed to improve the performance in speed, accuracy, and robustness. It is found that the AMFC improves the speed performance by a factor of two over the conventional non-adaptive control methods for given accuracy requirements while proving to be more robust with respect to payload variations. Yet there are clear limitations on the performance of AMFC alone as well, which are imposed by the arm flexibility. In the search to further improve speed performance while providing a desired accuracy and robustness, a combined control strategy is developed. Furthermore, the problem of switching from one control structure to another during the motion and implementation aspects of combined control are discussed.

  20. Optimal Throughput and Self-adaptability of Robust Real-Time IEEE 802.15.4 MAC for AMI Mesh Network

    NASA Astrophysics Data System (ADS)

    Shabani, Hikma; Mohamud Ahmed, Musse; Khan, Sheroz; Hameed, Shahab Ahmed; Hadi Habaebi, Mohamed

    2013-12-01

    A smart grid refers to a modernization of the electricity system that brings intelligence, reliability, efficiency and optimality to the power grid. To provide an automated and widely distributed energy delivery, the smart grid will be branded by a two-way flow of electricity and information system between energy suppliers and their customers. Thus, the smart grid is a power grid that integrates data communication networks which provide the collected and analysed data at all levels in real time. Therefore, the performance of communication systems is so vital for the success of smart grid. Merit to the ZigBee/IEEE802.15.4std low cost, low power, low data rate, short range, simplicity and free licensed spectrum that makes wireless sensor networks (WSNs) the most suitable wireless technology for smart grid applications. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In order to improve the performance of communication systems, this paper proposes an optimal throughput and self-adaptability of ZigBee/IEEE802.15.4std for smart grid.

  1. Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

    SciTech Connect

    Schmidt, Matthew Grzetic, Shelby; Lo, Joseph Y.; Lutzky, Carly; Brizel, David M.; Das, Shiva K.

    2015-08-15

    Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention

  2. How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

    NASA Astrophysics Data System (ADS)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2015-04-01

    In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the

  3. Development of a frameless stereotactic radiosurgery system based on real-time 6D position monitoring and adaptive head motion compensation

    NASA Astrophysics Data System (ADS)

    Wiersma, Rodney D.; Wen, Zhifei; Sadinski, Meredith; Farrey, Karl; Yenice, Kamil M.

    2010-01-01

    Stereotactic radiosurgery delivers radiation with great spatial accuracy. To achieve sub-millimeter accuracy for intracranial SRS, a head ring is rigidly fixated to the skull to create a fixed reference. For some patients, the invasiveness of the ring can be highly uncomfortable and not well tolerated. In addition, placing and removing the ring requires special expertise from a neurosurgeon, and patient setup time for SRS can often be long. To reduce the invasiveness, hardware limitations and setup time, we are developing a system for performing accurate head positioning without the use of a head ring. The proposed method uses real-time 6D optical position feedback for turning on and off the treatment beam (gating) and guiding a motor-controlled 3D head motion compensation stage. The setup consists of a central control computer, an optical patient motion tracking system and a 3D motion compensation stage attached to the front of the LINAC couch. A styrofoam head cast was custom-built for patient support and was mounted on the compensation stage. The motion feedback of the markers was processed by the control computer, and the resulting motion of the target was calculated using a rigid body model. If the target deviated beyond a preset position of 0.2 mm, an automatic position correction was performed with stepper motors to adjust the head position via the couch mount motion platform. In the event the target deviated more than 1 mm, a safety relay switch was activated and the treatment beam was turned off. The feasibility of the concept was tested using five healthy volunteers. Head motion data were acquired with and without the use of motion compensation over treatment times of 15 min. On average, test subjects exceeded the 0.5 mm tolerance 86% of the time and the 1.0 mm tolerance 45% of the time without motion correction. With correction, this percentage was reduced to 5% and 2% for the 0.5 mm and 1.0 mm tolerances, respectively.

  4. Robust Hitting with Dynamics Shaping

    NASA Astrophysics Data System (ADS)

    Yashima, Masahito; Yamawaki, Tasuku

    The present paper proposes the trajectory planning based on “the dynamics shaping” for a redundant robotic arm to hit a target robustly toward the desired direction, of which the concept is to shape the robot dynamics appropriately by changing its posture in order to achieve the robust motion. The positional error of the end-effector caused by unknown disturbances converges onto near the singular vector corresponding to its maximum singular value of the output controllability matrix of the robotic arm. Therefore, if we can control the direction of the singular vector by applying the dynamics shaping, we will be able to control the direction of the positional error of the end-effector caused by unknown disturbances. We propose a novel trajectory planning based on the dynamics shaping and verify numerically and experimentally that the robotic arm can robustly hit the target toward the desired direction with a simple open-loop control system even though the disturbance is applied.

  5. Motion Alters Color Appearance

    PubMed Central

    Hong, Sang-Wook; Kang, Min-Suk

    2016-01-01

    Chromatic induction compellingly demonstrates that chromatic context as well as spectral lights reflected from an object determines its color appearance. Here, we show that when one colored object moves around an identical stationary object, the perceived saturation of the stationary object decreases dramatically whereas the saturation of the moving object increases. These color appearance shifts in the opposite directions suggest that normalization induced by the object’s motion may mediate the shift in color appearance. We ruled out other plausible alternatives such as local adaptation, attention, and transient neural responses that could explain the color shift without assuming interaction between color and motion processing. These results demonstrate that the motion of an object affects both its own color appearance and the color appearance of a nearby object, suggesting a tight coupling between color and motion processing. PMID:27824098

  6. Plate motion

    SciTech Connect

    Gordon, R.G. )

    1991-01-01

    The motion of tectonic plates on the earth is characterized in a critical review of U.S. research from the period 1987-1990. Topics addressed include the NUVEL-1 global model of current plate motions, diffuse plate boundaries and the oceanic lithosphere, the relation between plate motions and distributed deformations, accelerations and the steadiness of plate motions, the distribution of current Pacific-North America motion across western North America and its margin, plate reconstructions and their uncertainties, hotspots, and plate dynamics. A comprehensive bibliography is provided. 126 refs.

  7. Alpha motion based on a motion detector, but not on the Müller-Lyer illusion

    NASA Astrophysics Data System (ADS)

    Suzuki, Masahiro

    2014-07-01

    This study examined the mechanism of alpha motion, the apparent motion of the Müller-Lyer figure's shaft that occurs when the arrowheads and arrow tails are alternately presented. The following facts were found: (a) reduced exposure duration decreased the amount of alpha motion, and this phenomenon was not explainable by the amount of the Müller-Lyer illusion; (b) the motion aftereffect occurred after adaptation to alpha motion; (c) occurrence of alpha motion became difficult when the temporal frequency increased, and this characteristic of alpha motion was similar to the characteristic of a motion detector that motion detection became difficult when the temporal frequency increased from the optimal frequency. These findings indicated that alpha motion occurs on the basis of a motion detector but not on the Müller-Lyer illusion, and that the mechanism of alpha motion is the same as that of general motion perception.

  8. Robust automated knowledge capture.

    SciTech Connect

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  9. Autoadaptive motion modelling for MR-based respiratory motion estimation.

    PubMed

    Baumgartner, Christian F; Kolbitsch, Christoph; McClelland, Jamie R; Rueckert, Daniel; King, Andrew P

    2017-01-01

    Respiratory motion poses significant challenges in image-guided interventions. In emerging treatments such as MR-guided HIFU or MR-guided radiotherapy, it may cause significant misalignments between interventional road maps obtained pre-procedure and the anatomy during the treatment, and may affect intra-procedural imaging such as MR-thermometry. Patient specific respiratory motion models provide a solution to this problem. They establish a correspondence between the patient motion and simpler surrogate data which can be acquired easily during the treatment. Patient motion can then be estimated during the treatment by acquiring only the simpler surrogate data. In the majority of classical motion modelling approaches once the correspondence between the surrogate data and the patient motion is established it cannot be changed unless the model is recalibrated. However, breathing patterns are known to significantly change in the time frame of MR-guided interventions. Thus, the classical motion modelling approach may yield inaccurate motion estimations when the relation between the motion and the surrogate data changes over the duration of the treatment and frequent recalibration may not be feasible. We propose a novel methodology for motion modelling which has the ability to automatically adapt to new breathing patterns. This is achieved by choosing the surrogate data in such a way that it can be used to estimate the current motion in 3D as well as to update the motion model. In particular, in this work, we use 2D MR slices from different slice positions to build as well as to apply the motion model. We implemented such an autoadaptive motion model by extending our previous work on manifold alignment. We demonstrate a proof-of-principle of the proposed technique on cardiac gated data of the thorax and evaluate its adaptive behaviour on realistic synthetic data containing two breathing types generated from 6 volunteers, and real data from 4 volunteers. On synthetic data

  10. Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

    PubMed

    Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

    2010-09-01

    This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

  11. Space motion sickness

    NASA Technical Reports Server (NTRS)

    Homick, J. L.

    1979-01-01

    Research on the etiology, prediction, treatment and prevention of space motion sickness, designed to minimize the impact of this syndrome which was experienced frequently and with severity by individuals on the Skylab missions, on Space Shuttle crews is reviewed. Theories of the cause of space motion sickness currently under investigation by NASA include sensory conflict, which argues that motion sickness symptoms result from a mismatch between the total pattern of information from the spatial senses and that stored from previous experiences, and fluid shift, based upon the redistribution of bodily fluids that occurs upon continued exposure to weightlessness. Attempts are underway to correlate space motion sickness susceptibility to different provocative environments, vestibular and nonvestibular responses, and the rate of acquisition and length of retention of sensory adaptation. Space motion sickness countermeasures under investigation include various drug combinations, of which the equal combination of promethazine and ephedrine has been found to be as effective as the scopolomine and dexedrine combination, and vestibular adaptation and biofeedback training and autogenic therapy.

  12. Adaptive and Robust Resource Allocation and Scheduling

    DTIC Science & Technology

    2010-05-03

    HOK nvjrnocn OT. vvunr. uim l NUMDUI /. rtni-unminiu UHUHNUA I IUN NMivttis) HNU Muuneosicoi Brown University Office of Research...telecommunication technologies which enables entreprises and organizations to track their operations in real-time us- ing technologies such as GPS...RFIDs, sensors, and high- performance networks. The ubiquity of telecommunication technologies led to a paradigm shift in business processes

  13. Robust Adaptive Control of Multivariable Nonlinear Systems

    DTIC Science & Technology

    2011-03-28

    Systems: Challenge Problem Integration and NASA s Integrated Resilient Aircraft Control . We also revealed some similarities with the disturbance ... observer (DOB) controllers and identified the main features in the difference between them. The key feature of this difference is that the estimation loop

  14. TU-AB-303-06: Does Online Adaptive Radiation Therapy Mean Zero Margin for Intermediate-Risk Prostate Cancer? An Intra-Fractional Seminal Vesicles Motion Analysis

    SciTech Connect

    Sheng, Y; Li, T; Lee, W; Yin, F; Wu, Q

    2015-06-15

    Purpose: To provide benchmark for seminal vesicles (SVs) margin selection to account for intra-fractional motion; and to investigate the effectiveness of two motion surrogates in predicting intra-fractional SV underdosage. Methods: 9 prostate SBRT patients were studied; each has five pairs of pre-treatment and post-treatment cone-beam CTs (CBCTs). Each pair of CBCTs was registered based on fiducial markers in the prostate. To provide “ground truth” for coverage evaluation, all pre-treatment SVs were expanded with isotropic margin of 1,2,3,5 and 8mm, and their overlap with post-treatment SVs were used to quantify intra-fractional coverage. Two commonly used motion surrogates, the center-of-mass (COM) and the border of contour (the most distal points in SI/AP/LR directions) were evaluated using Receiver-Operating Characteristic (ROC) analyses for predicting SV underdosage due to intra-fractional motion. Action threshold of determining underdosage for each surrogate was calculated by selecting the optimal balancing between sensitivity and specificity. For comparison, margin for each surrogate was also calculated based on traditional margin recipe. Results: 90% post-treatment SV coverage can be achieved in 47%, 82%, 91%, 98% and 98% fractions for 1,2,3,5 and 8mm margins. 3mm margin ensured the 90% intra-fractional SV coverage in 90% fractions when prostate was aligned. The ROC analysis indicated the AUC for COM and border were 0.88 and 0.72. The underdosage threshold was 2.9mm for COM and 4.1mm for border. The Van Herk’s margin recipe recommended 0.5, 0 and 1.8mm margin in LR, AP and SI direction based on COM and for border, the corresponding margin was 2.1, 4.5 and 3mm. Conclusion: 3mm isotropic margin is the minimum required to mitigate the intra-fractional SV motion when prostate is aligned. ROC analysis reveals that both COM and border are acceptable predictors for SV underdosage with 2.9mm and 4.1mm action threshold. Traditional margin calculation is less

  15. Brownian motion

    NASA Astrophysics Data System (ADS)

    Lavenda, B. H.

    1985-02-01

    Brownian motion, the doubly random motion of small particles suspended in a liquid due to molecular collisions, and its implications and applications in the history of modern science are discussed. Topics examined include probabilistic phenomena, the kinetic theory of gases, Einstein's atomic theory of Brownian motion, particle displacement, diffusion measurements, the determination of the mass of the atom and of Avogadro's number, the statistical mechanics of thermodynamics, nonequilibrium systems, Langevin's equation of motion, time-reversed evolution, mathematical analogies, and applications in economics and radio navigation. Diagrams and drawings are provided.

  16. Analysis and Synthesis of Robust Data Structures

    DTIC Science & Technology

    1990-08-01

    1.3.2 Multiversion Software. .. .. .. .. .. .... .. ... .. ...... 5 1.3.3 Robust Data Structure .. .. .. .. .. .. .. .. .. ... .. ..... 6 1.4...context are 0 multiversion software, which is an adaptation oi N-modulo redundancy (NMR) tech- nique. * recovery blocks, which is an adaptation of...implementations using these features for such a hybrid approach. 1.3.2 Multiversion Software Avizienis [AC77] was the first to adapt NMR technique into

  17. Dynamic optimal sliding-mode control for six-DOF follow-up robust tracking of active satellite

    NASA Astrophysics Data System (ADS)

    Yuankai, Li; Zhongliang, Jing; Shiqiang, Hu

    2011-09-01

    This paper presents a six-DOF follow-up tracking scheme for active target satellite tracking. The scheme is mainly composed of a robust tracking algorithm and a six-DOF follow-up control law. Firstly, a relative motion model using osculating reference orbit (ORO) is built and applied to the redundant adaptive robust extended Kalman filter (RAREKF) to form an ORO-based robust method as the tracking algorithm. Then, a dynamic optimal sliding-mode control (DOSMC) with dynamic optimal sliding surface (DOSS) is proposed to design the six-DOF follow-up control of both relative orbit and chaser attitude. The scheme structure is also discussed in the paper. Three cases are simulated to illustrate the advantage of ORO-based RAREKF and DOSMC and to verify the effectiveness of the presented follow-up tracking scheme.

  18. Adaptive controllability of omnidirectional vehicle over unpredictable terrain

    NASA Astrophysics Data System (ADS)

    Cheok, Ka C.; Radovnikovich, Micho; Hudas, Gregory R.; Overholt, James L.; Fleck, Paul

    2009-05-01

    In this paper, the controllability of a Mecanum omnidirectional vehicle (ODV) is investigated. An adaptive drive controller is developed that guides the ODV over irregular and unpredictable driving surfaces. Using sensor fusion with appropriate filtering, the ODV gets an accurate perception of the conditions it encounters and then adapts to them to robustly control its motion. Current applications of Mecanum ODVs are designed for use on smooth, regular driving surfaces, and don't actively detect the characteristics of disturbances in the terrain. The intention of this work is to take advantage of the mobility of ODVs in environments where they weren't originally intended to be used. The methods proposed in this paper were implemented in hardware on an ODV. Experimental results did not perform as designed due to incorrect assumptions and over-simplification of the system model. Future work will concentrate on developing more robust control schemes to account for the unknown nonlinear dynamics inherent in the system.

  19. Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

    NASA Astrophysics Data System (ADS)

    Carvalho, Schubert R.; Boulic, Ronan; Thalmann, Daniel

    The growth of motion capture systems have contributed to the proliferation of human motion database, mainly because human motion is important in many applications, ranging from games entertainment and films to sports and medicine. However, the captured motions normally attend specific needs. As an effort for adapting and reusing captured human motions in new tasks and environments and improving the animator's work, we present and discuss a new data-driven constraint-based animation system for interactive human motion editing. This method offers the compelling advantage that it provides faster deformations and more natural-looking motion results compared to goal-directed constraint-based methods found in the literature.

  20. Advances in Adaptive Control Methods

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2009-01-01

    This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

  1. Suppressive mechanisms in visual motion processing: from perception to intelligence

    PubMed Central

    Tadin, Duje

    2015-01-01

    Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and those with schizophrenia—a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores. PMID:26299386

  2. Circular Motion.

    ERIC Educational Resources Information Center

    Lee, Paul D.

    1995-01-01

    Provides a period-long activity using battery powered cars rolling in a circular motion on a tile floor. Students measure the time and distance as the car moves to derive the equation for centripetal acceleration. (MVL)

  3. Environmental change makes robust ecological networks fragile

    PubMed Central

    Strona, Giovanni; Lafferty, Kevin D.

    2016-01-01

    Complex ecological networks appear robust to primary extinctions, possibly due to consumers' tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems. PMID:27511722

  4. Environmental change makes robust ecological networks fragile

    USGS Publications Warehouse

    Strona, Giovanni; Lafferty, Kevin D.

    2016-01-01

    Complex ecological networks appear robust to primary extinctions, possibly due to consumers’ tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems.

  5. Robust Multiobjective Controllability of Complex Neuronal Networks.

    PubMed

    Tang, Yang; Gao, Huijun; Du, Wei; Lu, Jianquan; Vasilakos, Athanasios V; Kurths, Jurgen

    2016-01-01

    This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework for robust multiobjective controllability is proposed by introducing interval uncertainties and optimization algorithms. By appropriate definitions of robust multiobjective controllability, a robust nondominated sorting adaptive differential evolution (NSJaDE) is presented by means of the nondominated sorting mechanism and the adaptive differential evolution (JaDE). The simulation experimental results illustrate the satisfactory performance of NSJaDE for robust multiobjective controllability, in comparison with six statistical methods and two multiobjective evolutionary algorithms (MOEAs): nondominated sorting genetic algorithms II (NSGA-II) and nondominated sorting composite differential evolution. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affects the controllability of neuronal networks. We also unveil that driver nodes play a more drastic role than control gains in robust controllability. The developed NSJaDE and obtained results will shed light on the understanding of robustness in controlling realistic complex networks such as transportation networks, power grid networks, biological networks, etc.

  6. Heart motion uncertainty compensation prediction method for robot assisted beating heart surgery - Master-slave Kalman Filters approach.

    PubMed

    Liang, Fan; Yu, Yang; Cui, Shigang; Zhao, Li; Wu, Xingli

    2014-05-01

    Robot Assisted Coronary Artery Bypass Graft (CABG) allows the heart keep beating in the surgery by actively eliminating the relative motion between point of interest (POI) on the heart surface and surgical tool. The inherited nonlinear and diverse nature of beating heart motion gives a huge obstacle for the robot to meet the demanding tracking control requirements. In this paper, we novelty propose a Master-slave Kalman Filter based on beating heart motion Nonlinear Adaptive Prediction (NAP) algorithm. In the study, we describe the beating heart motion as the combination of nonlinearity relating mathematics part and uncertainty relating non-mathematics part. Specifically, first, we model the nonlinearity of the heart motion via quadratic modulated sinusoids and estimate it by a Master Kalman Filter. Second, we involve the uncertainty heart motion by adaptively change the covariance of the process noise through the slave Kalman Filter. We conduct comparative experiments to evaluate the proposed approach with four distinguished datasets. The results indicate that the new approach reduces prediction errors by at least 30 μm. Moreover, the new approach performs well in robustness test, in which two kinds of arrhythmia datasets from MIT-BIH arrhythmia database are assessed.

  7. Improved shear wave motion detection using coded excitation for transient elastography.

    PubMed

    He, Xiao-Nian; Diao, Xian-Fen; Lin, Hao-Ming; Zhang, Xin-Yu; Shen, Yuan-Yuan; Chen, Si-Ping; Qin, Zheng-Di; Chen, Xin

    2017-03-15

    Transient elastography (TE) is well adapted for use in studying liver elasticity. However, because the shear wave motion signal is extracted from the ultrasound signal, the weak ultrasound signal can significantly deteriorate the shear wave motion tracking process and make it challenging to detect the shear wave motion in a severe noise environment, such as within deep tissues and within obese patients. This paper, therefore, investigated the feasibility of implementing coded excitation in TE for shear wave detection, with the hypothesis that coded ultrasound signals can provide robustness to weak ultrasound signals compared with traditional short pulse. The Barker 7, Barker 13, and short pulse were used for detecting the shear wave in the TE application. Two phantom experiments and one in vitro liver experiment were done to explore the performances of the coded excitation in TE measurement. The results show that both coded pulses outperform the short pulse by providing superior shear wave signal-to-noise ratios (SNR), robust shear wave speed measurement, and higher penetration intensity. In conclusion, this study proved the feasibility of applying coded excitation in shear wave detection for TE application. The proposed method has the potential to facilitate robust shear elasticity measurements of tissue.

  8. Improved shear wave motion detection using coded excitation for transient elastography

    PubMed Central

    He, Xiao-Nian; Diao, Xian-Fen; Lin, Hao-Ming; Zhang, Xin-Yu; Shen, Yuan-Yuan; Chen, Si-Ping; Qin, Zheng-Di; Chen, Xin

    2017-01-01

    Transient elastography (TE) is well adapted for use in studying liver elasticity. However, because the shear wave motion signal is extracted from the ultrasound signal, the weak ultrasound signal can significantly deteriorate the shear wave motion tracking process and make it challenging to detect the shear wave motion in a severe noise environment, such as within deep tissues and within obese patients. This paper, therefore, investigated the feasibility of implementing coded excitation in TE for shear wave detection, with the hypothesis that coded ultrasound signals can provide robustness to weak ultrasound signals compared with traditional short pulse. The Barker 7, Barker 13, and short pulse were used for detecting the shear wave in the TE application. Two phantom experiments and one in vitro liver experiment were done to explore the performances of the coded excitation in TE measurement. The results show that both coded pulses outperform the short pulse by providing superior shear wave signal-to-noise ratios (SNR), robust shear wave speed measurement, and higher penetration intensity. In conclusion, this study proved the feasibility of applying coded excitation in shear wave detection for TE application. The proposed method has the potential to facilitate robust shear elasticity measurements of tissue. PMID:28295027

  9. Robust flight control of rotorcraft

    NASA Astrophysics Data System (ADS)

    Pechner, Adam Daniel

    With recent design improvement in fixed wing aircraft, there has been a considerable interest in the design of robust flight control systems to compensate for the inherent instability necessary to achieve desired performance. Such systems are designed for maximum available retention of stability and performance in the presence of significant vehicle damage or system failure. The rotorcraft industry has shown similar interest in adopting these reconfigurable flight control schemes specifically because of their ability to reject disturbance inputs and provide a significant amount of robustness for all but the most catastrophic of situations. The research summarized herein focuses on the extension of the pseudo-sliding mode control design procedure interpreted in the frequency domain. Application of the technique is employed and simulated on two well known helicopters, a simplified model of a hovering Sikorsky S-61 and the military's Black Hawk UH-60A also produced by Sikorsky. The Sikorsky helicopter model details are readily available and was chosen because it can be limited to pitch and roll motion reducing the number of degrees of freedom and yet contains two degrees of freedom, which is the minimum requirement in proving the validity of the pseudo-sliding control technique. The full order model of a hovering Black Hawk system was included both as a comparison to the S-61 helicopter design system and as a means to demonstrate the scaleability and effectiveness of the control technique on sophisticated systems where design robustness is of critical concern.

  10. Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients †

    PubMed Central

    Fidan, Barış; Umay, Ilknur

    2015-01-01

    Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. PMID:26690441

  11. Dynamic Engagement of Human Motion Detectors across Space–Time Coordinates

    PubMed Central

    2014-01-01

    Motion detection is a fundamental property of the visual system. The gold standard for studying and understanding this function is the motion energy model. This computational tool relies on spatiotemporally selective filters that capture the change in spatial position over time afforded by moving objects. Although the filters are defined in space–time, their human counterparts have never been studied in their native spatiotemporal space but rather in the corresponding frequency domain. When this frequency description is back-projected to spatiotemporal description, not all characteristics of the underlying process are retained, leaving open the possibility that important properties of human motion detection may have remained unexplored. We derived descriptors of motion detectors in native space–time, and discovered a large unexpected dynamic structure involving a >2× change in detector amplitude over the first ∼100 ms. This property is not predicted by the energy model, generalizes across the visual field, and is robust to adaptation; however, it is silenced by surround inhibition and is contrast dependent. We account for all results by extending the motion energy model to incorporate a small network that supports feedforward spread of activation along the motion trajectory via a simple gain-control circuit. PMID:24948800

  12. Robust Software Architecture for Robots

    NASA Technical Reports Server (NTRS)

    Aghazanian, Hrand; Baumgartner, Eric; Garrett, Michael

    2009-01-01

    Robust Real-Time Reconfigurable Robotics Software Architecture (R4SA) is the name of both a software architecture and software that embodies the architecture. The architecture was conceived in the spirit of current practice in designing modular, hard, realtime aerospace systems. The architecture facilitates the integration of new sensory, motor, and control software modules into the software of a given robotic system. R4SA was developed for initial application aboard exploratory mobile robots on Mars, but is adaptable to terrestrial robotic systems, real-time embedded computing systems in general, and robotic toys.

  13. Brownian Motion.

    ERIC Educational Resources Information Center

    Lavenda, Bernard H.

    1985-01-01

    Explains the phenomenon of Brownian motion, which serves as a mathematical model for random processes. Topics addressed include kinetic theory, Einstein's theory, particle displacement, and others. Points out that observations of the random course of a particle suspended in fluid led to the first accurate measurement of atomic mass. (DH)

  14. Motion Sickness

    MedlinePlus

    ... but it is more common in children, pregnant women, and people taking certain medicines. Motion sickness can start suddenly, with a queasy feeling and cold sweats. It can then lead to dizziness and nausea and vomiting. Your brain senses movement by getting signals from your inner ears, eyes, ...

  15. Motion perception during saccadic eye movements.

    PubMed

    Castet, E; Masson, G S

    2000-02-01

    During rapid eye movements, motion of the stationary world is generally not perceived despite displacement of the whole image on the retina. Here we report that during saccades, human observers sensed visual motion of patterns with low spatial frequency. The effect was greatest when the stimulus was spatiotemporally optimal for motion detection by the magnocellular pathway. Adaptation experiments demonstrated dependence of this intrasaccadic motion percept on activation of direction-selective mechanisms. Even two-dimensional complex motion percepts requiring spatial integration of early motion signals were observed during saccades. These results indicate that the magnocellular pathway functions during saccades, and that only spatiotemporal limitations of visual motion perception are important in suppressing awareness of intrasaccadic motion signals.

  16. Motion correction in MRI of the brain

    PubMed Central

    Godenschweger, F; Kägebein, U; Stucht, D; Yarach, U; Sciarra, A; Yakupov, R; Lüsebrink, F; Schulze, P; Speck, O

    2016-01-01

    Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed. PMID:26864183

  17. Motion correction in MRI of the brain

    NASA Astrophysics Data System (ADS)

    Godenschweger, F.; Kägebein, U.; Stucht, D.; Yarach, U.; Sciarra, A.; Yakupov, R.; Lüsebrink, F.; Schulze, P.; Speck, O.

    2016-03-01

    Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.

  18. Robust models for optic flow coding in natural scenes inspired by insect biology.

    PubMed

    Brinkworth, Russell S A; O'Carroll, David C

    2009-11-01

    The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors.

  19. Quantitative framework for prospective motion correction evaluation

    PubMed Central

    Pannetier, Nicolas; Stavrinos, Theano; Ng, Peter; Herbst, Michael; Zaitsev, Maxim; Young, Karl; Matson, Gerald; Schuff, Norbert

    2014-01-01

    Purpose Establishing a framework to evaluate performances of prospective motion correction (PMC) MRI considering motion variability between MRI scans. Method A framework was developed to obtain quantitative comparisons between different motion correction setups, considering that varying intrinsic motion patterns between acquisitions can induce bias. Intrinsic motion was considered by replaying in a phantom experiment the recorded motion trajectories from subjects. T1-weighted MRI on five volunteers and two different marker fixations (mouth guard and nose bridge fixations) were used to test the framework. Two metrics were investigated to quantify the improvement of the image quality with PMC. Results Motion patterns vary between subjects as well as between repeated scans within a subject. This variability can be approximated by replaying the motion in a distinct phantom experiment and used as a covariate in models comparing motion corrections. We show that considering the intrinsic motion alters the statistical significance in comparing marker fixations. As an example, two marker fixations, a mouth guard and a nose bridge, were evaluated in terms of their effectiveness for PMC. A mouth guard achieved better PMC performance. Conclusion Intrinsic motion patterns can bias comparisons between PMC configurations and must be considered for robust evaluations. A framework for evaluating intrinsic motion patterns in PMC is presented. PMID:25761550

  20. Space motion sickness

    NASA Technical Reports Server (NTRS)

    Vanderploeg, J. M.; Stewart, D. F.; Davis, J. R.

    1986-01-01

    Space motion sickness clinical characteristics, time course, prediction of susceptibility, and effectiveness of countermeasures were evaluated. Although there is wide individual variability, there appear to be typical patterns of symptom development. The duration of symptoms ranges from several hours to four days with the majority of individuals being symptom free by the end of third day. The etiology of this malady remains uncertain but evidence points to reinterpretation of otolith inputs as being a key factor in the response of the neurovestibular system. Prediction of susceptibility and severity remains unsatisfactory. Countermeasures tried include medications, preflight adaptation, and autogenic feedback training. No countermeasure is entirely successful in eliminating or alleviating symptoms.

  1. Endocrine correlates of susceptibility to motion sickness

    NASA Technical Reports Server (NTRS)

    Kohl, R. L.

    1985-01-01

    Motion sickness releases ACTH, epinerphrine, and norepinephrine. The endocrine responses to motion sickness, adaptive responses leading to the resolution of the syndrome, and the way in which antimotion-sickness drugs influence the endocrine responses were studied. Susceptible or insusceptible subjects were administered antimotion-sickness drugs prior to stressful stimulation. Insusceptible subjects displayed more pronounced elevations of ACTH, epinephrine, and norepinephrine after stressful motion. Predrug levels of ACTH were higher in insusceptible subjects (p less than 0.01). Acute blockade of hormone responses to stressful motion or alteration of levels of ACTH by drugs were not correlated with individual susceptibility. No correlation was apparent between epinephrine and ACTH release. These endocrine differences may represent neurochemical markers for susceptibility to motion, stress, or general adaptability, and it may be that the chronic modulation of their levels might be more effective in preventing motion sickness than the acute blockage or stimulation of specific receptors.

  2. [Motion sickness].

    PubMed

    Taillemite, J P; Devaulx, P; Bousquet, F

    1997-01-01

    Motion sickness is a general term covering sea-sickness, car-sickness, air-sickness, and space-sickness. Symptoms can occur when a person is exposed to unfamiliar movement whether real or simulated. Despite progress in the technology and comfort of modern transportation (planes, boats, and overland vehicles), a great number of travelers still experience motion sickness. Bouts are characterized by an initial phase of mild discomfort followed by neurologic and gastro-intestinal manifestations. The delay in onset depends on specific circumstances and individual susceptibility. Attacks are precipitated by conflicting sensory, visual, and vestibular signals but the underlying mechanism is unclear. Most medications used for prevention and treatment (e.g. anticholinergics and antihistamines) induce unwanted sedation. Furthermore no one drug is completely effective or preventive under all conditions.

  3. Motion aftereffect of combined first-order and second-order motion.

    PubMed

    van der Smagt, M J; Verstraten, F A; Vaessen, E B; van Londen, T; van de Grind, W A

    1999-01-01

    When, after prolonged viewing of a moving stimulus, a stationary (test) pattern is presented to an observer, this results in an illusory movement in the direction opposite to the adapting motion. Typically, this motion aftereffect (MAE) does not occur after adaptation to a second-order motion stimulus (i.e. an equiluminous stimulus where the movement is defined by a contrast or texture border, not by a luminance border). However, a MAE of second-order motion is perceived when, instead of a static test pattern, a dynamic test pattern is used. Here, we investigate whether a second-order motion stimulus does affect the MAE on a static test pattern (sMAE), when second-order motion is presented in combination with first-order motion during adaptation. The results show that this is indeed the case. Although the second-order motion stimulus is too weak to produce a convincing sMAE on its own, its influence on the sMAE is of equal strength to that of the first-order motion component, when they are adapted to simultaneously. The results suggest that the perceptual appearance of the sMAE originates from the site where first-order and second-order motion are integrated.

  4. Habituation of visual adaptation

    PubMed Central

    Dong, Xue; Gao, Yi; Lv, Lili; Bao, Min

    2016-01-01

    Our sensory system adjusts its function driven by both shorter-term (e.g. adaptation) and longer-term (e.g. learning) experiences. Most past adaptation literature focuses on short-term adaptation. Only recently researchers have begun to investigate how adaptation changes over a span of days. This question is important, since in real life many environmental changes stretch over multiple days or longer. However, the answer to the question remains largely unclear. Here we addressed this issue by tracking perceptual bias (also known as aftereffect) induced by motion or contrast adaptation across multiple daily adaptation sessions. Aftereffects were measured every day after adaptation, which corresponded to the degree of adaptation on each day. For passively viewed adapters, repeated adaptation attenuated aftereffects. Once adapters were presented with an attentional task, aftereffects could either reduce for easy tasks, or initially show an increase followed by a later decrease for demanding tasks. Quantitative analysis of the decay rates in contrast adaptation showed that repeated exposure of the adapter appeared to be equivalent to adaptation to a weaker stimulus. These results suggest that both attention and a non-attentional habituation-like mechanism jointly determine how adaptation develops across multiple daily sessions. PMID:26739917

  5. An extended framework for adaptive playback-based video summarization

    NASA Astrophysics Data System (ADS)

    Peker, Kadir A.; Divakaran, Ajay

    2003-11-01

    In our previous work, we described an adaptive fast playback framework for video summarization where we changed the playback rate using the motion activity feature so as to maintain a constant "pace." This method provides an effective way of skimming through video, especially when the motion is not too complex and the background is mostly still, such as in surveillance video. In this paper, we present an extended summarization framework that, in addition to motion activity, uses semantic cues such as face or skin color appearance, speech and music detection, or other domain dependent semantically significant events to control the playback rate. The semantic features we use are computationally inexpensive and can be computed in compressed domain, yet are robust, reliable, and have a wide range of applicability across different content types. The presented framework also allows for adaptive summaries based on preference, for example, to include more dramatic vs. action elements, or vice versa. The user can switch at any time between the skimming and the normal playback modes. The continuity of the video is preserved, and complete omission of segments that may be important to the user is avoided by using adaptive fast playback instead of skipping over long segments. The rule-set and the input parameters can be further modified to fit a certain domain or application. Our framework can be used by itself, or as a subsequent presentation stage for a summary produced by any other summarization technique that relies on generating a sub-set of the content.

  6. Robust coding over noisy overcomplete channels.

    PubMed

    Doi, Eizaburo; Balcan, Doru C; Lewicki, Michael S

    2007-02-01

    We address the problem of robust coding in which the signal information should be preserved in spite of intrinsic noise in the representation. We present a theoretical analysis for 1- and 2-D cases and characterize the optimal linear encoder and decoder in the mean-squared error sense. Our analysis allows for an arbitrary number of coding units, thus including both under- and over-complete representations, and provides insights into optimal coding strategies. In particular, we show how the form of the code adapts to the number of coding units and to different data and noise conditions in order to achieve robustness. We also present numerical solutions of robust coding for high-dimensional image data, demonstrating that these codes are substantially more robust than other linear image coding methods such as PCA, ICA, and wavelets.

  7. Robust Critical Point Detection

    SciTech Connect

    Bhatia, Harsh

    2016-07-28

    Robust Critical Point Detection is a software to compute critical points in a 2D or 3D vector field robustly. The software was developed as a part of the author's work at the lab as a Phd student under Livermore Scholar Program (now called Livermore Graduate Scholar Program).

  8. Mechanisms for Robust Cognition

    ERIC Educational Resources Information Center

    Walsh, Matthew M.; Gluck, Kevin A.

    2015-01-01

    To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within…

  9. Robust stability and performance of time-delay control systems.

    PubMed

    Keviczky, L; Bányász, Cs

    2007-04-01

    Most of the optimal and adaptive regulators assume an a priori known time delay. The time-delay mismatch can cause unwanted instability. Influence of this uncertainty is investigated in connection with the required performance and robustness.

  10. Physiologic adaptation to space - Space adaptation syndrome

    NASA Technical Reports Server (NTRS)

    Vanderploeg, J. M.

    1985-01-01

    The adaptive changes of the neurovestibular system to microgravity, which result in space motion sickness (SMS), are studied. A list of symptoms, which range from vomiting to drowsiness, is provided. The two patterns of symptom development, rapid and gradual, and the duration of the symptoms are described. The concept of sensory conflict and rearrangements to explain SMS is being investigated.

  11. Robust Registration of Dynamic Facial Sequences.

    PubMed

    Sariyanidi, Evangelos; Gunes, Hatice; Cavallaro, Andrea

    2017-04-01

    Accurate face registration is a key step for several image analysis applications. However, existing registration methods are prone to temporal drift errors or jitter among consecutive frames. In this paper, we propose an iterative rigid registration framework that estimates the misalignment with trained regressors. The input of the regressors is a robust motion representation that encodes the motion between a misaligned frame and the reference frame(s), and enables reliable performance under non-uniform illumination variations. Drift errors are reduced when the motion representation is computed from multiple reference frames. Furthermore, we use the L2 norm of the representation as a cue for performing coarse-to-fine registration efficiently. Importantly, the framework can identify registration failures and correct them. Experiments show that the proposed approach achieves significantly higher registration accuracy than the state-of-the-art techniques in challenging sequences.

  12. Motion robust PPG-imaging through color channel mapping

    PubMed Central

    Moço, Andreia V.; Stuijk, Sander; de Haan, Gerard

    2016-01-01

    Photoplethysmography (PPG)-imaging is an emerging noninvasive technique that maps spatial blood-volume variations in living tissue with a video camera. In this paper, we clarify how cardiac-related (i.e., ballistocardiographic; BCG) artifacts occur in this imaging modality and address these using algorithms from the remote-PPG literature. Performance is assessed under stationary conditions at the immobilized hand. Our proposal outperforms the state-of-the-art, blood pulsation imaging [Biomed. Opt. Express 5, 3123 (2014)25401026. ], even in our best attempt to create diffused illumination. BCG-artifacts are suppressed to an order of magnitude below PPG-signal strength, which is sufficient to prevent interpretation errors. PMID:27231618

  13. Robustness. [in space systems

    NASA Technical Reports Server (NTRS)

    Ryan, Robert

    1993-01-01

    The concept of rubustness includes design simplicity, component and path redundancy, desensitization to the parameter and environment variations, control of parameter variations, and punctual operations. These characteristics must be traded with functional concepts, materials, and fabrication approach against the criteria of performance, cost, and reliability. The paper describes the robustness design process, which includes the following seven major coherent steps: translation of vision into requirements, definition of the robustness characteristics desired, criteria formulation of required robustness, concept selection, detail design, manufacturing and verification, operations.

  14. Motion Simulator

    NASA Technical Reports Server (NTRS)

    1993-01-01

    MOOG, Inc. supplies hydraulic actuators for the Space Shuttle. When MOOG learned NASA was interested in electric actuators for possible future use, the company designed them with assistance from Marshall Space Flight Center. They also decided to pursue the system's commercial potential. This led to partnership with InterActive Simulation, Inc. for production of cabin flight simulators for museums, expositions, etc. The resulting products, the Magic Motion Simulator 30 Series, are the first electric powered simulators. Movements are computer-guided, including free fall to heighten the sense of moving through space. A projection system provides visual effects, and the 11 speakers of a digital laser based sound system add to the realism. The electric actuators are easier to install, have lower operating costs, noise, heat and staff requirements. The U.S. Space & Rocket Center and several other organizations have purchased the simulators.

  15. Spatially adaptive regularized iterative high-resolution image reconstruction algorithm

    NASA Astrophysics Data System (ADS)

    Lim, Won Bae; Park, Min K.; Kang, Moon Gi

    2000-12-01

    High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The

  16. Station-keeping control for a stratospheric airship platform via fuzzy adaptive backstepping approach

    NASA Astrophysics Data System (ADS)

    Yang, Yueneng; Wu, Jie; Zheng, Wei

    2013-04-01

    This paper presents a novel approach for station-keeping control of a stratospheric airship platform in the presence of parametric uncertainty and external disturbance. First, conceptual design of the stratospheric airship platform is introduced, including the target mission, configuration, energy sources, propeller and payload. Second, the dynamics model of the airship platform is presented, and the mathematical model of its horizontal motion is derived. Third, a fuzzy adaptive backstepping control approach is proposed to develop the station-keeping control system for the simplified horizontal motion. The backstepping controller is designed assuming that the airship model is accurately known, and a fuzzy adaptive algorithm is used to approximate the uncertainty of the airship model. The stability of the closed-loop control system is proven via the Lyapunov theorem. Finally, simulation results illustrate the effectiveness and robustness of the proposed control approach.

  17. Efficient infill sampling for unconstrained robust optimization problems

    NASA Astrophysics Data System (ADS)

    Rehman, Samee Ur; Langelaar, Matthijs

    2016-08-01

    A novel infill sampling criterion is proposed for efficient estimation of the global robust optimum of expensive computer simulation based problems. The algorithm is especially geared towards addressing problems that are affected by uncertainties in design variables and problem parameters. The method is based on constructing metamodels using Kriging and adaptively sampling the response surface via a principle of expected improvement adapted for robust optimization. Several numerical examples and an engineering case study are used to demonstrate the ability of the algorithm to estimate the global robust optimum using a limited number of expensive function evaluations.

  18. Motion estimation in the 3-D Gabor domain.

    PubMed

    Feng, Mu; Reed, Todd R

    2007-08-01

    Motion estimation methods can be broadly classified as being spatiotemporal or frequency domain in nature. The Gabor representation is an analysis framework providing localized frequency information. When applied to image sequences, the 3-D Gabor representation displays spatiotemporal/spatiotemporal-frequency (st/stf) information, enabling the application of robust frequency domain methods with adjustable spatiotemporal resolution. In this work, the 3-D Gabor representation is applied to motion analysis. We demonstrate that piecewise uniform translational motion can be estimated by using a uniform translation motion model in the st/stf domain. The resulting motion estimation method exhibits both good spatiotemporal resolution and substantial noise resistance compared to existing spatiotemporal methods. To form the basis of this model, we derive the signature of the translational motion in the 3-D Gabor domain. Finally, to obtain higher spatiotemporal resolution for more complex motions, a dense motion field estimation method is developed to find a motion estimate for every pixel in the sequence.

  19. The eigenmode analysis of human motion

    NASA Astrophysics Data System (ADS)

    Park, Juyong; Lee, Deok-Sun; González, Marta C.

    2010-11-01

    Rapid advances in modern communication technology are enabling the accumulation of large-scale, high-resolution observational data of the spatiotemporal movements of humans. Classification and prediction of human mobility based on the analysis of such data has great potential in applications such as urban planning in addition to being a subject of theoretical interest. A robust theoretical framework is therefore required to study and properly understand human motion. Here we perform the eigenmode analysis of human motion data gathered from mobile communication records, which allows us to explore the scaling properties and characteristics of human motion.

  20. Robust moving mesh algorithms for hybrid stretched meshes: Application to moving boundaries problems

    NASA Astrophysics Data System (ADS)

    Landry, Jonathan; Soulaïmani, Azzeddine; Luke, Edward; Ben Haj Ali, Amine

    2016-12-01

    A robust Mesh-Mover Algorithm (MMA) approach is designed to adapt meshes of moving boundaries problems. A new methodology is developed from the best combination of well-known algorithms in order to preserve the quality of initial meshes. In most situations, MMAs distribute mesh deformation while preserving a good mesh quality. However, invalid meshes are generated when the motion is complex and/or involves multiple bodies. After studying a few MMA limitations, we propose the following approach: use the Inverse Distance Weighting (IDW) function to produce the displacement field, then apply the Geometric Element Transformation Method (GETMe) smoothing algorithms to improve the resulting mesh quality, and use an untangler to revert negative elements. The proposed approach has been proven efficient to adapt meshes for various realistic aerodynamic motions: a symmetric wing that has suffered large tip bending and twisting and the high-lift components of a swept wing that has moved to different flight stages. Finally, the fluid flow problem has been solved on meshes that have moved and they have produced results close to experimental ones. However, for situations where moving boundaries are too close to each other, more improvements need to be made or other approaches should be taken, such as an overset grid method.

  1. Auditory Motion Elicits a Visual Motion Aftereffect

    PubMed Central

    Berger, Christopher C.; Ehrsson, H. Henrik

    2016-01-01

    The visual motion aftereffect is a visual illusion in which exposure to continuous motion in one direction leads to a subsequent illusion of visual motion in the opposite direction. Previous findings have been mixed with regard to whether this visual illusion can be induced cross-modally by auditory stimuli. Based on research on multisensory perception demonstrating the profound influence auditory perception can have on the interpretation and perceived motion of visual stimuli, we hypothesized that exposure to auditory stimuli with strong directional motion cues should induce a visual motion aftereffect. Here, we demonstrate that horizontally moving auditory stimuli induced a significant visual motion aftereffect—an effect that was driven primarily by a change in visual motion perception following exposure to leftward moving auditory stimuli. This finding is consistent with the notion that visual and auditory motion perception rely on at least partially overlapping neural substrates. PMID:27994538

  2. Costs and benefits of mutational robustness in RNA viruses.

    PubMed

    Stern, Adi; Bianco, Simone; Yeh, Ming Te; Wright, Caroline; Butcher, Kristin; Tang, Chao; Nielsen, Rasmus; Andino, Raul

    2014-08-21

    The accumulation of mutations in RNA viruses is thought to facilitate rapid adaptation to changes in the environment. However, most mutations have deleterious effects on fitness, especially for viruses. Thus, tolerance to mutations should determine the nature and extent of genetic diversity that can be maintained in the population. Here, we combine population genetics theory, computer simulation, and experimental evolution to examine the advantages and disadvantages of tolerance to mutations, also known as mutational robustness. We find that mutational robustness increases neutral diversity and, as expected, can facilitate adaptation to a new environment. Surprisingly, under certain conditions, robustness may also be an impediment for viral adaptation, if a highly diverse population contains a large proportion of previously neutral mutations that are deleterious in the new environment. These findings may inform therapeutic strategies that cause extinction of otherwise robust viral populations.

  3. Collective motion

    NASA Astrophysics Data System (ADS)

    Vicsek, Tamás; Zafeiris, Anna

    2012-08-01

    We review the observations and the basic laws describing the essential aspects of collective motion - being one of the most common and spectacular manifestation of coordinated behavior. Our aim is to provide a balanced discussion of the various facets of this highly multidisciplinary field, including experiments, mathematical methods and models for simulations, so that readers with a variety of background could get both the basics and a broader, more detailed picture of the field. The observations we report on include systems consisting of units ranging from macromolecules through metallic rods and robots to groups of animals and people. Some emphasis is put on models that are simple and realistic enough to reproduce the numerous related observations and are useful for developing concepts for a better understanding of the complexity of systems consisting of many simultaneously moving entities. As such, these models allow the establishing of a few fundamental principles of flocking. In particular, it is demonstrated, that in spite of considerable differences, a number of deep analogies exist between equilibrium statistical physics systems and those made of self-propelled (in most cases living) units. In both cases only a few well defined macroscopic/collective states occur and the transitions between these states follow a similar scenario, involving discontinuity and algebraic divergences.

  4. Parallel Anisotropic Tetrahedral Adaptation

    NASA Technical Reports Server (NTRS)

    Park, Michael A.; Darmofal, David L.

    2008-01-01

    An adaptive method that robustly produces high aspect ratio tetrahedra to a general 3D metric specification without introducing hybrid semi-structured regions is presented. The elemental operators and higher-level logic is described with their respective domain-decomposed parallelizations. An anisotropic tetrahedral grid adaptation scheme is demonstrated for 1000-1 stretching for a simple cube geometry. This form of adaptation is applicable to more complex domain boundaries via a cut-cell approach as demonstrated by a parallel 3D supersonic simulation of a complex fighter aircraft. To avoid the assumptions and approximations required to form a metric to specify adaptation, an approach is introduced that directly evaluates interpolation error. The grid is adapted to reduce and equidistribute this interpolation error calculation without the use of an intervening anisotropic metric. Direct interpolation error adaptation is illustrated for 1D and 3D domains.

  5. Robust and fault tolerant control of modular and reconfigurable robots

    NASA Astrophysics Data System (ADS)

    Abdul, Sajan

    Modular and reconfigurable robot has been one of the main areas of robotics research in recent years due to its wide range of applications, especially in aerospace sector. Dynamic control of manipulators can be performed using joint torque sensing with little information of the link dynamics. From the modular robot perspective, this advantage offered by the torque sensor can be taken to enhance the modularity of the control system. Known modular robots though boast novel and diverse mechanical design on joint modules in one way or another, they still require the whole robot dynamic model for motion control, and modularity offered in the mechanical side does not offer any advantage in the control design. In this work, a modular distributed control technique is formulated for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under this control methodology, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need of re-tuning the controller. Model uncertainties associated with load and links are compensated by the use of joint torque sensors. Other model uncertainties at each joint module are compensated by a decomposition based robust controller for each module. The proposed distributed control technique offers a 'modular' approach, featuring a unique joint-by-joint control synthesis of the joint modules. Fault tolerance and fault detection are formulated as a decentralized control problem for modular and reconfigurable robots in this thesis work. The modularity of the system is exploited to derive a strategy dependent only on a single joint module, while eliminating the need for the motion states of other joint modules. While the traditional fault tolerant and detection schemes are suitable for robots with the whole dynamic model, this proposed technique is ideal for modular and reconfigurable robots because of its modular nature. The proposed methods have been

  6. Piezoelectric step-motion actuator

    DOEpatents

    Mentesana; Charles P.

    2006-10-10

    A step-motion actuator using piezoelectric material to launch a flight mass which, in turn, actuates a drive pawl to progressively engage and drive a toothed wheel or rod to accomplish stepped motion. Thus, the piezoelectric material converts electrical energy into kinetic energy of the mass, and the drive pawl and toothed wheel or rod convert the kinetic energy of the mass into the desired rotary or linear stepped motion. A compression frame may be secured about the piezoelectric element and adapted to pre-compress the piezoelectric material so as to reduce tensile loads thereon. A return spring may be used to return the mass to its resting position against the compression frame or piezoelectric material following launch. Alternative embodiment are possible, including an alternative first embodiment wherein two masses are launched in substantially different directions, and an alternative second embodiment wherein the mass is eliminated in favor of the piezoelectric material launching itself.

  7. Biological Motion Cues Trigger Reflexive Attentional Orienting

    ERIC Educational Resources Information Center

    Shi, Jinfu; Weng, Xuchu; He, Sheng; Jiang, Yi

    2010-01-01

    The human visual system is extremely sensitive to biological signals around us. In the current study, we demonstrate that biological motion walking direction can induce robust reflexive attentional orienting. Following a brief presentation of a central point-light walker walking towards either the left or right direction, observers' performance…

  8. Stretchable Materials for Robust Soft Actuators towards Assistive Wearable Devices

    NASA Astrophysics Data System (ADS)

    Agarwal, Gunjan; Besuchet, Nicolas; Audergon, Basile; Paik, Jamie

    2016-09-01

    Soft actuators made from elastomeric active materials can find widespread potential implementation in a variety of applications ranging from assistive wearable technologies targeted at biomedical rehabilitation or assistance with activities of daily living, bioinspired and biomimetic systems, to gripping and manipulating fragile objects, and adaptable locomotion. In this manuscript, we propose a novel two-component soft actuator design and design tool that produces actuators targeted towards these applications with enhanced mechanical performance and manufacturability. Our numerical models developed using the finite element method can predict the actuator behavior at large mechanical strains to allow efficient design iterations for system optimization. Based on two distinctive actuator prototypes’ (linear and bending actuators) experimental results that include free displacement and blocked-forces, we have validated the efficacy of the numerical models. The presented extensive investigation of mechanical performance for soft actuators with varying geometric parameters demonstrates the practical application of the design tool, and the robustness of the actuator hardware design, towards diverse soft robotic systems for a wide set of assistive wearable technologies, including replicating the motion of several parts of the human body.

  9. Stretchable Materials for Robust Soft Actuators towards Assistive Wearable Devices.

    PubMed

    Agarwal, Gunjan; Besuchet, Nicolas; Audergon, Basile; Paik, Jamie

    2016-09-27

    Soft actuators made from elastomeric active materials can find widespread potential implementation in a variety of applications ranging from assistive wearable technologies targeted at biomedical rehabilitation or assistance with activities of daily living, bioinspired and biomimetic systems, to gripping and manipulating fragile objects, and adaptable locomotion. In this manuscript, we propose a novel two-component soft actuator design and design tool that produces actuators targeted towards these applications with enhanced mechanical performance and manufacturability. Our numerical models developed using the finite element method can predict the actuator behavior at large mechanical strains to allow efficient design iterations for system optimization. Based on two distinctive actuator prototypes' (linear and bending actuators) experimental results that include free displacement and blocked-forces, we have validated the efficacy of the numerical models. The presented extensive investigation of mechanical performance for soft actuators with varying geometric parameters demonstrates the practical application of the design tool, and the robustness of the actuator hardware design, towards diverse soft robotic systems for a wide set of assistive wearable technologies, including replicating the motion of several parts of the human body.

  10. Stretchable Materials for Robust Soft Actuators towards Assistive Wearable Devices

    PubMed Central

    Agarwal, Gunjan; Besuchet, Nicolas; Audergon, Basile; Paik, Jamie

    2016-01-01

    Soft actuators made from elastomeric active materials can find widespread potential implementation in a variety of applications ranging from assistive wearable technologies targeted at biomedical rehabilitation or assistance with activities of daily living, bioinspired and biomimetic systems, to gripping and manipulating fragile objects, and adaptable locomotion. In this manuscript, we propose a novel two-component soft actuator design and design tool that produces actuators targeted towards these applications with enhanced mechanical performance and manufacturability. Our numerical models developed using the finite element method can predict the actuator behavior at large mechanical strains to allow efficient design iterations for system optimization. Based on two distinctive actuator prototypes’ (linear and bending actuators) experimental results that include free displacement and blocked-forces, we have validated the efficacy of the numerical models. The presented extensive investigation of mechanical performance for soft actuators with varying geometric parameters demonstrates the practical application of the design tool, and the robustness of the actuator hardware design, towards diverse soft robotic systems for a wide set of assistive wearable technologies, including replicating the motion of several parts of the human body. PMID:27670953

  11. Perceptual shrinkage of a one-way motion path with high-speed motion

    PubMed Central

    Nakajima, Yutaka; Sakaguchi, Yutaka

    2016-01-01

    Back-and-forth motion induces perceptual shrinkage of the motion path, but such shrinkage is hardly perceived for one-way motion. If the shrinkage is caused by temporal averaging of stimulus position around the endpoints, it should also be induced for one-way motion at higher motion speeds. In psychophysical experiments with a high-speed projector, we tested this conjecture for a one-way motion stimulus at various speeds (4–100 deg/s) along a straight path. Results showed that perceptual shrinkage of the motion path was robustly observed in higher-speed motion (faster than 66.7 deg/s). In addition, the amount of the forwards shift at the onset position was larger than that of the backwards shift at the offset position. These results demonstrate that high-speed motion can induce shrinkage, even for a one-way motion path. This can be explained by the view that perceptual position is represented by the integration of the temporal average of instantaneous position and the motion representation. PMID:27464844

  12. Adaptation of the modified Bouc–Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: Testing using MRI

    SciTech Connect

    Dasari, Paul K. R.; Shazeeb, Mohammed Salman; Könik, Arda; Lindsay, Clifford; Mukherjee, Joyeeta M.; Johnson, Karen L.; King, Michael A.

    2014-11-01

    Purpose: Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc–Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors’ previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart. Methods: In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior–inferior direction during free breathing using MRI navigators. A visual tracking system (VTS) synchronized with MRI acquisition tracked the anterior–posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc–Wen model by inputting the VTS derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson’s linear correlation coefficient between the

  13. Adaptation of the modified Bouc–Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: Testing using MRI

    PubMed Central

    Dasari, Paul K. R.; Shazeeb, Mohammed Salman; Könik, Arda; Lindsay, Clifford; Mukherjee, Joyeeta M.; Johnson, Karen L.; King, Michael A.

    2014-01-01

    Purpose: Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc–Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors’ previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart. Methods: In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior–inferior direction during free breathing using MRI navigators. A visual tracking system (vts) synchronized with MRI acquisition tracked the anterior–posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc–Wen model by inputting the vts derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson’s linear correlation coefficient between the

  14. Modeling repetitive motions using structured light.

    PubMed

    Xu, Yi; Aliaga, Daniel G

    2010-01-01

    Obtaining models of dynamic 3D objects is an important part of content generation for computer graphics. Numerous methods have been extended from static scenarios to model dynamic scenes. If the states or poses of the dynamic object repeat often during a sequence (but not necessarily periodically), we call such a repetitive motion. There are many objects, such as toys, machines, and humans, undergoing repetitive motions. Our key observation is that when a motion-state repeats, we can sample the scene under the same motion state again but using a different set of parameters; thus, providing more information of each motion state. This enables robustly acquiring dense 3D information difficult for objects with repetitive motions using only simple hardware. After the motion sequence, we group temporally disjoint observations of the same motion state together and produce a smooth space-time reconstruction of the scene. Effectively, the dynamic scene modeling problem is converted to a series of static scene reconstructions, which are easier to tackle. The varying sampling parameters can be, for example, structured-light patterns, illumination directions, and viewpoints resulting in different modeling techniques. Based on this observation, we present an image-based motion-state framework and demonstrate our paradigm using either a synchronized or an unsynchronized structured-light acquisition method.

  15. Life in motion, in motion!

    NASA Technical Reports Server (NTRS)

    Kovalenko, Y. A.

    1983-01-01

    A 120 day limited mobility experiment with young male rats and its results, including retarded growth and degenerative changes in the cardiac muscle, are described. A 120 day strict bedrest experiment with 10 human volunteers and its results are described and discussed. Early subjective complaints, subsequent adaptation and eventual progressive changes in excitability and reactivity, reduction in functional capability of the cerebral cortex, and disturbances in water-salt, protein and fat metabolism, including development of precursors of atherosclerosis, as well as poor results of the orthostatic test after 4 months, are presented. These results are explained as applied to sedentary workers and recommendations are given for such persons to exercise in the morning, at work and in the evening in order to prevent hypokinesis and its physical, mental and physiological effects.

  16. Self Motion Perception and Motion Sickness

    NASA Technical Reports Server (NTRS)

    Fox, Robert A. (Principal Investigator)

    1991-01-01

    The studies conducted in this research project examined several aspects of motion sickness in animal models. A principle objective of these studies was to investigate the neuroanatomy that is important in motion sickness with the objectives of examining both the utility of putative models and defining neural mechanisms that are important in motion sickness.

  17. Robustness of spatial micronetworks

    NASA Astrophysics Data System (ADS)

    McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.

    2015-04-01

    Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

  18. Robust Control Systems.

    DTIC Science & Technology

    1981-12-01

    106 A. 13 XSU ......................................... 108 A.14 DDTCON...................................... 108 A.15 DKFTR...operation is preserved. Although some papers (Refs 6 and 13 ) deal with robustness only in regard to parameter variations within the basic controlled...since these can ofter be neglected in actual implementation, a constant-gain time 13 ........................................ invariant solution with

  19. Robustness of spatial micronetworks.

    PubMed

    McAndrew, Thomas C; Danforth, Christopher M; Bagrow, James P

    2015-04-01

    Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

  20. Robustness analysis of stochastic biochemical systems.

    PubMed

    Ceska, Milan; Safránek, David; Dražan, Sven; Brim, Luboš

    2014-01-01

    We propose a new framework for rigorous robustness analysis of stochastic biochemical systems that is based on probabilistic model checking techniques. We adapt the general definition of robustness introduced by Kitano to the class of stochastic systems modelled as continuous time Markov Chains in order to extensively analyse and compare robustness of biological models with uncertain parameters. The framework utilises novel computational methods that enable to effectively evaluate the robustness of models with respect to quantitative temporal properties and parameters such as reaction rate constants and initial conditions. We have applied the framework to gene regulation as an example of a central biological mechanism where intrinsic and extrinsic stochasticity plays crucial role due to low numbers of DNA and RNA molecules. Using our methods we have obtained a comprehensive and precise analysis of stochastic dynamics under parameter uncertainty. Furthermore, we apply our framework to compare several variants of two-component signalling networks from the perspective of robustness with respect to intrinsic noise caused by low populations of signalling components. We have successfully extended previous studies performed on deterministic models (ODE) and showed that stochasticity may significantly affect obtained predictions. Our case studies demonstrate that the framework can provide deeper insight into the role of key parameters in maintaining the system functionality and thus it significantly contributes to formal methods in computational systems biology.

  1. Self-Motion Perception and Motion Sickness

    NASA Technical Reports Server (NTRS)

    Fox, Robert A.

    1991-01-01

    Motion sickness typically is considered a bothersome artifact of exposure to passive motion in vehicles of conveyance. This condition seldom has significant impact on the health of individuals because it is of brief duration, it usually can be prevented by simply avoiding the eliciting condition and, when the conditions that produce it are unavoidable, sickness dissipates with continued exposure. The studies conducted examined several aspects of motion sickness in animal models. A principle objective of these studies was to investigate the neuroanatomy that is important in motion sickness with the objectives of examining both the utility of putative models and defining neural mechanisms that are important in motion sickness.

  2. Automatic Mode Transition Enabled Robust Triboelectric Nanogenerators.

    PubMed

    Chen, Jun; Yang, Jin; Guo, Hengyu; Li, Zhaoling; Zheng, Li; Su, Yuanjie; Wen, Zhen; Fan, Xing; Wang, Zhong Lin

    2015-12-22

    Although the triboelectric nanogenerator (TENG) has been proven to be a renewable and effective route for ambient energy harvesting, its robustness remains a great challenge due to the requirement of surface friction for a decent output, especially for the in-plane sliding mode TENG. Here, we present a rationally designed TENG for achieving a high output performance without compromising the device robustness by, first, converting the in-plane sliding electrification into a contact separation working mode and, second, creating an automatic transition between a contact working state and a noncontact working state. The magnet-assisted automatic transition triboelectric nanogenerator (AT-TENG) was demonstrated to effectively harness various ambient rotational motions to generate electricity with greatly improved device robustness. At a wind speed of 6.5 m/s or a water flow rate of 5.5 L/min, the harvested energy was capable of lighting up 24 spot lights (0.6 W each) simultaneously and charging a capacitor to greater than 120 V in 60 s. Furthermore, due to the rational structural design and unique output characteristics, the AT-TENG was not only capable of harvesting energy from natural bicycling and car motion but also acting as a self-powered speedometer with ultrahigh accuracy. Given such features as structural simplicity, easy fabrication, low cost, wide applicability even in a harsh environment, and high output performance with superior device robustness, the AT-TENG renders an effective and practical approach for ambient mechanical energy harvesting as well as self-powered active sensing.

  3. Adaptive vision-based control of a motor-toggle mechanism: Simulations and experiments

    NASA Astrophysics Data System (ADS)

    Chuang, Chin-Wen; Huang, Ming-Shyan; Chen, Kun-Yung; Fung, Rong-Fong

    2008-05-01

    The dynamic motion of an adaptive visual servoing feedback-controlled punching machine, which is made up by a toggle mechanism driven by a permanent magnet (PM) synchronous servomotor, is studied numerically and experimentally. First, Hamilton's principle, Lagrange multiplier, geometric constraints and partitioning method are employed to derive its dynamic equations for numerical simulations. To satisfy the demand of the machine performance, adaptive controller by using stability analysis with inertia-related Lyapunov function is designed to control the slider responses. Different from the previous studies, the vision servo system of a non-contact measurement of a charge-coupled device (CCD) camera is employed to measure the shape patterns as output states instead of using the expensive linear scale or encoder of the motor-mechanism system. Finally, the stable and robust control performances of an adaptive controller by the Lyapunov stable theory for a motor-toggle mechanism with external disturbances are proposed. A combination of the visual servoing measurement system and the motion control system are established experimentally for the motor-toggle mechanism system. From the agreements between numerical simulations and experimental results, it is demonstrated that the proposed controller, by use of machine vision, is robust to external disturbances for a punching machine system.

  4. Unsupervised motion-based object segmentation refined by color

    NASA Astrophysics Data System (ADS)

    Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

    2003-06-01

    for its ability to estimate motion vectors which closely resemble the true motion. BLOCK-BASED MOTION SEGMENTATION As mentioned above we start with a block-resolution segmentation based on motion vectors. The presented method is inspired by the well-known K-means segmentation method te{K-means}. Several other methods (e.g. te{kmeansc}) adapt K-means for connectedness by adding a weighted shape-error. This adds the additional difficulty of finding the correct weights for the shape-parameters. Also, these methods often bias one particular pre-defined shape. The presented method, which we call K-regions, encourages connectedness because only blocks at the edges of segments may be assigned to another segment. This constrains the segmentation method to such a degree that it allows the method to use least squares for the robust fitting of affine motion models for each segment. Contrary to te{parmkm}, the segmentation step still operates on vectors instead of model parameters. To make sure the segmentation is temporally consistent, the segmentation of the previous frame will be used as initialisation for every new frame. We also present a scheme which makes the algorithm independent of the initially chosen amount of segments. COLOUR-BASED INTRA-BLOCK SEGMENTATION The block resolution motion-based segmentation forms the starting point for the pixel resolution segmentation. The pixel resolution segmentation is obtained from the block resolution segmentation by reclassifying pixels only at the edges of clusters. We assume that an edge between two objects can be found in either one of two neighbouring blocks that belong to different clusters. This assumption allows us to do the pixel resolution segmentation on each pair of such neighbouring blocks separately. Because of the local nature of the segmentation, it largely avoids problems with heterogeneously coloured areas. Because no new segments are introduced in this step, it also does not suffer from oversegmentation problems

  5. Survival and innovation: The role of mutational robustness in evolution.

    PubMed

    Fares, Mario A

    2015-12-01

    Biological systems are resistant to perturbations caused by the environment and by the intrinsic noise of the system. Robustness