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Sample records for adaptive robust motion

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

    PubMed Central

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

    2015-01-01

    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. PMID:26600996

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

  3. Adaptive vehicle motion estimation and prediction

    NASA Astrophysics Data System (ADS)

    Zhao, Liang; Thorpe, Chuck E.

    1999-01-01

    Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

  4. Robust human motion detection via fuzzy set based image understanding

    NASA Astrophysics Data System (ADS)

    Li, Qin; You, Jane

    2006-02-01

    This paper presents an image understanding approach to monitor human movement and identify the abnormal circumstance by robust motion detection for the care of the elderly in a home-based environment. In contrast to the conventional approaches which apply either a single feature extraction scheme or a fixed object model for motion detection and tracking, we introduce a multiple feature extraction scheme for robust motion detection. The proposed algorithms include 1) multiple image feature extraction including the fuzzy compactness based detection of interesting points and fuzzy blobs, 2) adaptive image segmentation via multiple features, 3) Hierarchical motion detection, 4) a flexible model of human motion adapted in both rigid and non-rigid conditions, and 5) Fuzzy decision making via multiple features.

  5. 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.

  6. Rapid contrast gain reduction following motion adaptation.

    PubMed

    Nordström, Karin; Moyer de Miguel, Irene; O'Carroll, David C

    2011-12-01

    Neural and sensory systems adapt to prolonged stimulation to allow signaling across broader input ranges than otherwise possible with the limited bandwidth of single neurons and receptors. In the visual system, adaptation takes place at every stage of processing, from the photoreceptors that adapt to prevailing luminance conditions, to higher-order motion-sensitive neurons that adapt to prolonged exposure to motion. Recent experiments using dynamic, fluctuating visual stimuli indicate that adaptation operates on a time scale similar to that of the response itself. Further work from our own laboratory has highlighted the role for rapid motion adaptation in reliable encoding of natural image motion. Physiologically, motion adaptation can be broken down into four separate components. It is not clear from the previous studies which of these motion adaptation components are involved in the fast and dynamic response changes. To investigate the adapted response in more detail, we therefore analyzed the effect of motion adaptation using a test-adapt-test protocol with adapting durations ranging from 20 ms to 20 s. Our results underscore the very rapid rate of motion adaptation, suggesting that under free flight, visual motion-sensitive neurons continuously adapt to the changing scenery. This might help explain recent observations of strong invariance in the response to natural scenes with highly variable contrast and image structure.

  7. 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.

  8. 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.

  9. Robust Image Restoration for Motion Blur of Image Sensors.

    PubMed

    Yang, Fasheng; Huang, Yongmei; Luo, Yihan; Li, Lixing; Li, Hongwei

    2016-06-09

    Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly. To deal with these problems, we present a robust image restoration algorithm for motion blur of general image sensors in this paper. Firstly, we propose a self-adaptive structure extraction method based on the total variation (TV) to separate the reliable structures from textures and small details of a blurred image which may damage the kernel estimation and interim latent image restoration. Secondly, we combine the reliable structures with priors of the blur kernel, such as sparsity and continuity, by a two-step method with which noise can be removed during iterations of the estimation to improve the precision of the estimated blur kernel. Finally, we use a MR-based Wiener filter as the non-blind deconvolution algorithm to restore the final latent image. Experimental results demonstrate that our algorithm can restore large blur images with rich, small details effectively.

  10. Robust Image Restoration for Motion Blur of Image Sensors

    PubMed Central

    Yang, Fasheng; Huang, Yongmei; Luo, Yihan; Li, Lixing; Li, Hongwei

    2016-01-01

    Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly. To deal with these problems, we present a robust image restoration algorithm for motion blur of general image sensors in this paper. Firstly, we propose a self-adaptive structure extraction method based on the total variation (TV) to separate the reliable structures from textures and small details of a blurred image which may damage the kernel estimation and interim latent image restoration. Secondly, we combine the reliable structures with priors of the blur kernel, such as sparsity and continuity, by a two-step method with which noise can be removed during iterations of the estimation to improve the precision of the estimated blur kernel. Finally, we use a MR-based Wiener filter as the non-blind deconvolution algorithm to restore the final latent image. Experimental results demonstrate that our algorithm can restore large blur images with rich, small details effectively. PMID:27294926

  11. Robust Image Restoration for Motion Blur of Image Sensors.

    PubMed

    Yang, Fasheng; Huang, Yongmei; Luo, Yihan; Li, Lixing; Li, Hongwei

    2016-01-01

    Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly. To deal with these problems, we present a robust image restoration algorithm for motion blur of general image sensors in this paper. Firstly, we propose a self-adaptive structure extraction method based on the total variation (TV) to separate the reliable structures from textures and small details of a blurred image which may damage the kernel estimation and interim latent image restoration. Secondly, we combine the reliable structures with priors of the blur kernel, such as sparsity and continuity, by a two-step method with which noise can be removed during iterations of the estimation to improve the precision of the estimated blur kernel. Finally, we use a MR-based Wiener filter as the non-blind deconvolution algorithm to restore the final latent image. Experimental results demonstrate that our algorithm can restore large blur images with rich, small details effectively. PMID:27294926

  12. 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.

  13. Adaptive control: Stability, convergence, and robustness

    NASA Technical Reports Server (NTRS)

    Sastry, Shankar; Bodson, Marc

    1989-01-01

    The deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers. Chapters are devoted to basic AC approaches, notation and fundamental theorems, the identification problem, model-reference AC, parameter convergence using averaging techniques, and AC robustness. Consideration is given to the use of prior information, the global stability of indirect AC schemes, multivariable AC, linearizing AC for a class of nonlinear systems, AC of linearizable minimum-phase systems, and MIMO systems decouplable by static state feedback.

  14. 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.

  15. Adaptive GOP structure based on motion coherence

    NASA Astrophysics Data System (ADS)

    Ma, Yanzhuo; Wan, Shuai; Chang, Yilin; Yang, Fuzheng; Wang, Xiaoyu

    2009-08-01

    Adaptive Group of Pictures (GOP) is helpful for increasing the efficiency of video encoding by taking account of characteristics of video content. This paper proposes a method for adaptive GOP structure selection for video encoding based on motion coherence, which extracts key frames according to motion acceleration, and assigns coding type for each key and non-key frame correspondingly. Motion deviation is then used instead of motion magnitude in the selection of the number of B frames. Experimental results show that the proposed method for adaptive GOP structure selection achieves performance gain of 0.2-1dB over the fixed GOP, and has the advantage of better transmission resilience. Moreover, this method can be used in real-time video coding due to its low complexity.

  16. Robust adaptive control for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Kahveci, Nazli E.

    anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.

  17. 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.

  18. Decision-level adaptation in motion perception

    PubMed Central

    2015-01-01

    Prolonged exposure to visual stimuli causes a bias in observers' responses to subsequent stimuli. Such adaptation-induced biases are usually explained in terms of changes in the relative activity of sensory neurons in the visual system which respond selectively to the properties of visual stimuli. However, the bias could also be due to a shift in the observer's criterion for selecting one response rather than the alternative; adaptation at the decision level of processing rather than the sensory level. We investigated whether adaptation to implied motion is best attributed to sensory-level or decision-level bias. Three experiments sought to isolate decision factors by changing the nature of the participants' task while keeping the sensory stimulus unchanged. Results showed that adaptation-induced bias in reported stimulus direction only occurred when the participants' task involved a directional judgement, and disappeared when adaptation was measured using a non-directional task (reporting where motion was present in the display, regardless of its direction). We conclude that adaptation to implied motion is due to decision-level bias, and that a propensity towards such biases may be widespread in sensory decision-making. PMID:27019726

  19. Nonlinear transform for robust dense block-based motion estimation.

    PubMed

    Xu, Rui; Taubman, David; Naman, Aous Thabit

    2014-05-01

    We present a noniterative multiresolution motion estimation strategy, involving block-based comparisons in each detail band of a Laplacian pyramid. A novel matching score is developed and analyzed. The proposed matching score is based on a class of nonlinear transformations of Laplacian detail bands, yielding 1-bit or 2-bit representations. The matching score is evaluated in a dense full-search motion estimation setting, with synthetic video frames and an optical flow data set. Together with a strategy for combining the matching scores across resolutions, the proposed method is shown to produce smoother and more robust estimates than mean square error (MSE) in each detail band and combined. It tolerates more of nontranslational motion, such as rotation, validating the analysis, while providing much better localization of the motion discontinuities. We also provide an efficient implementation of the motion estimation strategy and show that the computational complexity of the approach is closely related to the traditional MSE block-based full-search motion estimation procedure.

  20. 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

  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. PMID:24987749

  2. Robust adaptive vibration control of a flexible structure.

    PubMed

    Khoshnood, A M; Moradi, H M

    2014-07-01

    Different types of L1 adaptive control systems show that using robust theories with adaptive control approaches has produced high performance controllers. In this study, a model reference adaptive control scheme considering robust theories is used to propose a practical control system for vibration suppression of a flexible launch vehicle (FLV). In this method, control input of the system is shaped from the dynamic model of the vehicle and components of the control input are adaptively constructed by estimating the undesirable vibration frequencies. Robust stability of the adaptive vibration control system is guaranteed by using the L1 small gain theorem. Simulation results of the robust adaptive vibration control strategy confirm that the effects of vibration on the vehicle performance considerably decrease without the loss of the phase margin of the system.

  3. 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.

  4. Decentralized digital adaptive control of robot motion

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1990-01-01

    A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

  5. Adaptive prediction of respiratory motion for motion compensation radiotherapy

    NASA Astrophysics Data System (ADS)

    Ren, Qing; Nishioka, Seiko; Shirato, Hiroki; Berbeco, Ross I.

    2007-11-01

    One potential application of image-guided radiotherapy is to track the target motion in real time, then deliver adaptive treatment to a dynamic target by dMLC tracking or respiratory gating. However, the existence of a finite time delay (or a system latency) between the image acquisition and the response of the treatment system to a change in tumour position implies that some kind of predictive ability should be included in the real-time dynamic target treatment. If diagnostic x-ray imaging is used for the tracking, the dose given over a whole image-guided radiotherapy course can be significant. Therefore, the x-ray beam used for motion tracking should be triggered at a relatively slow pulse frequency, and an interpolation between predictions can be used to provide a fast tracking rate. This study evaluates the performance of an autoregressive-moving average (ARMA) model based prediction algorithm for reducing tumour localization error due to system latency and slow imaging rate. For this study, we use 3D motion data from ten lung tumour cases where the peak-to-peak motion is greater than 8 mm. Some strongly irregular traces with variation in amplitude and phase were included. To evaluate the prediction accuracy, the standard deviations between predicted and actual motion position are computed for three system latencies (0.1, 0.2 and 0.4 s) at several imaging rates (1.25-10 Hz), and compared against the situation of no prediction. The simulation results indicate that the implementation of the prediction algorithm in real-time target tracking can improve the localization precision for all latencies and imaging rates evaluated. From a common initial setting of model parameters, the predictor can quickly provide an accurate prediction of the position after collecting 20 initial data points. In this retrospective analysis, we calculate the standard deviation of the predicted position from the twentieth position data to the end of the session at 0.1 s interval. For both

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

    PubMed

    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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Robust Adaptive Control In Hilbert Space

    NASA Technical Reports Server (NTRS)

    Wen, John Ting-Yung; Balas, Mark J.

    1990-01-01

    Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.

  14. 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.

  15. 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

  16. Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.

    PubMed

    Peng, Jinzhu; Yu, Jie; Wang, Jie

    2014-07-01

    In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. PMID:24917071

  17. 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.

  18. Adaptive robust control of the EBR-II reactor

    SciTech Connect

    Power, M.A.; Edwards, R.M.

    1996-05-01

    Simulation results are presented for an adaptive H{sub {infinity}} controller, a fixed H{sub {infinity}} controller, and a classical controller. The controllers are applied to a simulation of the Experimental Breeder Reactor II primary system. The controllers are tested for the best robustness and performance by step-changing the demanded reactor power and by varying the combined uncertainty in initial reactor power and control rod worth. The adaptive H{sub {infinity}} controller shows the fastest settling time, fastest rise time and smallest peak overshoot when compared to the fixed H{sub {infinity}} and classical controllers. This makes for a superior and more robust controller.

  19. 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.

  20. 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.

  1. 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. PMID:24808035

  2. 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.

  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. 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

  5. Robust adaptive dynamic programming with an application to power systems.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2013-07-01

    This brief presents a novel framework of robust adaptive dynamic programming (robust-ADP) aimed at computing globally stabilizing and suboptimal control policies in the presence of dynamic uncertainties. A key strategy is to integrate ADP theory with techniques in modern nonlinear control with a unique objective of filling up a gap in the past literature of ADP without taking into account dynamic uncertainties. Neither the system dynamics nor the system order are required to be precisely known. As an illustrative example, the computational algorithm is applied to the controller design of a two-machine power system. PMID:24808528

  6. Robust control of a bimorph mirror for adaptive optics systems.

    PubMed

    Baudouin, Lucie; Prieur, Christophe; Guignard, Fabien; Arzelier, Denis

    2008-07-10

    We apply robust control techniques to an adaptive optics system including a dynamic model of the deformable mirror. The dynamic model of the mirror is a modification of the usual plate equation. We propose also a state-space approach to model the turbulent phase. A continuous time control of our model is suggested, taking into account the frequential behavior of the turbulent phase. An H(infinity) controller is designed in an infinite-dimensional setting. Because of the multivariable nature of the control problem involved in adaptive optics systems, a significant improvement is obtained with respect to traditional single input-single output methods.

  7. 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.

  8. 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.

  9. How MAP kinase modules function as robust, yet adaptable, circuits

    PubMed Central

    Tian, Tianhai; Harding, Angus

    2014-01-01

    Genetic and biochemical studies have revealed that the diversity of cell types and developmental patterns evident within the animal kingdom is generated by a handful of conserved, core modules. Core biological modules must be robust, able to maintain functionality despite perturbations, and yet sufficiently adaptable for random mutations to generate phenotypic variation during evolution. Understanding how robust, adaptable modules have influenced the evolution of eukaryotes will inform both evolutionary and synthetic biology. One such system is the MAP kinase module, which consists of a 3-tiered kinase circuit configuration that has been evolutionarily conserved from yeast to man. MAP kinase signal transduction pathways are used across eukaryotic phyla to drive biological functions that are crucial for life. Here we ask the fundamental question, why do MAPK modules follow a conserved 3-tiered topology rather than some other number? Using computational simulations, we identify a fundamental 2-tiered circuit topology that can be readily reconfigured by feedback loops and scaffolds to generate diverse signal outputs. When this 2-kinase circuit is connected to proximal input kinases, a 3-tiered modular configuration is created that is both robust and adaptable, providing a biological circuit that can regulate multiple phenotypes and maintain functionality in an uncertain world. We propose that the 3-tiered signal transduction module has been conserved through positive selection, because it facilitated the generation of phenotypic variation during eukaryotic evolution. PMID:25483189

  10. An adaptive robust controller for time delay maglev transportation systems

    NASA Astrophysics Data System (ADS)

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  11. How protein materials balance strength, robustness, and adaptability

    PubMed Central

    Buehler, Markus J.; Yung, Yu Ching

    2010-01-01

    Proteins form the basis of a wide range of biological materials such as hair, skin, bone, spider silk, or cells, which play an important role in providing key functions to biological systems. The focus of this article is to discuss how protein materials are capable of balancing multiple, seemingly incompatible properties such as strength, robustness, and adaptability. To illustrate this, we review bottom-up materiomics studies focused on the mechanical behavior of protein materials at multiple scales, from nano to macro. We focus on alpha-helix based intermediate filament proteins as a model system to explain why the utilization of hierarchical structural features is vital to their ability to combine strength, robustness, and adaptability. Experimental studies demonstrating the activation of angiogenesis, the growth of new blood vessels, are presented as an example of how adaptability of structure in biological tissue is achieved through changes in gene expression that result in an altered material structure. We analyze the concepts in light of the universality and diversity of the structural makeup of protein materials and discuss the findings in the context of potential fundamental evolutionary principles that control their nanoscale structure. We conclude with a discussion of multiscale science in biology and de novo materials design. PMID:20676305

  12. Robust flicker evaluation method for low power adaptive dimming LCDs

    NASA Astrophysics Data System (ADS)

    Kim, Seul-Ki; Song, Seok-Jeong; Nam, Hyoungsik

    2015-05-01

    This paper describes a robust dimming flicker evaluation method of adaptive dimming algorithms for low power liquid crystal displays (LCDs). While the previous methods use sum of square difference (SSD) values without excluding the image sequence information, the proposed modified SSD (mSSD) values are obtained only with the dimming flicker effects by making use of differential images. The proposed scheme is verified for eight dimming configurations of two dimming level selection methods and four temporal filters over three test videos. Furthermore, a new figure of merit is introduced to cover the dimming flicker as well as image qualities and power consumption.

  13. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    PubMed Central

    Quagliotti, Fulvia

    2014-01-01

    The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. Moreover, if the controller parameters are tuned for a specific gust model, even if the gust frequency changes, no parameter retuning is required. PMID:24688411

  14. Self-evaluation on Motion Adaptation for Service Robots

    NASA Astrophysics Data System (ADS)

    Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

    We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. Effects of crowding and attention on high-levels of motion processing and motion adaptation.

    PubMed

    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.

  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. PMID:26422902

  1. 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.

  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. Human motor adaptation in whole body motion.

    PubMed

    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

  4. 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.

  5. Fast-coding robust motion estimation model in a GPU

    NASA Astrophysics Data System (ADS)

    García, Carlos; Botella, Guillermo; de Sande, Francisco; Prieto-Matias, Manuel

    2015-02-01

    Nowadays vision systems are used with countless purposes. Moreover, the motion estimation is a discipline that allow to extract relevant information as pattern segmentation, 3D structure or tracking objects. However, the real-time requirements in most applications has limited its consolidation, considering the adoption of high performance systems to meet response times. With the emergence of so-called highly parallel devices known as accelerators this gap has narrowed. Two extreme endpoints in the spectrum of most common accelerators are Field Programmable Gate Array (FPGA) and Graphics Processing Systems (GPU), which usually offer higher performance rates than general propose processors. Moreover, the use of GPUs as accelerators involves the efficient exploitation of any parallelism in the target application. This task is not easy because performance rates are affected by many aspects that programmers should overcome. In this paper, we evaluate OpenACC standard, a programming model with directives which favors porting any code to a GPU in the context of motion estimation application. The results confirm that this programming paradigm is suitable for this image processing applications achieving a very satisfactory acceleration in convolution based problems as in the well-known Lucas & Kanade method.

  6. 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.

  7. 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.

  8. 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.

  9. 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. PMID:26465549

  10. An adaptive algorithm for motion compensated color image coding

    NASA Technical Reports Server (NTRS)

    Kwatra, Subhash C.; Whyte, Wayne A.; Lin, Chow-Ming

    1987-01-01

    This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.

  11. Towards robust 3D visual tracking for motion compensation in beating heart surgery.

    PubMed

    Richa, Rogério; Bó, Antônio P L; Poignet, Philippe

    2011-06-01

    In the context of minimally invasive cardiac surgery, active vision-based motion compensation schemes have been proposed for mitigating problems related to physiological motion. However, robust and accurate visual tracking remains a difficult task. The purpose of this paper is to present a robust visual tracking method that estimates the 3D temporal and spatial deformation of the heart surface using stereo endoscopic images. The novelty is the combination of a visual tracking method based on a Thin-Plate Spline (TPS) model for representing the heart surface deformations with a temporal heart motion model based on a time-varying dual Fourier series for overcoming tracking disturbances or failures. The considerable improvements in tracking robustness facing specular reflections and occlusions are demonstrated through experiments using images of in vivo porcine and human beating hearts.

  12. Towards robust 3D visual tracking for motion compensation in beating heart surgery.

    PubMed

    Richa, Rogério; Bó, Antônio P L; Poignet, Philippe

    2011-06-01

    In the context of minimally invasive cardiac surgery, active vision-based motion compensation schemes have been proposed for mitigating problems related to physiological motion. However, robust and accurate visual tracking remains a difficult task. The purpose of this paper is to present a robust visual tracking method that estimates the 3D temporal and spatial deformation of the heart surface using stereo endoscopic images. The novelty is the combination of a visual tracking method based on a Thin-Plate Spline (TPS) model for representing the heart surface deformations with a temporal heart motion model based on a time-varying dual Fourier series for overcoming tracking disturbances or failures. The considerable improvements in tracking robustness facing specular reflections and occlusions are demonstrated through experiments using images of in vivo porcine and human beating hearts. PMID:21277821

  13. Multiple ping sonar accuracy improvement using robust motion estimation and ping fusion.

    PubMed

    Yu, Lian; Neretti, Nicola; Intrator, Nathan

    2006-04-01

    Noise degrades the accuracy of sonar systems. We demonstrate a practical method for increasing the effective signal-to-noise ratio (SNR) by fusing time delay information from a burst of multiple sonar pings. This approach can be useful when there is no relative motion between the sonar and the target during the burst of sonar pinging. Otherwise, the relative motion degrades the fusion and therefore, has to be addressed before fusion can be used. In this paper, we present a robust motion estimation algorithm which uses information from multiple receivers to estimate the relative motion between pings in the burst. We then compensate for motion, and show that the fusion of information from the burst of motion compensated pings improves both the resilience to noise and sonar accuracy, consequently increasing the operating range of the sonar system.

  14. Investigation of the robustness of adaptive neuro-fuzzy inference system for tracking moving tumors in external radiotherapy.

    PubMed

    Torshabi, Ahmad Esmaili

    2014-12-01

    In external radiotherapy of dynamic targets such as lung and breast cancers, accurate correlation models are utilized to extract real time tumor position by means of external surrogates in correlation with the internal motion of tumors. In this study, a correlation method based on the neuro-fuzzy model is proposed to correlate the input external motion data with internal tumor motion estimation in real-time mode, due to its robustness in motion tracking. An initial test of the performance of this model was reported in our previous studies. In this work by implementing some modifications it is resulted that ANFIS is still robust to track tumor motion more reliably by reducing the motion estimation error remarkably. After configuring new version of our ANFIS model, its performance was retrospectively tested over ten patients treated with Synchrony Cyberknife system. In order to assess the performance of our model, the predicted tumor motion as model output was compared with respect to the state of the art model. Final analyzed results show that our adaptive neuro-fuzzy model can reduce tumor tracking errors more significantly, as compared with ground truth database and even tumor tracking methods presented in our previous works. PMID:25412886

  15. An adaptive recurrent-neural-network motion controller for X-Y table in CNC machine.

    PubMed

    Lin, Faa-Jeng; Shieh, Hsin-Jang; Shieh, Po-Huang; Shen, Po-Hung

    2006-04-01

    In this paper, an adaptive recurrent-neural-network (ARNN) motion control system for a biaxial motion mechanism driven by two field-oriented control permanent magnet synchronous motors (PMSMs) in the computer numerical control (CNC) machine is proposed. In the proposed ARNN control system, a RNN with accurate approximation capability is employed to approximate an unknown dynamic function, and the adaptive learning algorithms that can learn the parameters of the RNN on line are derived using Lyapunov stability theorem. Moreover, a robust controller is proposed to confront the uncertainties including approximation error, optimal parameter vectors, higher-order terms in Taylor series, external disturbances, cross-coupled interference and friction torque of the system. To relax the requirement for the value of lumped uncertainty in the robust controller, an adaptive lumped uncertainty estimation law is investigated. Using the proposed control, the position tracking performance is substantially improved and the robustness to uncertainties including cross-coupled interference and friction torque can be obtained as well. Finally, some experimental results of the tracking of various reference contours demonstrate the validity of the proposed design for practical applications. PMID:16602590

  16. Adaptation and the temporal delay filter of fly motion detectors.

    PubMed

    Harris, R A; O'Carroll, D C; Laughlin, S B

    1999-08-01

    Recent accounts attribute motion adaptation to a shortening of the delay filter in elementary motion detectors (EMDs). Using computer modelling and recordings from HS neurons in the drone-fly Eristalis tenax, we present evidence that challenges this theory. (i) Previous evidence for a change in the delay filter comes from 'image step' (or 'velocity impulse') experiments. We note a large discrepancy between the temporal frequency tuning predicted from these experiments and the observed tuning of motion sensitive cells. (ii) The results of image step experiments are highly sensitive to the experimental method used. (iii) An apparent motion stimulus reveals a much shorter EMD delay than suggested by previous 'image step' experiments. This short delay agrees with the observed temporal frequency sensitivity of the unadapted cell. (iv) A key prediction of a shortening delay filter is that the temporal frequency optimum of the cell should show a large shift to higher temporal frequencies after motion adaptation. We show little change in the temporal or spatial frequency (and hence velocity) optima following adaptation.

  17. 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.

  18. Robust stochastic resonance: Signal detection and adaptation in impulsive noise

    NASA Astrophysics Data System (ADS)

    Kosko, Bart; Mitaim, Sanya

    2001-11-01

    Stochastic resonance (SR) occurs when noise improves a system performance measure such as a spectral signal-to-noise ratio or a cross-correlation measure. All SR studies have assumed that the forcing noise has finite variance. Most have further assumed that the noise is Gaussian. We show that SR still occurs for the more general case of impulsive or infinite-variance noise. The SR effect fades as the noise grows more impulsive. We study this fading effect on the family of symmetric α-stable bell curves that includes the Gaussian bell curve as a special case. These bell curves have thicker tails as the parameter α falls from 2 (the Gaussian case) to 1 (the Cauchy case) to even lower values. Thicker tails create more frequent and more violent noise impulses. The main feedback and feedforward models in the SR literature show this fading SR effect for periodic forcing signals when we plot either the signal-to-noise ratio or a signal correlation measure against the dispersion of the α-stable noise. Linear regression shows that an exponential law γopt(α)=cAα describes this relation between the impulsive index α and the SR-optimal noise dispersion γopt. The results show that SR is robust against noise ``outliers.'' So SR may be more widespread in nature than previously believed. Such robustness also favors the use of SR in engineering systems. We further show that an adaptive system can learn the optimal noise dispersion for two standard SR models (the quartic bistable model and the FitzHugh-Nagumo neuron model) for the signal-to-noise ratio performance measure. This also favors practical applications of SR and suggests that evolution may have tuned the noise-sensitive parameters of biological systems.

  19. Smart Rehabilitation Devices: Part II – Adaptive Motion Control

    PubMed Central

    Dong, Shufang; Lu, Ke-Qian; Sun, J. Q.; Rudolph, Katherine

    2008-01-01

    This article presents a study of adaptive motion control of smart versatile rehabilitation devices using MR fluids. The device provides both isometric and isokinetic strength training and is reconfigurable for several human joints. Adaptive controls are developed to regulate resistance force based on the prescription of the therapist. Special consideration has been given to the human–machine interaction in the adaptive control that can modify the behavior of the device to account for strength gains or muscle fatigue of the human subject. PMID:18548131

  20. Memory-based robust adaptive control of a variable length stepping nanomanipulator

    NASA Astrophysics Data System (ADS)

    Saeidpourazar, Reza; Jalili, Nader

    2007-04-01

    This paper presents the modeling and memory-based robust adaptive control of a variable length stepping nanomanipulator. A three degree of freedom (3DOF) nanomanipulator with revolute revolute prismatic (RRP) actuator structure, namely here MM3A, is utilized for a variety of nanomanipulation tasks. Unlike widely used Cartesian-structure nanomanipulators, the MM3A is equipped with revolute-piezoelectric actuators which result in outstanding performance for controlling the nanomanipulator's tip alignment during the nanomanipulation process. However, the RRP structure of the nanomanipulator introduces complicity in kinematic and dynamic equations of the system which needs to be addressed in order to control the nanomanipulation process. Dissimilar to the ordinary piezoelectric actuators which provide only a couple of micrometers working range, the piezoelectric actuators utilized in MM3A, namely Nanomotors, provide wide range of action (120° in revolute actuators and 12mm in prismatic actuator) with sub-nano scale precision (0.1 μrad in revolute actuators and 0.25 nm in prismatic actuator). This wide range of action combined with sub-nano scale precision is achieved using a special stick/slip moving principle of the Nanomotors. However, such stick/slip motion results in stepping movement of the MM3A. Hence, due to the RRP structure and stepping movement principle of the MM3A nanomanipulator, controller design for the nanomanipulation process is not a trivial task. In this paper, a novel memory-based robust adaptive controller is proposed to overcome these shortfalls. Following the development of the memory-based robust adaptive controller, numerical simulations of the proposed controller are preformed to demonstrate the positioning performance capability of the controller in nanomanipulation tasks.

  1. 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.

  2. Motion prediction using dual Kalman filter for robust beating heart tracking.

    PubMed

    Yang, Bo; Liu, Chao; Poignet, Philippe; Zheng, Wenfeng; Liu, Shan

    2015-08-01

    A novel prediction method for robust beating heart tracking is proposed. The dual time-varying Fourier series is used to model the heart motion. The frequency parameters and Fourier coefficients in the model are estimated respectively by using a dual Kalman filter scheme. The instantaneous frequencies of breathing and heartbeat motion are measured online from the 3D trajectory of the point of interest using an orthogonal decomposition algorithm. The proposed method is evaluated based on both the simulated signals and the real motion signals, which are measured from the videos recorded using the da Vinci surgical system.

  3. 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

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

    PubMed

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

    2013-03-01

    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.

  5. 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.

  6. 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.

  7. Quantification of organ motion based on an adaptive image-based scale invariant feature method

    SciTech Connect

    Paganelli, Chiara; Peroni, Marta

    2013-11-15

    Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT

  8. 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.

  9. Robust adaptive relative position and attitude control for spacecraft autonomous proximity.

    PubMed

    Sun, Liang; Huo, Wei; Jiao, Zongxia

    2016-07-01

    This paper provides new results of the dynamical modeling and controller designing for autonomous close proximity phase during rendezvous and docking in the presence of kinematic couplings and model uncertainties. A globally defined relative motion mechanical model for close proximity operations is introduced firstly. Then, in spite of the kinematic couplings and thrust misalignment between relative rotation and relative translation, robust adaptive relative position and relative attitude controllers are designed successively. Finally, stability of the overall system is proved that the relative position and relative attitude are uniformly ultimately bounded, and the size of the ultimate bound can be regulated small enough by control system parameters. Performance of the controlled overall system is demonstrated via a representative numerical example. PMID:26993103

  10. 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.

  11. 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.

  12. 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.

  13. 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. PMID:23821598

  14. Robust Identification of Local Adaptation from Allele Frequencies

    PubMed Central

    Günther, Torsten; Coop, Graham

    2013-01-01

    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. PMID:23821598

  15. 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

  16. An adaptive motion estimation scheme for video coding.

    PubMed

    Liu, Pengyu; 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.

  17. 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.

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

    PubMed

    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

  19. 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

  20. Optimization under uncertainty: Adaptive variance reduction, adaptive metamodeling, and investigation of robustness measures

    NASA Astrophysics Data System (ADS)

    Medina, Juan Camilo

    This dissertation offers computational and theoretical advances for optimization under uncertainty problems that utilize a probabilistic framework for addressing such uncertainties, and adopt a probabilistic performance as objective function. Emphasis is placed on applications that involve potentially complex numerical and probability models. A generalized approach is adopted, treating the system model as a "black-box" and relying on stochastic simulation for evaluating the probabilistic performance. This approach can impose, though, an elevated computational cost, and two of the advances offered in this dissertation aim at decreasing the computational burden associated with stochastic simulation when integrated with optimization applications. The first one develops an adaptive implementation of importance sampling (a popular variance reduction technique) by sharing information across the iterations of the numerical optimization algorithm. The system model evaluations from the current iteration are utilized to formulate importance sampling densities for subsequent iterations with only a small additional computational effort. The characteristics of these densities as well as the specific model parameters these densities span are explicitly optimized. The second advancement focuses on adaptive tuning of a kriging metamodel to replace the computationally intensive system model. A novel implementation is considered, establishing a metamodel with respect to both the uncertain model parameters as well as the design variables, offering significant computational savings. Additionally, the adaptive selection of certain characteristics of the metamodel, such as support points or order of basis functions, is considered by utilizing readily available information from the previous iteration of the optimization algorithm. The third advancement extends to a different application and considers the assessment of the appropriateness of different candidate robust designs. A novel

  1. 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.

  2. 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.

  3. Space motion sickness and vestibular adaptation to weightlessness

    NASA Technical Reports Server (NTRS)

    Young, L. R.

    1983-01-01

    Theories of space motion sickness are discussed together with near future vestibular experiments for three Spacelab missions. The sensory conflict theory is covered, as well as theories involving unequal otolith masses, semicircular canals, cardiovascular adaptation and fluid shift toward the head, and extra-labyrinthine effects. Experiments will test the hypothesis that the sensitivity of the otolith organ response is shifted during weightlessness and that this shift carries over to the post-flight experience. Visual-vestibular-tactile interaction, vestibulo-ocular reflexes, ocular counterrolling, awareness of body position, otolith-spinal reflexes, and motion sickness susceptibility are among the parameters to be studied. Preflight and postflight tests will emphasize evaluation of any residual effects of the seven day weightless exposure on vestibulo-spinal and vestibulo-ocular pathways.

  4. Different time scales of motion integration for anticipatory smooth pursuit and perceptual adaptation

    PubMed Central

    Maus, Gerrit W.; Potapchuk, Elena; Watamaniuk, Scott N. J.; Heinen, Stephen J.

    2015-01-01

    When repeatedly exposed to moving stimuli, the oculomotor system elicits anticipatory smooth pursuit (ASP) eye movements, even before the stimulus moves. ASP is affected oppositely to perceptual speed judgments of repetitive moving stimuli: After a sequence of fast stimuli, ASP velocity increases, whereas perceived speed decreases. These two effects—perceptual adaptation and oculomotor priming—could result from adapting a single common internal speed representation that is used for perceptual comparisons and for generating ASP. Here we test this hypothesis by assessing the temporal dependence of both effects on stimulus history. Observers performed speed discriminations on moving random dot stimuli, either while pursuing the movement or maintaining steady fixation. In both cases, responses showed perceptual adaptation: Stimuli preceded by fast speeds were perceived as slower, and vice versa. To evaluate oculomotor priming, we analyzed ASP velocity as a function of average stimulus speed in preceding trials and found strong positive dependencies. Interestingly, maximal priming occurred over short stimulus histories (∼two trials), whereas adaptation was maximal over longer histories (∼15 trials). The temporal dissociation of adaptation and priming suggests different underlying mechanisms. It may be that perceptual adaptation integrates over a relatively long period to robustly calibrate the operating range of the motion system, thereby avoiding interference from transient changes in stimulus speed. On the other hand, the oculomotor system may rapidly prime anticipatory velocity to efficiently match it to that of the pursuit target. PMID:25761334

  5. Robust neural network motion tracking control of piezoelectric actuation systems for micro/nanomanipulation.

    PubMed

    Liaw, Hwee Choo; Shirinzadeh, Bijan; Smith, Julian

    2009-02-01

    This paper presents a robust neural network motion tracking control methodology for piezoelectric actuation systems employed in micro/nanomanipulation. This control methodology is proposed for tracking of desired motion trajectories in the presence of unknown system parameters, nonlinearities including the hysteresis effect and external disturbances in the control systems. In this paper, the related control issues are investigated, and a control methodology is established including the neural networks and a sliding control scheme. In particular, the radial basis function (RBF) neural networks are chosen for function approximations. The stability of the closed-loop system, as well as the convergence of the position and velocity tracking errors to zero, is assured by the control methodology in the presence of the aforementioned conditions. An offline learning procedure is also proposed for the improvement of the motion tracking performance. Precise tracking results of the proposed control methodology for a desired motion trajectory are demonstrated in the experimental study. With such a motion tracking capability, the proposed control methodology promises the realization of high-performance piezoelectric actuated micro/nanomanipulation systems.

  6. The Circle will Now be Closed, Finally. (On the Inability to Adapt Circular Motion to Arbitrary Motions)

    NASA Astrophysics Data System (ADS)

    Jochim, E. F. M.

    2015-04-01

    The description of the motion of the Sun, Moon, stars, planets and satellites was originally based on a model of circular uniform motion. Improved observational methods required an improved model which was found by superposition of different circles, each traversed by uniform motion. Copernicus seems to have been the first (or at least one of the first) to have recognized that the planets do not move in a circle. The new curve to be adapted to planetary motion was found by Kepler. Based on a general theory of adaptation of any motion as a consequence of the method of the variation of parameters, the present paper shows that the circle is the only curve which is not able to be adapted to any general motion.

  7. 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.

  8. 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

  9. 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. PMID:25159049

  10. Non-adaptive robust filters for speckle noise reduction

    NASA Astrophysics Data System (ADS)

    Frery, Alejandro C.; Santanna, Sidnei J. S.

    1993-06-01

    After briefly reviewing some classical filters for speckle removal, five filters with characteristics of robustness, suitable for speckle noise reduction, are derived and implemented. These filters are the ones based on the trimmed maximum likelihood and moments estimators, the ones based on the median, on the inter-quartile range, and on the median absolute deviation. Assuming that observations within a synthetic aperture radar image are outcomes of independent Rayleigh random variables, these filters exhibit a good performance from both the signal-to-noise reduction and from the edge preserving criteria. The problem of filtering in an image is posed as an estimation problem.

  11. 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.

  12. Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

    NASA Astrophysics Data System (ADS)

    Wang, Xiuzhong; Srinivas, Chukka

    2016-03-01

    This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

  13. 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.

  14. 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. PMID:24696801

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Robust mosaicing with correction of motion distortions and tissue deformations for in vivo fibered microscopy.

    PubMed

    Vercauteren, Tom; Perchant, Aymeric; Malandain, Grégoire; Pennec, Xavier; Ayache, Nicholas

    2006-10-01

    Real-time in vivo and in situ imaging at the cellular level can be achieved with fibered confocal microscopy. As interesting as dynamic sequences may be, there is a need for the biologist or physician to get an efficient and complete representation of the entire imaged region. For this demand, the potential of this imaging modality is enhanced by using video mosaicing techniques. Classical mosaicing algorithms do not take into account the characteristics of fibered confocal microscopy, namely motion distortions, irregularly sampled frames and non-rigid deformations of the imaged tissue. Our approach is based on a hierarchical framework that is able to recover a globally consistent alignment of the input frames, to compensate for the motion distortions and to capture the non-rigid deformations. The proposed global alignment scheme is seen as an estimation problem on a Lie group. We model the relationship between the motion and the motion distortions to correct for these distortions. An efficient scattered data approximation scheme is proposed both for the construction of the mosaic and to adapt the demons registration algorithm to our irregularly sampled inputs. Controlled experiments have been conducted to evaluate the performance of our algorithm. Results on several sequences acquired in vivo on both human and mouse tissue also demonstrate the relevance of our approach. PMID:16887375

  20. Robust estimation of motion blur kernel using a piecewise-linear model.

    PubMed

    Sungchan Oh; Gyeonghwan Kim

    2014-03-01

    Blur kernel estimation is a crucial step in the deblurring process for images. Estimation of the kernel, especially in the presence of noise, is easily perturbed, and the quality of the resulting deblurred images is hence degraded. Since every motion blur in a single exposure image can be represented by 2D parametric curves, we adopt a piecewise-linear model to approximate the curves for the reliable blur kernel estimation. The model is found to be an effective tradeoff between flexibility and robustness as it takes advantage of two extremes: (1) the generic model, represented by a discrete 2D function, which has a high degree of freedom (DOF) for the maximum flexibility but suffers from noise and (2) the linear model, which enhances robustness and simplicity but has limited expressiveness due to its low DOF. We evaluate several deblurring methods based on not only the generic model, but also the piecewise-linear model as an alternative. After analyzing the experiment results using real-world images with significant levels of noise and a benchmark data set, we conclude that the proposed model is not only robust with respect to noise, but also flexible in dealing with various types of blur.

  1. Automated 3D Motion Tracking using Gabor Filter Bank, Robust Point Matching, and Deformable Models

    PubMed Central

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

    2013-01-01

    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

  2. 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.

  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. 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.

  5. Joint Robust Transmit/Receive Adaptive Beamforming for MIMO Radar Using Probability-Constrained Optimization

    NASA Astrophysics Data System (ADS)

    Zhang, Weiyu; Vorobyov, Sergiy A.

    2016-01-01

    A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.

  6. A fast, robust, and simple implicit method for adaptive time-stepping on adaptive mesh-refinement grids

    NASA Astrophysics Data System (ADS)

    Commerçon, B.; Debout, V.; Teyssier, R.

    2014-03-01

    Context. Implicit solvers present strong limitations when used on supercomputing facilities and in particular for adaptive mesh-refinement codes. Aims: We present a new method for implicit adaptive time-stepping on adaptive mesh-refinement grids. We implement it in the radiation-hydrodynamics solver we designed for the RAMSES code for astrophysical purposes and, more particularly, for protostellar collapse. Methods: We briefly recall the radiation-hydrodynamics equations and the adaptive time-stepping methodology used for hydrodynamical solvers. We then introduce the different types of boundary conditions (Dirichlet, Neumann, and Robin) that are used at the interface between levels and present our implementation of the new method in the RAMSES code. The method is tested against classical diffusion and radiation-hydrodynamics tests, after which we present an application for protostellar collapse. Results: We show that using Dirichlet boundary conditions at level interfaces is a good compromise between robustness and accuracy and that it can be used in structure formation calculations. The gain in computational time over our former unique time step method ranges from factors of 5 to 50 depending on the level of adaptive time-stepping and on the problem. We successfully compare the old and new methods for protostellar collapse calculations that involve highly non linear physics. Conclusions: We have developed a simple but robust method for adaptive time-stepping of implicit scheme on adaptive mesh-refinement grids. It can be applied to a wide variety of physical problems that involve diffusion processes.

  7. 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

  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. Simple method for adaptive filtering of motion artifacts in E-textile wearable ECG sensors.

    PubMed

    Alkhidir, Tamador; Sluzek, Andrzej; Yapici, Murat Kaya

    2015-08-01

    In this paper, we have developed a simple method for adaptive out-filtering of the motion artifact from the electrocardiogram (ECG) obtained by using conductive textile electrodes. The textile electrodes were placed on the left and the right wrist to measure ECG through lead-1 configuration. The motion artifact was induced by simple hand movements. The reference signal for adaptive filtering was obtained by placing additional electrodes at one hand to capture the motion of the hand. The adaptive filtering was compared to independent component analysis (ICA) algorithm. The signal-to-noise ratio (SNR) for the adaptive filtering approach was higher than independent component analysis in most cases.

  10. Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

    PubMed

    Huang, X N; Ren, H P

    2016-01-01

    Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043

  11. Multivariable output feedback robust adaptive tracking control design for a class of delayed systems

    NASA Astrophysics Data System (ADS)

    Mirkin, Boris; Gutman, Per-Olof

    2015-02-01

    In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.

  12. 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

  13. Spatial orientation, adaptation, and motion sickness in real and virtual environments

    NASA Technical Reports Server (NTRS)

    Dizio, Paul; Lackner, James R.

    1992-01-01

    Reason and Brand (1975) noted that motion sickness occurs in many situations involving either passive body motion or active interaction with the world via indirect sensorimotor interfaces (e.g., prism spectacles). As might be expected, motion sickness is being reported in VEs that involve apparent self-motion through space, the best known examples being flight simulators (Kennedy et al., 1990). The goals of this paper are to introduce the motion-sickness symptomatology; to outline some concepts that are central to theories of motion sickness, spatial orientation, and adaptation; and to discuss the implications of some trends in VE research and development.

  14. Adaptive SVM fusion for robust multi-biometrics verification with missing data

    NASA Astrophysics Data System (ADS)

    Zhai, Xiuna; Zhao, Yan; Wang, Jingyan; Li, Yongping

    2013-03-01

    Conventional multimodal biometrics systems usually do not account for missing data (missing modalities or incomplete score lists) that is commonly encountered in real applications. The presence of missing data in multimodal biometric systems can be inconvenient to the client, as the system will reject the submitted biometric data and request for another trial. In such cases, robust multimodal biometric verification is needed. In this paper, we present the criteria, fusion method and performance metrics of a robust multimodal biometrics verification system that verifies the client's identity at any condition of data missing. A novel adaptive SVM classification method is proposed for missing dimensional values, which can handle the missing data in multimodal biometrics. We show that robust multibiometrics imposes additional requirements on multimodal fusion when compared to conventional multibiometrics. We also argue that the usual performance metrics of false accept and false reject rates are insufficient yardsticks for robust verification and propose new metrics against which we benchmark our system.

  15. Iterative Robust Capon Beamforming with Adaptively Updated Array Steering Vector Mismatch Levels

    PubMed Central

    Sun, Liguo

    2014-01-01

    The performance of the conventional adaptive beamformer is sensitive to the array steering vector (ASV) mismatch. And the output signal-to interference and noise ratio (SINR) suffers deterioration, especially in the presence of large direction of arrival (DOA) error. To improve the robustness of traditional approach, we propose a new approach to iteratively search the ASV of the desired signal based on the robust capon beamformer (RCB) with adaptively updated uncertainty levels, which are derived in the form of quadratically constrained quadratic programming (QCQP) problem based on the subspace projection theory. The estimated levels in this iterative beamformer present the trend of decreasing. Additionally, other array imperfections also degrade the performance of beamformer in practice. To cover several kinds of mismatches together, the adaptive flat ellipsoid models are introduced in our method as tight as possible. In the simulations, our beamformer is compared with other methods and its excellent performance is demonstrated via the numerical examples. PMID:27355008

  16. 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.

  17. Adaptive quarter-pel motion estimation and motion vector coding algorithm for the H.264/AVC standard

    NASA Astrophysics Data System (ADS)

    Jung, Seung-Won; Park, Chun-Su; Ha, Le Thanh; Ko, Sung-Jea

    2009-11-01

    We present an adaptive quarter-pel (Qpel) motion estimation (ME) method for H.264/AVC. Instead of applying Qpel ME to all macroblocks (MBs), the proposed method selectively performs Qpel ME in an MB level. In order to reduce the bit rate, we also propose a motion vector (MV) encoding technique that adaptively selects a different variable length coding (VLC) table according to the accuracy of the MV. Experimental results show that the proposed method can achieve about 3% average bit rate reduction.

  18. Fibre-coupled multiphoton microscope with adaptive motion compensation.

    PubMed

    Sherlock, Ben; Warren, Sean; Stone, James; Neil, Mark; Paterson, Carl; Knight, Jonathan; French, Paul; Dunsby, Chris

    2015-05-01

    To address the challenge of sample motion during in vivo imaging, we present a fibre-coupled multiphoton microscope with active axial motion compensation. The position of the sample surface is measured using optical coherence tomography and fed back to a piezo actuator that adjusts the axial location of the objective to compensate for sample motion. We characterise the system's performance and demonstrate that it can compensate for axial sample velocities up to 700 µm/s. Finally we illustrate the impact of motion compensation when imaging multiphoton excited autofluorescence in ex vivo mouse skin.

  19. Fibre-coupled multiphoton microscope with adaptive motion compensation

    PubMed Central

    Sherlock, Ben; Warren, Sean; Stone, James; Neil, Mark; Paterson, Carl; Knight, Jonathan; French, Paul; Dunsby, Chris

    2015-01-01

    To address the challenge of sample motion during in vivo imaging, we present a fibre-coupled multiphoton microscope with active axial motion compensation. The position of the sample surface is measured using optical coherence tomography and fed back to a piezo actuator that adjusts the axial location of the objective to compensate for sample motion. We characterise the system’s performance and demonstrate that it can compensate for axial sample velocities up to 700 µm/s. Finally we illustrate the impact of motion compensation when imaging multiphoton excited autofluorescence in ex vivo mouse skin. PMID:26137387

  20. 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.

  1. Cross-domain adaptation reveals that a common mechanism computes stereoscopic (cyclopean) and luminance plaid motion.

    PubMed

    Bowd, C; Donnelly, M; Shorter, S; Patterson, R

    2000-01-01

    Across three experiments, this study investigated the visual processing of moving stereoscopic plaid patterns (plaids created with cyclopean components defined by moving binocular disparity embedded in a dynamic random-dot stereogram). Results showed that adaptation to a moving stereoscopic plaid or its components affected the perceived coherence of a luminance test plaid, and vice versa. Cross-domain adaptation suggests that stereoscopic and luminance motion signals feed into a common pattern-motion mechanism, consistent with the idea that stereoscopic motion signals are computed early in the motion processing stream.

  2. 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,…

  3. 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

  4. Rapid Motion Adaptation Reveals the Temporal Dynamics of Spatiotemporal Correlation between ON and OFF Pathways

    PubMed Central

    Oluk, Can; Pavan, Andrea; Kafaligonul, Hulusi

    2016-01-01

    At the early stages of visual processing, information is processed by two major thalamic pathways encoding brightness increments (ON) and decrements (OFF). Accumulating evidence suggests that these pathways interact and merge as early as in primary visual cortex. Using regular and reverse-phi motion in a rapid adaptation paradigm, we investigated the temporal dynamics of within and across pathway mechanisms for motion processing. When the adaptation duration was short (188 ms), reverse-phi and regular motion led to similar adaptation effects, suggesting that the information from the two pathways are combined efficiently at early-stages of motion processing. However, as the adaption duration was increased to 752 ms, reverse-phi and regular motion showed distinct adaptation effects depending on the test pattern used, either engaging spatiotemporal correlation between the same or opposite contrast polarities. Overall, these findings indicate that spatiotemporal correlation within and across ON-OFF pathways for motion processing can be selectively adapted, and support those models that integrate within and across pathway mechanisms for motion processing. PMID:27667401

  5. 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.

  6. 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.

  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. 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. PMID:26892402

  9. The impact of head movements on EEG and contact impedance: an adaptive filtering solution for motion artifact reduction.

    PubMed

    Mihajlovic, Vojkan; Patki, Shrishail; Grundlehner, Bernard

    2014-01-01

    Designing and developing a comfortable and convenient EEG system for daily usage that can provide reliable and robust EEG signal, encompasses a number of challenges. Among them, the most ambitious is the reduction of artifacts due to body movements. This paper studies the effect of head movement artifacts on the EEG signal and on the dry electrode-tissue impedance (ETI), monitored continuously using the imec's wireless EEG headset. We have shown that motion artifacts have huge impact on the EEG spectral content in the frequency range lower than 20 Hz. Coherence and spectral analysis revealed that ETI is not capable of describing disturbances at very low frequencies (below 2 Hz). Therefore, we devised a motion artifact reduction (MAR) method that uses a combination of a band-pass filtering and multi-channel adaptive filtering (AF), suitable for real-time MAR. This method was capable of substantially reducing artifacts produced by head movements.

  10. Continuous motion decoding from EMG using independent component analysis and adaptive model training.

    PubMed

    Zhang, Qin; Xiong, Caihua; Chen, Wenbin

    2014-01-01

    Surface Electromyography (EMG) is popularly used to decode human motion intention for robot movement control. Traditional motion decoding method uses pattern recognition to provide binary control command which can only move the robot as predefined limited patterns. In this work, we proposed a motion decoding method which can accurately estimate 3-dimensional (3-D) continuous upper limb motion only from multi-channel EMG signals. In order to prevent the muscle activities from motion artifacts and muscle crosstalk which especially obviously exist in upper limb motion, the independent component analysis (ICA) was applied to extract the independent source EMG signals. The motion data was also transferred from 4-manifold to 2-manifold by the principle component analysis (PCA). A hidden Markov model (HMM) was proposed to decode the motion from the EMG signals after the model trained by an adaptive model identification process. Experimental data were used to train the decoding model and validate the motion decoding performance. By comparing the decoded motion with the measured motion, it is found that the proposed motion decoding strategy was feasible to decode 3-D continuous motion from EMG signals.

  11. 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.

  12. 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).

  13. A robust adaptive sampling method for faster acquisition of MR images.

    PubMed

    Vellagoundar, Jaganathan; Machireddy, Ramasubba Reddy

    2015-06-01

    A robust adaptive k-space sampling method is proposed for faster acquisition and reconstruction of MR images. In this method, undersampling patterns are generated based on magnitude profile of a fully acquired 2-D k-space data. Images are reconstructed using compressive sampling reconstruction algorithm. Simulation experiments are done to assess the performance of the proposed method under various signal-to-noise ratio (SNR) levels. The performance of the method is better than non-adaptive variable density sampling method when k-space SNR is greater than 10dB. The method is implemented on a fully acquired multi-slice raw k-space data and a quality assurance phantom data. Data reduction of up to 60% is achieved in the multi-slice imaging data and 75% is achieved in the phantom imaging data. The results show that reconstruction accuracy is improved over non-adaptive or conventional variable density sampling method. The proposed sampling method is signal dependent and the estimation of sampling locations is robust to noise. As a result, it eliminates the necessity of mathematical model and parameter tuning to compute k-space sampling patterns as required in non-adaptive sampling methods.

  14. 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.

  15. VSS Robust Adaptive Control Including a Self-Tuning Controller for a Rotary Inverted Pendulum

    NASA Astrophysics Data System (ADS)

    Hirata, Hiroshi; Takabe, Tomohiro; Anabuki, Masatoshi; Ouchi, Shigeto

    So many papers with respect to the stabilization of the inverted pendulum are reported, because it is typically unstable system and is well used as example to verify many control theories. However, few approaches consider the inverted pendulum as unknown parameter system. This paper proposes a new VSS (Variable Structure System) robust adaptive control system including a self-tuning controller for a rotary inverted pendulum whose whole parameters are unknown. The control system prepares two kinds of adaptive controllers, and the stabilization of inverted pendulum is achieved by separating the system to two parts of the pendulum and the rotary arm. The rotational angle of the pendulum is stabilized by tracking type's VSS adaptive control method, and the rotary arm is simultaneously stabilized by STC (self-tuning control) system that assures the boundary reference angle of the pendulum. It is then not sufficient to construct STC system by using only adjustable parameter of VSS adaptive control system. Therefore, whole basic parameters are recursively estimated in order to realize STC system by using least squares parameter adaptive law, and it is achieved by superposing the perturbation signal to the stable adaptive control input on limited short interval. Furthermore, STC system designs LQ controller by developing an efficient QR method for real time operation. Finally, the validity of the proposed system is demonstrated through some numerical simulations and practical experimental result.

  16. 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.

  17. 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. PMID:24574910

  18. 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

  19. 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.

  20. Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

    PubMed

    Ye, Jinzuo; Chi, Chongwei; Xue, Zhenwen; Wu, Ping; An, Yu; Xu, Han; Zhang, Shuang; Tian, Jie

    2014-02-01

    Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

  1. Reduction of skin stretch induced motion artifacts in electrocardiogram monitoring using adaptive filtering.

    PubMed

    Liu, Yan; Pecht, Michael G

    2006-01-01

    The effectiveness of electrocardiogram (ECG) monitors can be significantly impaired by motion artifacts which can cause misdiagnoses, lead to inappropriate treatment decisions, and trigger false alarms. Skin stretch associated with patient motion is a significant source of motion artifacts in current ECG monitoring. In this study, motion artifacts are adaptively filtered by using skin strain as the reference variable. Skin strain is measured non-invasively using a light emitting diode (LED) and an optical sensor incorporated in an ECG electrode. The results demonstrate that this device and method can significantly reduce skin strain induced ECG artifacts.

  2. 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

  3. 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

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

    PubMed

    Williams, Caroline M; Watanabe, Miki; Guarracino, Mario R; Ferraro, Maria B; Edison, Arthur S; Morgan, Theodore J; Boroujerdi, Arezue F B; Hahn, Daniel A

    2014-12-01

    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 nuclear magnetic resonance (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.

  5. 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

  6. Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks.

    PubMed

    Briat, Corentin; Gupta, Ankit; Khammash, Mustafa

    2016-01-27

    The ability to adapt to stimuli is a defining feature of many biological systems and critical to maintaining homeostasis. While it is well appreciated that negative feedback can be used to achieve homeostasis when networks behave deterministically, the effect of noise on their regulatory function is not understood. Here, we combine probability and control theory to develop a theory of biological regulation that explicitly takes into account the noisy nature of biochemical reactions. We introduce tools for the analysis and design of robust homeostatic circuits and propose a new regulation motif, which we call antithetic integral feedback. This motif exploits stochastic noise, allowing it to achieve precise regulation in scenarios where similar deterministic regulation fails. Specifically, antithetic integral feedback preserves the stability of the overall network, steers the population of any regulated species to a desired set point, and adapts perfectly. We suggest that this motif may be prevalent in endogenous biological circuits and useful when creating synthetic circuits. PMID:27136686

  7. 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.

  8. Robust velocity computation from a biologically motivated model of motion perception

    PubMed Central

    Johnston, A.; McOwan, P. W.; Benton, C. P.

    1999-01-01

    Current computational models of motion processing in the primate motion pathway do not cope well with image sequences in which a moving pattern is superimposed upon a static texture. The use of non-linear operations and the need for contrast normalization in motion models mean that the separation of the influences of moving and static patterns on the motion computation is not trivial. Therefore, the response to the superposition of static and moving patterns provides an important means of testing various computational strategies. Here we describe a computational model of motion processing in the visual cortex, one of the advantages of which is that it is highly resistant to interference from static patterns.

  9. Tactile Motion Adaptation Reduces Perceived Speed but Shows No Evidence of Direction Sensitivity

    PubMed Central

    McIntyre, Sarah; Holcombe, Alex O.; Birznieks, Ingvars; Seizova-Cajic, Tatjana

    2012-01-01

    Introduction While the directionality of tactile motion processing has been studied extensively, tactile speed processing and its relationship to direction is little-researched and poorly understood. We investigated this relationship in humans using the ‘tactile speed aftereffect’ (tSAE), in which the speed of motion appears slower following prolonged exposure to a moving surface. Method We used psychophysical methods to test whether the tSAE is direction sensitive. After adapting to a ridged moving surface with one hand, participants compared the speed of test stimuli on the adapted and unadapted hands. We varied the direction of the adapting stimulus relative to the test stimulus. Results Perceived speed of the surface moving at 81 mms−1 was reduced by about 30% regardless of the direction of the adapting stimulus (when adapted in the same direction, Mean reduction = 23 mms−1, SD = 11; with opposite direction, Mean reduction = 26 mms−1, SD = 9). In addition to a large reduction in perceived speed due to adaptation, we also report that this effect is not direction sensitive. Conclusions Tactile motion is susceptible to speed adaptation. This result complements previous reports of reliable direction aftereffects when using a dynamic test stimulus as together they describe how perception of a moving stimulus in touch depends on the immediate history of stimulation. Given that the tSAE is not direction sensitive, we argue that peripheral adaptation does not explain it, because primary afferents are direction sensitive with friction-creating stimuli like ours (thus motion in their preferred direction should result in greater adaptation, and if perceived speed were critically dependent on these afferents’ response intensity, the tSAE should be direction sensitive). The adaptation that reduces perceived speed therefore seems to be of central origin. PMID:23029010

  10. Adaptive step-size strategy for noise-robust Fourier ptychographic microscopy.

    PubMed

    Zuo, Chao; Sun, Jiasong; Chen, Qian

    2016-09-01

    The incremental gradient approaches, such as PIE and ePIE, are widely used in the field of ptychographic imaging due to their great flexibility and computational efficiency. Nevertheless, their stability and reconstruction quality may be significantly degraded when non-negligible noise is present in the image. Though this problem is often attributed to the non-convex nature of phase retrieval, we found the reason for this is more closely related to the choice of the step-size, which needs to be gradually diminishing for convergence even in the convex case. To this end, we introduce an adaptive step-size strategy that decreases the step-size whenever sufficient progress is not made. The synthetic and real experiments on Fourier ptychographic microscopy show that the adaptive step-size strategy significantly improves the stability and robustness of the reconstruction towards noise yet retains the fast initial convergence speed of PIE and ePIE. More importantly, the proposed approach is simple, nonparametric, and does not require any preknowledge about the noise statistics. The great performance and limited computational complexity make it a very attractive and promising technique for robust Fourier ptychographic microscopy under noisy conditions. PMID:27607676

  11. Adaptive robust stabilisation for a class of uncertain nonlinear time-delay dynamical systems

    NASA Astrophysics Data System (ADS)

    Wu, Hansheng

    2013-02-01

    The problem of adaptive robust stabilisation is considered for a class of uncertain nonlinear dynamical systems with multiple time-varying delays. It is assumed that the upper bounds of the nonlinear delayed state perturbations are unknown and that the time-varying delays are any non-negative continuous and bounded functions which do not require that their derivatives have to be less than one. In particular, it is only required that the nonlinear uncertainties, which can also include time-varying delays, are bounded in any non-negative nonlinear functions which are not required to be known for the system designer. For such a class of uncertain nonlinear time-delay systems, a new method is presented whereby a class of continuous memoryless adaptive robust state feedback controllers with a rather simpler structure is proposed. It is also shown that the solutions of uncertain nonlinear time-delay systems can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, as an application, an uncertain nonlinear time-delay ecosystem with two competing species is given to demonstrate the validity of the results.

  12. 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.

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

    PubMed Central

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

    2016-01-01

    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. PMID:27399704

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

    PubMed

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

    2016-01-01

    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. PMID:27399704

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

    PubMed

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

    2016-01-01

    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.

  16. 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.

  17. 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

  18. 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.

  19. 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. PMID:19423437

  20. 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.

  1. Prostate Intrafraction Motion Assessed by Simultaneous kV Fluoroscopy at MV Delivery II: Adaptive Strategies

    SciTech Connect

    Adamson, Justus; Wu Qiuwen

    2010-12-01

    Purpose: To investigate potential benefits of adaptive strategies for managing prostate intrafractional uncertainties when interfraction motion is corrected online. Methods and Materials: Prostate intrafraction motion was measured using kV fluoroscopy during MV delivery for 571 fractions from 30 hypofractionated radiotherapy patients. We evaluated trending over treatment course using analysis of variance statistics, and we evaluated the ability to correct patient-specific systematic error and apply patient-specific statistical margins after 2 to 15 fractions to compensate 90% of motion. We also evaluated the ability to classify patients into small- and large-motion subgroups based on the first 2 to 20 fractions using discriminant analysis. Results: No time trend was observed over treatment course, and intrafraction motion was patient specific (p < 0.0001). Systematic error in the first week correlated well with that in subsequent weeks, with correlation coefficients of 0.53, 0.50, and 0.41 in right-left (RL), anterior-posterior (AP), and superior-inferior (SI), respectively. After 5 fractions, the adaptive strategy resulted in average margin reductions of 0.3, 0.7, and 0.7 mm in RL, AP, and SI, respectively, with margins ranging from 1 to 3.2 mm in RL, 2 to 7.0 mm in AP, and 2 to 6.6 mm in SI. By contrast, population margins to include the same percentage of motion were 1.7, 4.0, and 4.1 mm. After 2 and 5 fractions, patients were classified into small- and large-motion groups with {approx}77% and {approx}83% accuracy. Conclusions: Adaptive strategies are feasible and beneficial for intrafraction motion management in prostate cancer online image guidance. Patients may be classified into large- and small-motion groups in early fractions using discriminant analysis.

  2. Design of a motion JPEG (M/JPEG) adapter card

    NASA Astrophysics Data System (ADS)

    Lee, D. H.; Sudharsanan, Subramania I.

    1994-05-01

    In this paper we describe a design of a high performance JPEG (Joint Photographic Experts Group) Micro Channel adapter card. The card, tested on a range of PS/2 platforms (models 50 to 95), can complete JPEG operations on a 640 by 240 pixel image within 1/60 of a second, thus enabling real-time capture and display of high quality digital video. The card accepts digital pixels for either a YUV 4:2:2 or an RGB 4:4:4 pixel bus and has been shown to handle up to 2.05 MBytes/second of compressed data. The compressed data is transmitted to a host memory area by Direct Memory Access operations. The card uses a single C-Cube's CL550 JPEG processor that complies with the baseline JPEG. We give broad descriptions of the hardware that controls the video interface, CL550, and the system interface. Some critical design points that enhance the overall performance of the M/JPEG systems are pointed out. The control of the adapter card is achieved by an interrupt driven software that runs under DOS. The software performs a variety of tasks that include change of color space (RGB or YUV), change of quantization and Huffman tables, odd and even field control and some diagnostic operations.

  3. 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.

  4. 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.

  5. 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.

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

    PubMed

    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.

  7. 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.

  8. Robust sensorimotor representation to physical interaction changes in humanoid motion learning.

    PubMed

    Shimizu, Toshihiko; Saegusa, Ryo; Ikemoto, Shuhei; Ishiguro, Hiroshi; Metta, Giorgio

    2015-05-01

    This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply this knowledge during different physical interactions between a robot and its surroundings. The phase transfer sequence represents the temporal order of the changing points in multiple time sequences. It encodes the dynamical aspects of the sequences so as to absorb the gaps in timing and amplitude derived from interaction changes. The phase transfer sequence was evaluated in reinforcement learning of sitting-up and walking motions conducted by a real humanoid robot and compatible simulator. In both tasks, the robotic motions were less dependent on physical interactions when learned by the proposed feature than by conventional similarity measurements. Phase transfer sequence also enhanced the convergence speed of motion learning. Our proposed feature is original primarily because it absorbs the gaps caused by changes of the originally acquired physical interactions, thereby enhancing the learning speed in subsequent interactions.

  9. Robust sensorimotor representation to physical interaction changes in humanoid motion learning.

    PubMed

    Shimizu, Toshihiko; Saegusa, Ryo; Ikemoto, Shuhei; Ishiguro, Hiroshi; Metta, Giorgio

    2015-05-01

    This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply this knowledge during different physical interactions between a robot and its surroundings. The phase transfer sequence represents the temporal order of the changing points in multiple time sequences. It encodes the dynamical aspects of the sequences so as to absorb the gaps in timing and amplitude derived from interaction changes. The phase transfer sequence was evaluated in reinforcement learning of sitting-up and walking motions conducted by a real humanoid robot and compatible simulator. In both tasks, the robotic motions were less dependent on physical interactions when learned by the proposed feature than by conventional similarity measurements. Phase transfer sequence also enhanced the convergence speed of motion learning. Our proposed feature is original primarily because it absorbs the gaps caused by changes of the originally acquired physical interactions, thereby enhancing the learning speed in subsequent interactions. PMID:25029488

  10. Dynamic recurrent neural networks for stable adaptive control of wing rock motion

    NASA Astrophysics Data System (ADS)

    Kooi, Steven Boon-Lam

    Wing rock is a self-sustaining limit cycle oscillation (LCO) which occurs as the result of nonlinear coupling between the dynamic response of the aircraft and the unsteady aerodynamic forces. In this thesis, dynamic recurrent RBF (Radial Basis Function) network control methodology is proposed to control the wing rock motion. The concept based on the properties of the Presiach hysteresis model is used in the design of dynamic neural networks. The structure and memory mechanism in the Preisach model is analogous to the parallel connectivity and memory formation in the RBF neural networks. The proposed dynamic recurrent neural network has a feature for adding or pruning the neurons in the hidden layer according to the growth criteria based on the properties of ensemble average memory formation of the Preisach model. The recurrent feature of the RBF network deals with the dynamic nonlinearities and endowed temporal memories of the hysteresis model. The control of wing rock is a tracking problem, the trajectory starts from non-zero initial conditions and it tends to zero as time goes to infinity. In the proposed neural control structure, the recurrent dynamic RBF network performs identification process in order to approximate the unknown non-linearities of the physical system based on the input-output data obtained from the wing rock phenomenon. The design of the RBF networks together with the network controllers are carried out in discrete time domain. The recurrent RBF networks employ two separate adaptation schemes where the RBF's centre and width are adjusted by the Extended Kalman Filter in order to give a minimum networks size, while the outer networks layer weights are updated using the algorithm derived from Lyapunov stability analysis for the stable closed loop control. The issue of the robustness of the recurrent RBF networks is also addressed. The effectiveness of the proposed dynamic recurrent neural control methodology is demonstrated through simulations to

  11. Analysis of the Accuracy and Robustness of the Leap Motion Controller

    PubMed Central

    Weichert, Frank; Bachmann, Daniel; Rudak, Bartholomäus; Fisseler, Denis

    2013-01-01

    The Leap Motion Controller is a new device for hand gesture controlled user interfaces with declared sub-millimeter accuracy. However, up to this point its capabilities in real environments have not been analyzed. Therefore, this paper presents a first study of a Leap Motion Controller. The main focus of attention is on the evaluation of the accuracy and repeatability. For an appropriate evaluation, a novel experimental setup was developed making use of an industrial robot with a reference pen allowing a position accuracy of 0.2 mm. Thereby, a deviation between a desired 3D position and the average measured positions below 0.2 mm has been obtained for static setups and of 1.2 mm for dynamic setups. Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction. PMID:23673678

  12. Analysis of the accuracy and robustness of the leap motion controller.

    PubMed

    Weichert, Frank; Bachmann, Daniel; Rudak, Bartholomäus; Fisseler, Denis

    2013-05-14

    The Leap Motion Controller is a new device for hand gesture controlled user interfaces with declared sub-millimeter accuracy. However, up to this point its capabilities in real environments have not been analyzed. Therefore, this paper presents a first study of a Leap Motion Controller. The main focus of attention is on the evaluation of the accuracy and repeatability. For an appropriate evaluation, a novel experimental setup was developed making use of an industrial robot with a reference pen allowing a position accuracy of 0.2 mm. Thereby, a deviation between a desired 3D position and the average measured positions below 0.2 mm has been obtained for static setups and of 1.2 mm for dynamic setups. Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Robust adaptive control modeling of human arm movements subject to altered gravity and mechanical loads

    NASA Astrophysics Data System (ADS)

    Tryfonidis, Michail

    It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that

  19. 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

  20. Fast subpel motion estimation for H.264/advanced video coding with an adaptive motion vector accuracy decision

    NASA Astrophysics Data System (ADS)

    Lee, Hoyoung; Jung, Bongsoo; Jung, Jooyoung; Jeon, Byeungwoo

    2012-11-01

    The quarter-pel motion vector accuracy supported by H.264/advanced video coding (AVC) in motion estimation (ME) and compensation (MC) provides high compression efficiency. However, it also increases the computational complexity. While various well-known fast integer-pel ME methods are already available, lack of a good, fast subpel ME method results in problems associated with relatively high computational complexity. This paper presents one way of solving the complexity problem of subpel ME by making adaptive motion vector (MV) accuracy decisions in inter-mode selection. The proposed MV accuracy decision is made using inter-mode selection of a macroblock with two decision criteria. Pixels are classified as stationary (and/or homogeneous) or nonstationary (and/or nonhomogeneous). In order to avoid unnecessary interpolation and processing, a proper subpel ME level is chosen among four different combinations, each of which has a different MV accuracy and number of subpel ME iterations based on the classification. Simulation results using an open source x264 software encoder show that without any noticeable degradation (by -0.07 dB on average), the proposed method reduces total encoding time and subpel ME time, respectively, by 51.78% and by 76.49% on average, as compared to the conventional full-pel pixel search.

  1. 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.

  2. 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.

  3. 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.

  4. Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection.

    PubMed

    Su, Hai; Xing, Fuyong; Yang, Lin

    2016-06-01

    Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96.

  5. Robust adaptive control for a hybrid solid oxide fuel cell system

    NASA Astrophysics Data System (ADS)

    Snyder, Steven

    2011-12-01

    Solid oxide fuel cells (SOFCs) are electrochemical energy conversion devices. They offer a number of advantages beyond those of most other fuel cells due to their high operating temperature (800-1000°C), such as internal reforming, heat as a byproduct, and faster reaction kinetics without precious metal catalysts. Mitigating fuel starvation and improving load-following capabilities of SOFC systems are conflicting control objectives. However, this can be resolved by the hybridization of the system with an energy storage device, such as an ultra-capacitor. In this thesis, a steady-state property of the SOFC is combined with an input-shaping method in order to address the issue of fuel starvation. Simultaneously, an overall adaptive system control strategy is employed to manage the energy sharing between the elements as well as to maintain the state-of-charge of the energy storage device. The adaptive control method is robust to errors in the fuel cell's fuel supply system and guarantees that the fuel cell current and ultra-capacitor state-of-charge approach their target values and remain uniformly, ultimately bounded about these target values. Parameter saturation is employed to guarantee boundedness of the parameters. The controller is validated through hardware-in-the-loop experiments as well as computer simulations.

  6. Efficient low-bit-rate adaptive mesh-based motion compensation technique

    NASA Astrophysics Data System (ADS)

    Mahmoud, Hanan A.; Bayoumi, Magdy A.

    2001-08-01

    This paper proposes a two-stage global motion estimation method using a novel quadtree block-based motion estimation technique and an active mesh model. In the first stage, motion parameters are estimated by fitting block-based motion vectors computed using a new efficient quadtree technique, that divides a frame into equilateral triangle blocks using the quad-tree structure. Arbitrary partition shapes are achieved by allowing 4-to-1, 3-to-1 and 2-1 merge/combine of sibling blocks having the same motion vector . In the second stage, the mesh is constructed using an adaptive triangulation procedure that places more triangles over areas with high motion content, these areas are estimated during the first stage. finally the motion compensation is achieved by using a novel algorithm that is carried by both the encoder and the decoder to determine the optimal triangulation of the resultant partitions followed by affine mapping at the encoder. Computer simulation results show that the proposed method gives better performance that the conventional ones in terms of the peak signal-to-noise ration (PSNR) and the compression ratio (CR).

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

    PubMed Central

    Lu, George J.; Opella, Stanley J.

    2013-01-01

    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. PMID:24006989

  8. A saliency based motion detection model of visual system considering visual adaptation properties.

    PubMed

    Kodama, Mitsuhiro; Kohama, Takeshi; Yoshida, Hisashi

    2015-01-01

    The purpose of this study is to construct a mathematical model which predicts saliency regions in high-speed egocentric-motion movies, filmed by an embedded camera in a driving vehicle, by reproducing the characteristics of the area MT and MST neurons' receptive fields with consideration of visual adaptation properties. The area MT neurons integrate from the area V1 activation and respond well to regions where higher motion contrasts exist. While the area MST neurons detect global motions such as expansion, contraction, rotation, and so on. We modeled the area MT neurons' receptive fields as a center-surround spatial summation of counter sided motion vectors of visual scenery. The area MST neurons in our model integrate the responses of the MT neurons by convolving with spacial weight functions of which central portions are biased to preferred direction. Visual adaptations were taken as the primary delay filters for each visual feature channel to deplete the saliency of stationary objects and regions during particular frames. The simulation results for the movies which were taken in a running vehicle indicate that the proposed model detects more salient objects around the vanishing point than the conventional saliency based model. To evaluate the performance of proposed model, we defined the moving-NSS (normalized scan-path salience) scores as the averaged NSS scores in each moving time window. The moving-NSS scores for motion images of our model were higher than those of the conventional model. PMID:26737820

  9. 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. PMID:27106581

  10. Use of power-line interference for adaptive motion artifact removal in biopotential measurements.

    PubMed

    Xu, Lin; Rooijakkers, Michael J; Rabotti, Chiara; Peuscher, Jan; Mischi, Massimo

    2016-01-01

    Motion artifacts (MA) have long been a problem in biopotential measurements. Adaptive filtering is widely used for optimal noise removal in many biomedical applications. However, the existing adaptive filtering methods involve the use of additional sensors, limiting the applicability of adaptive filtering for MA reduction. In the present study, a novel adaptive filtering method without need for additional sensors is proposed. In biopotential measurements, movement of the electrodes and their leads may cause variations not only in the skin and half-cell potential (motion artifacts), but also in the electrode-skin impedance. Such impedance variations may also cause power-line interference modulation (PLIM), resulting in additional spectral components around the power-line interference (PLI) in the frequency domain. Demodulation of the PLI may reflect the movement-induced electrode-skin impedance variation, and can therefore represent a reference signal for the adaptive filter. Preliminary validation on ECG measurements with seven volunteers showed a high correlation coefficient (R  =  0.97) between MA and PLIM, and excellent MA removal by the proposed adaptive filter, possibly leading to improved analysis of biopotential signals. PMID:26641265

  11. Robustness of one-dimensional viscous fluid motion under multidimensional perturbations

    NASA Astrophysics Data System (ADS)

    Feireisl, Eduard; Sun, Yongzhong

    2015-12-01

    We adapt the relative energy functional associated to the compressible Navier-Stokes system to show stability of solutions emanating from 1-D initial data with respect to multidimensional N = 2, 3 perturbations. Besides the application of the relative energy inequality as a suitable "distance" between two solutions, refined regularity estimates in Lp based Sobolev spaces are used.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  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. PMID:23685285

  18. 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

  19. Adaptation to visual or auditory time intervals modulates the perception of visual apparent motion

    PubMed Central

    Zhang, Huihui; Chen, Lihan; Zhou, Xiaolin

    2012-01-01

    It is debated whether sub-second timing is subserved by a centralized mechanism or by the intrinsic properties of task-related neural activity in specific modalities (Ivry and Schlerf, 2008). By using a temporal adaptation task, we investigated whether adapting to different time intervals conveyed through stimuli in different modalities (i.e., frames of a visual Ternus display, visual blinking discs, or auditory beeps) would affect the subsequent implicit perception of visual timing, i.e., inter-stimulus interval (ISI) between two frames in a Ternus display. The Ternus display can induce two percepts of apparent motion (AM), depending on the ISI between the two frames: “element motion” for short ISIs, in which the endmost disc is seen as moving back and forth while the middle disc at the overlapping or central position remains stationary; “group motion” for longer ISIs, in which both discs appear to move in a manner of lateral displacement as a whole. In Experiment 1, participants adapted to either the typical “element motion” (ISI = 50 ms) or the typical “group motion” (ISI = 200 ms). In Experiments 2 and 3, participants adapted to a time interval of 50 or 200 ms through observing a series of two paired blinking discs at the center of the screen (Experiment 2) or hearing a sequence of two paired beeps (with pitch 1000 Hz). In Experiment 4, participants adapted to sequences of paired beeps with either low pitches (500 Hz) or high pitches (5000 Hz). After adaptation in each trial, participants were presented with a Ternus probe in which the ISI between the two frames was equal to the transitional threshold of the two types of motions, as determined by a pretest. Results showed that adapting to the short time interval in all the situations led to more reports of “group motion” in the subsequent Ternus probes; adapting to the long time interval, however, caused no aftereffect for visual adaptation but significantly more reports of group motion for

  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. Motion Estimation Based on Mutual Information and Adaptive Multi-Scale Thresholding.

    PubMed

    Xu, Rui; Taubman, David; Naman, Aous Thabit

    2016-03-01

    This paper proposes a new method of calculating a matching metric for motion estimation. The proposed method splits the information in the source images into multiple scale and orientation subbands, reduces the subband values to a binary representation via an adaptive thresholding algorithm, and uses mutual information to model the similarity of corresponding square windows in each image. A moving window strategy is applied to recover a dense estimated motion field whose properties are explored. The proposed matching metric is a sum of mutual information scores across space, scale, and orientation. This facilitates the exploitation of information diversity in the source images. Experimental comparisons are performed amongst several related approaches, revealing that the proposed matching metric is better able to exploit information diversity, generating more accurate motion fields.

  2. An Investigation of the Robustness of a Partial Credit Model-Based Computerized Adaptive Test to Misfitting Items.

    ERIC Educational Resources Information Center

    De Ayala, R. J.; And Others

    The robustness of a partial credit (PC) model-based computerized adaptive test's (CAT's) ability estimation to items that did not fit the PC model was investigated. A CAT program was written based on the PC model. The program used maximum likelihood estimation of ability. Item selection was on the basis of information. The simulation terminated…

  3. 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.

  4. 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.

  5. 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.

  6. Respiratory motion prediction by using the adaptive neuro fuzzy inference system (ANFIS)

    NASA Astrophysics Data System (ADS)

    Kakar, Manish; Nyström, Håkan; Rye Aarup, Lasse; Jakobi Nøttrup, Trine; Rune Olsen, Dag

    2005-10-01

    The quality of radiation therapy delivered for treating cancer patients is related to set-up errors and organ motion. Due to the margins needed to ensure adequate target coverage, many breast cancer patients have been shown to develop late side effects such as pneumonitis and cardiac damage. Breathing-adapted radiation therapy offers the potential for precise radiation dose delivery to a moving target and thereby reduces the side effects substantially. However, the basic requirement for breathing-adapted radiation therapy is to track and predict the target as precisely as possible. Recent studies have addressed the problem of organ motion prediction by using different methods including artificial neural network and model based approaches. In this study, we propose to use a hybrid intelligent system called ANFIS (the adaptive neuro fuzzy inference system) for predicting respiratory motion in breast cancer patients. In ANFIS, we combine both the learning capabilities of a neural network and reasoning capabilities of fuzzy logic in order to give enhanced prediction capabilities, as compared to using a single methodology alone. After training ANFIS and checking for prediction accuracy on 11 breast cancer patients, it was found that the RMSE (root-mean-square error) can be reduced to sub-millimetre accuracy over a period of 20 s provided the patient is assisted with coaching. The average RMSE for the un-coached patients was 35% of the respiratory amplitude and for the coached patients 6% of the respiratory amplitude.

  7. 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

  8. 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

  9. 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

  10. 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.

  11. Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

    PubMed

    Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

    2014-11-01

    This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system. PMID:25330468

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

    PubMed

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

    2016-04-21

    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.

  13. 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.

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

    PubMed

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

    2016-04-21

    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

  15. Motion-adaptive model-assisted compatible coding with spatiotemporal scalability

    NASA Astrophysics Data System (ADS)

    Lee, JaeBeom; Eleftheriadis, Alexandros

    1997-01-01

    We introduce the concept of motion adaptive spatio-temporal model-assisted compatible (MA-STMAC) coding, a technique to selectively encode areas of different importance to the human eye in terms of space and time in moving images with the consideration of object motion. PRevious STMAC was proposed base don the fact that human 'eye contact' and 'lip synchronization' are very important in person-to-person communication. Several areas including the eyes and lips need different types of quality, since different areas have different perceptual significance to human observers. The approach provides a better rate-distortion tradeoff than conventional image coding techniques base don MPEG-1, MPEG- 2, H.261, as well as H.263. STMAC coding is applied on top of an encoder, taking full advantage of its core design. Model motion tracking in our previous STMAC approach was not automatic. The proposed MA-STMAC coding considers the motion of the human face within the STMAC concept using automatic area detection. Experimental results are given using ITU-T H.263, addressing very low bit-rate compression.

  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. 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

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

    PubMed

    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

  19. 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

  20. 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.

  1. Motion artifact reduction in electrocardiogram using adaptive filtering based on half cell potential monitoring.

    PubMed

    Ko, Byung-hoon; Lee, Takhyung; Choi, Changmok; Kim, Youn-ho; Park, Gunguk; Kang, KyoungHo; Bae, Sang Kon; Shin, Kunsoo

    2012-01-01

    The electrocardiogram (ECG) is the main measurement parameter for effectively diagnosing chronic disease and guiding cardio-fitness therapy. ECGs contaminated by noise or artifacts disrupt the normal functioning of the automatic analysis algorithm. The objective of this study is to evaluate a method of measuring the HCP variation in motion artifacts through direct monitoring. The proposed wearable sensing device has two channels. One channel is used to measure the ECG through a differential amplifier. The other is for monitoring motion artifacts using the modified electrode and the same differential amplifier. Noise reduction was performed using adaptive filtering, based on a reference signal highly correlated with it. Direct measurement of HCP variations can eliminate the need for additional sensors. PMID:23366209

  2. 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.

  3. Aftereffect of motion-in-depth based on binocular cues: Effects of adaptation duration, interocular correlation, and temporal correlation.

    PubMed

    Sakano, Yuichi; Allison, Robert S

    2014-07-24

    There are at least two possible binocular cues to motion-in-depth, namely disparity change over time and interocular velocity differences. There has been significant controversy about their relative contributions to the perception of motion-in-depth. In the present study, we used the technique of selective adaptation to address this question. In Experiment 1, we found that adaptation to motion-in-depth depicted by temporally correlated random-dot stereograms, which contained coherent interocular velocity difference, produced motion aftereffect in the depth direction irrespective of the adaptors' interocular correlation for any adaptation duration tested. This suggests that coherent changing disparity does not contribute to motion-in-depth adaptation. Because the aftereffect duration did not saturate in the tested range of adaptation duration, it is unlikely that the lack of the effect of changing disparity was due to a ceiling effect. In Experiment 2, we used a novel adaptor that contained a unidirectional coherent interocular velocity difference signal and a bidirectional changing disparity signal that should not induce a motion aftereffect in depth. Following the adaptation, motion aftereffect in depth occurred in the opposite direction to the adaptor's motion-in-depth based on interocular velocity difference. Experiment 3 demonstrated that these results generalized in 12 untrained subjects. These experiments suggest that the contribution of interocular velocity difference to the perception of motion-in-depth is substantial, while that of changing disparity is very limited (if any), at least at the stages of direction-selective mechanisms subject to an aftereffect phenomenon.

  4. 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.

  5. Adaptive Position/Attitude Tracking Control of Aerial Robot With Unknown Inertial Matrix Based on a New Robust Neural Identifier.

    PubMed

    Lai, Guanyu; Liu, Zhi; Zhang, Yun; Chen, C L Philip

    2016-01-01

    This paper presents a novel adaptive controller for controlling an autonomous helicopter with unknown inertial matrix to asymptotically track the desired trajectory. To identify the unknown inertial matrix included in the attitude dynamic model, this paper proposes a new structural identifier that differs from those previously proposed in that it additionally contains a neural networks (NNs) mechanism and a robust adaptive mechanism, respectively. Using the NNs to compensate the unknown aerodynamic forces online and the robust adaptive mechanism to cancel the combination of the overlarge NNs compensation error and the external disturbances, the new robust neural identifier exhibits a better identification performance in the complex flight environment. Moreover, an optimized algorithm is included in the NNs mechanism to alleviate the burdensome online computation. By the strict Lyapunov argument, the asymptotic convergence of the inertial matrix identification error, position tracking error, and attitude tracking error to arbitrarily small neighborhood of the origin is proved. The simulation and implementation results are provided to evaluate the performance of the proposed controller. PMID:25794402

  6. A Fast and Robust Poisson-Boltzmann Solver Based on Adaptive Cartesian Grids.

    PubMed

    Boschitsch, Alexander H; Fenley, Marcia O

    2011-05-10

    An adaptive Cartesian grid (ACG) concept is presented for the fast and robust numerical solution of the 3D Poisson-Boltzmann Equation (PBE) governing the electrostatic interactions of large-scale biomolecules and highly charged multi-biomolecular assemblies such as ribosomes and viruses. The ACG offers numerous advantages over competing grid topologies such as regular 3D lattices and unstructured grids. For very large biological molecules and multi-biomolecule assemblies, the total number of grid-points is several orders of magnitude less than that required in a conventional lattice grid used in the current PBE solvers thus allowing the end user to obtain accurate and stable nonlinear PBE solutions on a desktop computer. Compared to tetrahedral-based unstructured grids, ACG offers a simpler hierarchical grid structure, which is naturally suited to multigrid, relieves indirect addressing requirements and uses fewer neighboring nodes in the finite difference stencils. Construction of the ACG and determination of the dielectric/ionic maps are straightforward, fast and require minimal user intervention. Charge singularities are eliminated by reformulating the problem to produce the reaction field potential in the molecular interior and the total electrostatic potential in the exterior ionic solvent region. This approach minimizes grid-dependency and alleviates the need for fine grid spacing near atomic charge sites. The technical portion of this paper contains three parts. First, the ACG and its construction for general biomolecular geometries are described. Next, a discrete approximation to the PBE upon this mesh is derived. Finally, the overall solution procedure and multigrid implementation are summarized. Results obtained with the ACG-based PBE solver are presented for: (i) a low dielectric spherical cavity, containing interior point charges, embedded in a high dielectric ionic solvent - analytical solutions are available for this case, thus allowing rigorous

  7. Robustness and adaptation reveal plausible cell cycle controlling subnetwork in Saccharomyces cerevisiae.

    PubMed

    Huang, Jiun-Yan; Huang, Chi-Wei; Kao, Kuo-Ching; Lai, Pik-Yin

    2013-04-10

    Biological systems are often organized spatially and temporally by multi-scale functional subsystems (modules). A specific subcellular process often corresponds to a subsystem composed of some of these interconnected modules. Accurate identification of system-level modularity organization from the large scale networks can provide valuable information on subsystem models of subcellular processes or physiological phenomena. Computational identification of functional modules from the large scale network is the key approach to solve the complexity of modularity in the past decade, but the overlapping and multi-scale nature of modules often renders unsatisfactory results in these methods. Most current methods for modularity detection are optimization-based and suffered from the drawback of size resolution limit. It is difficult to trace the origin of the unsatisfactory results, which may be due to poor data, inappropriate objective function selection or simply resulted from natural evolution, and hence no system-level accurate modular models for subcellular processes can be offered. Motivated by the idea of evolution with robustness and adaption as guiding principles, we propose a novel approach that can identify significant multi-scale overlapping modules that are sufficiently accurate at the system and subsystem levels, giving biological insights for subcellular processes. The success of our evolution strategy method is demonstrated by applying to the yeast protein-protein interaction network. Functional subsystems of important physiological phenomena can be revealed. In particular, the cell cycle controlling network is selected for detailed discussion. The cell cycle subcellular processes in yeast can be successfully dissected into functional modules of cell cycle control, cell size check point, spindle assembly checkpoint, and DNA damage check point in G2/M and S phases. The interconnections between check points and cell cycle control modules provide clues on the

  8. 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

  9. Neural adaptation in pSTS correlates with perceptual aftereffects to biological motion and with autistic traits.

    PubMed

    Thurman, Steven M; van Boxtel, Jeroen J A; Monti, Martin M; Chiang, Jeffrey N; Lu, Hongjing

    2016-08-01

    The adaptive nature of biological motion perception has been documented in behavioral studies, with research showing that prolonged viewing of an action can bias judgments of subsequent actions towards the opposite of its attributes. However, the neural mechanisms underlying action adaptation aftereffects remain unknown. We examined adaptation-induced changes in brain responses to an ambiguous action after adapting to walking or running actions within two bilateral regions of interest: 1) human middle temporal area (hMT+), a lower-level motion-sensitive region of cortex, and 2) posterior superior temporal sulcus (pSTS), a higher-level action-selective area. We found a significant correlation between neural adaptation strength in right pSTS and perceptual aftereffects to biological motion measured behaviorally, but not in hMT+. The magnitude of neural adaptation in right pSTS was also strongly correlated with individual differences in the degree of autistic traits. Participants with more autistic traits exhibited less adaptation-induced modulations of brain responses in right pSTS and correspondingly weaker perceptual aftereffects. These results suggest a direct link between perceptual aftereffects and adaptation of neural populations in right pSTS after prolonged viewing of a biological motion stimulus, and highlight the potential importance of this brain region for understanding differences in social-cognitive processing along the autistic spectrum.

  10. ADAPTIVE CONTROL OF CENTER OF MASS (GLOBAL) MOTION AND ITS JOINT (LOCAL) ORIGIN IN GAIT

    PubMed Central

    Yang, Feng; Pai, Yi-Chung

    2014-01-01

    Dynamic gait stability can be quantified by the relationship of the motion state (i.e. the position and velocity) between the body center of mass (COM) and its base of support (BOS). Humans learn how to adaptively control stability by regulating the absolute COM motion state (i.e., its position and velocity) or by controlling the BOS (through stepping) in a predictable manner, or by doing both simultaneously following an external perturbation that disrupts their regular relationship. Post repeated-slip perturbation training, for instance, older adults learned to forward shift their COM position while walking with a reduced step length, hence reduced their likelihood of falls. How and to what extent each individual joint influences such adaptive alterations is mostly unknown. A three-dimensional individualized human kinematic model was established. Based on the human model, sensitivity analysis was used to systematically quantify the influence of each lower limb joint on the COM position relative to the BOS and the step length during gait. It was found that the leading foot had the greatest effect on regulating the COM position relative to the BOS; and both hips bear the most influence on the step length. These findings could guide cost-effective but efficient fall-reduction training paradigm among older population. PMID:24998991

  11. Adaptation of the S-5-S pendulum seismometer for measurement of rotational ground motion

    NASA Astrophysics Data System (ADS)

    Knejzlík, Jaromír; Kaláb, Zdeněk; Rambouský, Zdeněk

    2012-10-01

    The Russian electrodynamic seismometer model S-5-S has been adapted for the measurement of rotational ground motion. The mechanical system of the original S-5-S seismometer consists of electrodynamic sensing and damping transducer coils mounted on an asymmetrical double-arm pendulum. This pendulum is suspended on a footing using two pairs of crossed flat springs, which operate as the axis of rotation. The pendulum is stabilised by an additional spring. The S-5-S can be used either as a vertical or as a horizontal sensor. The adaptation of the S-5-S seismometer described below involves removal of the additional spring and installation of an additional mass on the damping arm. Strain gauge angle sensors are installed on one pair of the crossed flat springs. The main dynamic parameters of the rotational seismometer created in this way, i.e. the natural period and damping, are controlled electronically by feedback currents proportional to the angular displacement and angular velocity, both fed to the damping transducer coil. This new seismometer, named the S-5-SR, enables measurement of the rotational component of ground motion around the horizontal or the vertical axes. The output signal from this S-5-SR seismometer can be proportional either to rotational displacement or rotational velocity.

  12. Dominant-Limb Range-of-Motion and Humeral-Retrotorsion Adaptation in Collegiate Baseball and Softball Position Players

    PubMed Central

    Hibberd, Elizabeth E.; Oyama, Sakiko; Tatman, Justin; Myers, Joseph B.

    2014-01-01

    Context: Biomechanically, the motions used by baseball and softball pitchers differ greatly; however, the throwing motions of position players in both sports are strikingly similar. Although the adaptations to the dominant limb from overhead throwing have been well documented in baseball athletes, these adaptations have not been clearly identified in softball players. This information is important in order to develop and implement injury-prevention programs specific to decreasing the risk of upper extremity injury in softball athletes. Objective: To compare range-of-motion and humeral-retrotorsion characteristics of collegiate baseball and softball position players and of baseball and softball players to sex-matched controls. Design: Cross-sectional study. Setting: Research laboratories and athletic training rooms at the University of North Carolina at Chapel Hill. Patients or Other Participants: Fifty-three collegiate baseball players, 35 collegiate softball players, 25 male controls (nonoverhead athletes), and 19 female controls (nonoverhead athletes). Intervention(s): Range of motion and humeral retrotorsion were measured using a digital inclinometer and diagnostic ultrasound. Main Outcome Measure(s): Glenohumeral internal-rotation deficit, external-rotation gain, total glenohumeral range of motion, and humeral retrotorsion. Results: Baseball players had greater glenohumeral internal-rotation deficit, total–range-of-motion, and humeral-retrotorsion difference than softball players and male controls. There were no differences between glenohumeral internal-rotation deficit, total–range-of-motion, and humeral-retrotorsion difference in softball players and female controls. Conclusions: Few differences were evident between softball players and female control participants, although range-of-motion and humeral-retrotorsion adaptations were significantly different than baseball players. The throwing motions are similar between softball and baseball, but the

  13. 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. PMID:26631149

  14. 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…

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Adaptive recovery of motion blur point spread function from differently exposed images

    NASA Astrophysics Data System (ADS)

    Albu, Felix; Florea, Corneliu; Drîmbarean, Alexandru; Zamfir, Adrian

    2010-01-01

    Motion due to digital camera movement during the image capture process is a major factor that degrades the quality of images and many methods for camera motion removal have been developed. Central to all techniques is the correct recovery of what is known as the Point Spread Function (PSF). A very popular technique to estimate the PSF relies on using a pair of gyroscopic sensors to measure the hand motion. However, the errors caused either by the loss of the translational component of the movement or due to the lack of precision in gyro-sensors measurements impede the achievement of a good quality restored image. In order to compensate for this, we propose a method that begins with an estimation of the PSF obtained from 2 gyro sensors and uses a pair of under-exposed image together with the blurred image to adaptively improve it. The luminance of the under-exposed image is equalized with that of the blurred image. An initial estimation of the PSF is generated from the output signal of 2 gyro sensors. The PSF coefficients are updated using 2D-Least Mean Square (LMS) algorithms with a coarse-to-fine approach on a grid of points selected from both images. This refined PSF is used to process the blurred image using known deblurring methods. Our results show that the proposed method leads to superior PSF support and coefficient estimation. Also the quality of the restored image is improved compared to 2 gyro only approach or to blind image de-convolution results.

  1. 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. PMID:21536526

  2. 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

  3. 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

  4. 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.

  5. Robust projective lag synchronization in drive-response dynamical networks via adaptive control

    NASA Astrophysics Data System (ADS)

    Al-mahbashi, G.; Noorani, M. S. Md; Bakar, S. A.; Al-sawalha, M. M.

    2016-02-01

    This paper investigates the problem of projective lag synchronization behavior in drive-response dynamical networks (DRDNs) with identical and non-identical nodes. An adaptive control method is designed to achieve projective lag synchronization with fully unknown parameters and unknown bounded disturbances. These parameters were estimated by adaptive laws obtained by Lyapunov stability theory. Furthermore, sufficient conditions for synchronization are derived analytically using the Lyapunov stability theory and adaptive control. In addition, the unknown bounded disturbances are also overcome by the proposed control. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Simulation results show the effectiveness of the proposed method.

  6. A robust method for suppressing motion-induced coil sensitivity variations during prospective correction of head motion in fMRI.

    PubMed

    Faraji-Dana, Zahra; Tam, Fred; Chen, J Jean; Graham, Simon J

    2016-10-01

    Prospective motion correction is a promising candidate solution to suppress the effects of head motion during fMRI, ideally allowing the imaging plane to remain fixed with respect to the moving head. Residual signal artifacts may remain, however, because head motion in relation to a fixed multi-channel receiver coil (with non-uniform sensitivity maps) can potentially introduce unwanted signal variations comparable to the weak fMRI BOLD signal (~1%-4% at 1.5-3.0T). The present work aimed to investigate the magnitude of these residual artifacts, and characterize the regime over which prospective motion correction benefits from adjusting sensitivity maps to reflect relative positional change between the head and the coil. Numerical simulations were used to inform human fMRI experiments. The simulations indicated that for axial imaging within a commonly used 12-channel head coil, 5° of head rotation in-plane produced artifact signal changes of ~3%. Subsequently, six young adults were imaged with and without overt head motions of approximately this extent, with and without prospective motion correction using the Prospective Acquisition CorrEction (PACE) method, and with and without sensitivity map adjustments. Sensitivity map adjustments combined with PACE strongly protected against the artifacts of interest, as indicated by comparing three metrics of data quality (number of activated voxels, Dice coefficient of activation overlap, temporal standard deviation of baseline fMRI timeseries data) across the different experimental conditions. It is concluded that head motion in relation to a fixed multi-channel coil can adversely affect fMRI with prospective motion correction, and that sensitivity map adjustment can mitigate this effect at 3.0T. PMID:27451407

  7. fMR-Adaptation Reveals Invariant Coding of Biological Motion on the Human STS

    PubMed Central

    Grossman, Emily D.; Jardine, Nicole L.; Pyles, John A.

    2009-01-01

    Neuroimaging studies of biological motion perception have found a network of coordinated brain areas, the hub of which appears to be the human posterior superior temporal sulcus (STSp). Understanding the functional role of the STSp requires characterizing the response tuning of neuronal populations underlying the BOLD response. Thus far our understanding of these response properties comes from single-unit studies of the monkey anterior STS, which has individual neurons tuned to body actions, with a small population invariant to changes in viewpoint, position and size of the action being viewed. To measure for homologous functional properties on the human STS, we used fMR-adaptation to investigate action, position and size invariance. Observers viewed pairs of point-light animations depicting human actions that were either identical, differed in the action depicted, locally scrambled, or differed in the viewing perspective, the position or the size. While extrastriate hMT+ had neural signals indicative of viewpoint specificity, the human STS adapted for all of these changes, as compared to viewing two different actions. Similar findings were observed in more posterior brain areas also implicated in action recognition. Our findings are evidence for viewpoint invariance in the human STS and related brain areas, with the implication that actions are abstracted into object-centered representations during visual analysis. PMID:20431723

  8. 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.

  9. Robust vibration suppression of an adaptive circular composite plate for satellite thrust vector control

    NASA Astrophysics Data System (ADS)

    Yan, Su; Ma, Kougen; Ghasemi-Nejhad, Mehrdad N.

    2008-03-01

    In this paper, a novel application of adaptive composite structures, a University of Hawaii at Manoa (UHM) smart composite platform, is developed for the Thrust Vector Control (TVC) of satellites. The device top plate of the UHM platform is an adaptive circular composite plate (ACCP) that utilizes integrated sensors/actuators and controllers to suppress low frequency vibrations during the thruster firing as well as to potentially isolate dynamic responses from the satellite structure bus. Since the disturbance due to the satellite thruster firing can be estimated, a combined strategy of an adaptive disturbance observer (DOB) and feed-forward control is proposed for vibration suppression of the ACCP with multi-sensors and multi-actuators. Meanwhile, the effects of the DOB cut-off frequency and the relative degree of the low-pass filter on the DOB performance are investigated. Simulations and experimental results show that higher relative degree of the low-pass filter with the required cut-off frequency will enhance the DOB performance for a high-order system control. Further, although the increase of the filter cut-off frequency can guarantee a sufficient stability margin, it may cause an undesirable increase of the control bandwidth. The effectiveness of the proposed adaptive DOB with feed-forward control strategy is verified through simulations and experiments using the ACCP system.

  10. Adaptive dynamic inversion robust control for BTT missile based on wavelet neural network

    NASA Astrophysics Data System (ADS)

    Li, Chuanfeng; Wang, Yongji; Deng, Zhixiang; Wu, Hao

    2009-10-01

    A new nonlinear control strategy incorporated the dynamic inversion method with wavelet neural networks is presented for the nonlinear coupling system of Bank-to-Turn(BTT) missile in reentry phase. The basic control law is designed by using the dynamic inversion feedback linearization method, and the online learning wavelet neural network is used to compensate the inversion error due to aerodynamic parameter errors, modeling imprecise and external disturbance in view of the time-frequency localization properties of wavelet transform. Weights adjusting laws are derived according to Lyapunov stability theory, which can guarantee the boundedness of all signals in the whole system. Furthermore, robust stability of the closed-loop system under this tracking law is proved. Finally, the six degree-of-freedom(6DOF) simulation results have shown that the attitude angles can track the anticipant command precisely under the circumstances of existing external disturbance and in the presence of parameter uncertainty. It means that the dependence on model by dynamic inversion method is reduced and the robustness of control system is enhanced by using wavelet neural network(WNN) to reconstruct inversion error on-line.

  11. Multiobjective control design including performance robustness for gust alleviation of a wing with adaptive material actuators

    NASA Astrophysics Data System (ADS)

    Layton, Jeffrey B.

    1997-06-01

    The goal of this paper is to examine the use of covariance control to directly design reduced-order multi-objective controllers for gust alleviation using adaptive materials as the control effector. It will use piezoelectric actuators as control effectors in a finite element model of a full-size wing model. More precisely, the finite element model is of the F-16 Agile Falcon/Active Flexible Wing that is modified to use piezoelectric actuators as control effectors. The paper will also examine the interacting roles of important control design constraints and objectives for designing an aeroservoelastic system. The paper will also present some results of multiobjective control design for the model, illustrating the benefits and complexity of modern practical control design for aeroservoelastic systems that use adaptive materials for actuation.

  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. PMID:26606851

  13. 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.

  14. A fast converging robust controller using adaptive second order sliding mode.

    PubMed

    Mondal, Sanjoy; Mahanta, Chitralekha

    2012-11-01

    This paper proposes an adaptive second order sliding mode (SOSM) controller with a nonlinear sliding surface. The nonlinear sliding surface consists of a gain matrix having a variable damping ratio. Initially the sliding surface uses a low value of damping ratio to get a quick system response. As the closed loop system approaches the desired reference, the value of the damping ratio gets increased with an aim to reducing the overshoot and the settling time. The time derivative of the control signal is used to design the controller. The actual control input obtained by integrating the derivative control signal is smooth and chattering free. The adaptive tuning law used by the proposed controller eliminates the need of prior knowledge about the upper bound of system uncertainties. Simulation results demonstrate the effectiveness of the proposed control strategy.

  15. Robust Adaptive 3-D Segmentation of Vessel Laminae From Fluorescence Confocal Microscope Images and Parallel GPU Implementation

    PubMed Central

    Narayanaswamy, Arunachalam; Dwarakapuram, Saritha; Bjornsson, Christopher S.; Cutler, Barbara M.; Shain, William

    2010-01-01

    This paper presents robust 3-D algorithms to segment vasculature that is imaged by labeling laminae, rather than the lumenal volume. The signal is weak, sparse, noisy, nonuniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding and Hessian filtering based methods are not effective. The structure deviates from a tubular geometry, so tracing algorithms are not effective. We propose a four step approach. The first step detects candidate voxels using a robust hypothesis test based on a model that assumes Poisson noise and locally planar geometry. The second step performs an adaptive region growth to extract weakly labeled and fine vessels while rejecting spectral artifacts. To enable interactive visualization and estimation of features such as statistical confidence, local curvature, local thickness, and local normal, we perform the third step. In the third step, we construct an accurate mesh representation using marching tetrahedra, volume-preserving smoothing, and adaptive decimation algorithms. To enable topological analysis and efficient validation, we describe a method to estimate vessel centerlines using a ray casting and vote accumulation algorithm which forms the final step of our algorithm. Our algorithm lends itself to parallel processing, and yielded an 8× speedup on a graphics processor (GPU). On synthetic data, our meshes had average error per face (EPF) values of (0.1–1.6) voxels per mesh face for peak signal-to-noise ratios from (110–28 dB). Separately, the error from decimating the mesh to less than 1% of its original size, the EPF was less than 1 voxel/face. When validated on real datasets, the average recall and precision values were found to be 94.66% and 94.84%, respectively. PMID:20199906

  16. Multibeam echosounder data cleaning through a hierarchic adaptive and robust local surfacing

    NASA Astrophysics Data System (ADS)

    Debese, Nathalie; Moitié, Rodéric; Seube, Nicolas

    2012-09-01

    Multibeam echo sounders (MBES) datasets generally contain sporadic outlier points. The huge volumes of MBES datasets in a hydrographic framework require the use of semi-automatic techniques. In very shallow waters depth, data cleaning becomes a challenging task when potential dangers to navigation have to be carefully checked. The aim of our paper is to attempt this goal by combining two well-known techniques. The seafloor is constructed as an assemblage of surface elements with the help of a robust statistical approach. The local parameters model is a priori chosen, its scale is driven through a quadtree descending approach using subdivision rules based on both statistical and spatio-temporal inferences. Our multi resolution approach provides, with the algorithm outputs, a classification map that notes areas of concern.

  17. Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

    NASA Astrophysics Data System (ADS)

    Rossant, Florence; Bloch, Isabelle

    2006-12-01

    This paper describes a system for optical music recognition (OMR) in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

  18. 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

  19. Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

    PubMed Central

    Wang, Ruliang; Li, Jie; Zhang, Shanshan; Gao, Dongmei; Sun, Huanlong

    2013-01-01

    We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme. PMID:23853544

  20. 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. PMID:21877804

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

    SciTech Connect

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

    2008-09-15

    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/s{sup 2} in the lateral direction, and 9.5 mm/s and 29.5 mm/s{sup 2} 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.

  2. 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. PMID:25983065

  3. 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.

  4. 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.

  5. Robust adaptive integrated translation and rotation control of a rigid spacecraft with control saturation and actuator misalignment

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Duan, Guangren

    2013-05-01

    This paper handles the integrated translation and rotation tracking control problem of a rigid spacecraft with unknown mass property, actuator misalignment and control saturation. In view of the system natural coupling, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment is taken into account. By using anti-windup technique and backstepping philosophy, a robust adaptive integrated control scheme is proposed such that the spacecraft is able to track the command position and attitude signals in the presence of external disturbance, unknown mass property, thruster misalignment and control saturation. Within the Lyapunov framework, the uniformly ultimate boundedness of the system states is guaranteed. In particular, given the nominal case, the asymptotic convergence of the system states can be further ensured by the proposed control scheme. Finally, numerical simulation demonstrates the effect of the designed control strategy.

  6. 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.

  7. Evidence for a common motion mechanism of luminance-modulated and contrast-modulated patterns: selective adaptation.

    PubMed

    Turano, K

    1991-01-01

    Selective adaptation effects were measured with contrast-modulated patterns and sine-wave gratings in order to determine the extent to which the two patterns are processed by common mechanisms. Direction-specific adaptation effects were measured for a contrast-modulated adapting pattern and a test pattern. The contrast-modulated adapting pattern was composed of a sine-wave grating of 8 cycles deg-1 whose contrast was spatially modulated by a sinusoid of 1 cycle deg-1 at one of four levels: 100%, 60%, 30%, or 0%. The results showed that contrast-modulation thresholds for contrast-modulated gratings were raised by 0.3 to 0.5 log units following adaptation to a contrast-modulated grating moving in the same direction as the test pattern, relative to thresholds obtained following adaptation to a contrast-modulated grafting moving in the opposite direction. Cross-adaptation effects were also measured with a sine-wave adapting pattern and a contrast-modulated test pattern. The sine-wave adapting pattern was a sine-wave grating of 1 cycle deg-1 whose contrast was set to one of three levels: 16.4%, 1.25%, or 0%. The contrast-modulated test pattern was a sine-wave grating of 8 cycles deg-1 whose contrast was modulated by a sinusoid of 1 cycle deg-1. The results revealed that contrast-modulation thresholds for contrast-modulated gratings were raised by approximately 0.25 log units following adaptation to moving sine-wave gratings, relative to thresholds obtained following adaptation to a uniform field. Cross-adaptation effects were also obtained with a contrast-modulated adapting pattern and a sine-wave test pattern. The results support the view that signals generated from luminance-domain stimuli and from contrast-domain stimuli are processed by a common motion mechanism.

  8. Robust semi-automatic segmentation of single- and multichannel MRI volumes through adaptable class-specific representation

    NASA Astrophysics Data System (ADS)

    Nielsen, Casper F.; Passmore, Peter J.

    2002-05-01

    Segmentation of MRI volumes is complicated by noise, inhomogeneity and partial volume artefacts. Fully or semi-automatic methods often require time consuming or unintuitive initialization. Adaptable Class-Specific Representation (ACSR) is a semi-automatic segmentation framework implemented by the Path Growing Algorithm (PGA), which reduces artefacts near segment boundaries. The user visually defines the desired segment classes through the selection of class templates and the following segmentation process is fully automatic. Good results have previously been achieved with color cryo section segmentation and ACSR has been developed further for the MRI modality. In this paper we present two optimizations for robust ACSR segmentation of MRI volumes. Automatic template creation based on an initial segmentation step using Learning Vector Quantization is applied for higher robustness to noise. Inhomogeneity correction is added as a pre-processing step, comparing the EQ and N3 algorithms. Results based on simulated T1-weighed and multispectral (T1 and T2) MRI data from the BrainWeb database and real data from the Internet Brain Segmentation Repository are presented. We show that ACSR segmentation compares favorably to previously published results on the same volumes and discuss the pros and cons of using quantitative ground truth evaluation compared to qualitative visual assessment.

  9. 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.

  10. Scan-pattern and signal processing for microvasculature visualization with complex SD-OCT: tissue-motion artifacts robustness and decorrelation time - blood vessel characteristics

    NASA Astrophysics Data System (ADS)

    Matveev, Lev A.; Zaitsev, Vladimir Y.; Gelikonov, Grigory V.; Matveyev, Alexandr L.; Moiseev, Alexander A.; Ksenofontov, Sergey Y.; Gelikonov, Valentin M.; Demidov, Valentin; Vitkin, Alex

    2015-03-01

    We propose a modification of OCT scanning pattern and corresponding signal processing for 3D visualizing blood microcirculation from complex-signal B-scans. We describe the scanning pattern modifications that increase the methods' robustness to bulk tissue motion artifacts, with speed up to several cm/s. Based on these modifications, OCT-based angiography becomes more realistic under practical measurement conditions. For these scan patterns, we apply novel signal processing to separate the blood vessels with different decorrelation times, by varying of effective temporal diversity of processed signals.

  11. 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

  12. 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

  13. 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.

  14. 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. PMID:24815269

  15. 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. PMID:27536516

  16. Robustness of external/internal correlation models for real-time tumor tracking to breathing motion variations

    NASA Astrophysics Data System (ADS)

    Seregni, M.; Cerveri, P.; Riboldi, M.; Pella, A.; Baroni, G.

    2012-11-01

    In radiotherapy, organ motion mitigation by means of dynamic tumor tracking requires continuous information about the internal tumor position, which can be estimated relying on external/internal correlation models as a function of external surface surrogates. In this work, we propose a validation of a time-independent artificial neural networks-based tumor tracking method in the presence of changes in the breathing pattern, evaluating the performance on two datasets. First, simulated breathing motion traces were specifically generated to include gradually increasing respiratory irregularities. Then, seven publically available human liver motion traces were analyzed for the assessment of tracking accuracy, whose sensitivity with respect to the structural parameters of the model was also investigated. Results on simulated data showed that the proposed method was not affected by hysteretic target trajectories and it was able to cope with different respiratory irregularities, such as baseline drift and internal/external phase shift. The analysis of the liver motion traces reported an average RMS error equal to 1.10 mm, with five out of seven cases below 1 mm. In conclusion, this validation study proved that the proposed method is able to deal with respiratory irregularities both in controlled and real conditions.

  17. 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

  18. Reproduction of Linear Motion with Adaptation for Change in Environmental Position

    NASA Astrophysics Data System (ADS)

    Tsunashima, Noboru; Katsura, Seiichiro

    In recent years, a technology for the preservation and reproduction of human motion has been in demand in the fields of manufacturing and human support. An efficient method for this purpose is the use of a motion-copying system. This system deals not only with the trajectory but also with the strength of human motion. However, there are several problems associated with this system. One of them is that the saved motion is not reproduced completely when the environmental location in the motion-loading system is different from that in the motion-saving system. For real-world haptics, a reproduction method that considers the relationship between human motion and the environment is necessary. In this paper, a motion-copying system based on acceleration information is proposed. In the proposed method, human motion is treated as the acceleration information. As a result, motion reproduction is realized even when the environmental location is different, because the acceleration information does not depend on the initial position. The validity of the proposed method is confirmed by experiments.

  19. A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

    PubMed

    Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei

    2014-11-01

    A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod.

  20. Perceived self-orientation and self-motion in microgravity, after landing and during preflight adaptation training

    NASA Technical Reports Server (NTRS)

    Harm, D. L.; Parker, D. E.

    1993-01-01

    The research described in this paper is intended to support development and evaluation of preflight adaptation training (PAT) apparatus and procedures. Successful training depends on appropriate manipulation of visual and inertial stimuli that control perception of self-motion and self-orientation. For one part of this process, astronauts are trained to report their self-motion and self-orientation experiences. Before their space mission, they are exposed to the altered sensory environments produced by the PAT trainers. During and after the mission, they report their motion and orientation experiences. Subsequently, they are again exposed to the PAT trainers and are asked to describe relationships between their experiences in microgravity and following entry and their experiences in the trainers.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. Observation-driven adaptive differential evolution and its application to accurate and smooth bronchoscope three-dimensional motion tracking.

    PubMed

    Luo, Xiongbiao; Wan, Ying; He, Xiangjian; Mori, Kensaku

    2015-08-01

    This paper proposes an observation-driven adaptive differential evolution algorithm that fuses bronchoscopic video sequences, electromagnetic sensor measurements, and computed tomography images for accurate and smooth bronchoscope three-dimensional motion tracking. Currently an electromagnetic tracker with a position sensor fixed at the bronchoscope tip is commonly used to estimate bronchoscope movements. The large tracking error from directly using sensor measurements, which may be deteriorated heavily by patient respiratory motion and the magnetic field distortion of the tracker, limits clinical applications. How to effectively use sensor measurements for precise and stable bronchoscope electromagnetic tracking remains challenging. We here exploit an observation-driven adaptive differential evolution framework to address such a challenge and boost the tracking accuracy and smoothness. In our framework, two advantageous points are distinguished from other adaptive differential evolution methods: (1) the current observation including sensor measurements and bronchoscopic video images is used in the mutation equation and the fitness computation, respectively and (2) the mutation factor and the crossover rate are determined adaptively on the basis of the current image observation. The experimental results demonstrate that our framework provides much more accurate and smooth bronchoscope tracking than the state-of-the-art methods. Our approach reduces the tracking error from 3.96 to 2.89 mm, improves the tracking smoothness from 4.08 to 1.62 mm, and increases the visual quality from 0.707 to 0.741. PMID:25660001

  7. Comparative analysis of different adaptive filters for tracking lower segments of a human body using inertial motion sensors

    NASA Astrophysics Data System (ADS)

    Öhberg, Fredrik; Lundström, Ronnie; Grip, Helena

    2013-08-01

    For all segments and tests, a modified Kalman filter and a quasi-static sensor fusion algorithm were equally accurate (precision and accuracy ˜2-3°) compared to normalized least mean squares filtering, recursive least-squares filtering and standard Kalman filtering. The aims were to: (1) compare adaptive filtering techniques used for sensor fusion and (2) evaluate the precision and accuracy for a chosen adaptive filter. Motion sensors (based on inertial measurement units) are limited by accumulative integration errors arising from sensor bias. This drift can partly be handled with adaptive filtering techniques. To advance the measurement technique in this area, a new modified Kalman filter is developed. Differences in accuracy were observed during different tests especially drift in the internal/external rotation angle. This drift can be minimized if the sensors include magnetometers.

  8. 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.

  9. 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.

  10. 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

  11. Robust 2D/3D registration for fast-flexion motion of the knee joint using hybrid optimization.

    PubMed

    Ohnishi, Takashi; Suzuki, Masahiko; Kobayashi, Tatsuya; Naomoto, Shinji; Sukegawa, Tomoyuki; Nawata, Atsushi; Haneishi, Hideaki

    2013-01-01

    Previously, we proposed a 2D/3D registration method that uses Powell's algorithm to obtain 3D motion of a knee joint by 3D computed-tomography and bi-plane fluoroscopic images. The 2D/3D registration is performed consecutively and automatically for each frame of the fluoroscopic images. This method starts from the optimum parameters of the previous frame for each frame except for the first one, and it searches for the next set of optimum parameters using Powell's algorithm. However, if the flexion motion of the knee joint is fast, it is likely that Powell's algorithm will provide a mismatch because the initial parameters are far from the correct ones. In this study, we applied a hybrid optimization algorithm (HPS) combining Powell's algorithm with the Nelder-Mead simplex (NM-simplex) algorithm to overcome this problem. The performance of the HPS was compared with the separate performances of Powell's algorithm and the NM-simplex algorithm, the Quasi-Newton algorithm and hybrid optimization algorithm with the Quasi-Newton and NM-simplex algorithms with five patient data sets in terms of the root-mean-square error (RMSE), target registration error (TRE), success rate, and processing time. The RMSE, TRE, and the success rate of the HPS were better than those of the other optimization algorithms, and the processing time was similar to that of Powell's algorithm alone.

  12. 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.

  13. Interaction of a laser with a qubit in thermal motion and its application to robust and efficient readout

    NASA Astrophysics Data System (ADS)

    Poschinger, U.; Walther, A.; Hettrich, M.; Ziesel, F.; Schmidt-Kaler, F.

    2012-06-01

    We present a detailed theoretical and experimental study on the optical control of a trapped-ion qubit subject to thermally induced fluctuations of the Rabi frequency. The coupling fluctuations are caused by thermal excitation on three harmonic oscillator modes. We develop an effective Maxwell-Boltzmann theory which leads to a replacement of several quantized oscillator modes by an effective continuous probability distribution function for the Rabi frequency. The model is experimentally verified for driving the quadrupole transition with resonant square pulses. This allows for the determination of the ion temperature with an accuracy of better than 2% of the temperature pertaining to the Doppler cooling limit T D over a range from 0.5 T D to 5 T D . The theory is then applied successfully to model experimental data for rapid adiabatic passage (RAP) pulses. We apply the model and the obtained experimental parameters to elucidate the robustness and efficiency of the RAP process by means of numerical simulations.

  14. 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

  15. Ultra-precision measurement and control of angle motion in piezo-based platforms using strain gauge sensors and a robust composite controller.

    PubMed

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

    2013-07-15

    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.

  16. 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

  17. Adaptive temporal integration of motion in direction-selective neurons in macaque visual cortex.

    PubMed

    Bair, Wyeth; Movshon, J Anthony

    2004-08-18

    Direction-selective neurons in the primary visual cortex (V1) and the extrastriate motion area MT/V5 constitute a critical channel that links early cortical mechanisms of spatiotemporal integration to downstream signals that underlie motion perception. We studied how temporal integration in direction-selective cells depends on speed, spatial frequency (SF), and contrast using randomly moving sinusoidal gratings and spike-triggered average (STA) analysis. The window of temporal integration revealed by the STAs varied substantially with stimulus parameters, extending farther back in time for slow motion, high SF, and low contrast. At low speeds and high SF, STA peaks were larger, indicating that a single spike often conveyed more information about the stimulus under conditions in which the mean firing rate was very low. The observed trends were similar in V1 and MT and offer a physiological correlate for a large body of psychophysical data on temporal integration. We applied the same visual stimuli to a model of motion detection based on oriented linear filters (a motion energy model) that incorporated an integrate-and-fire mechanism and found that it did not account for the neuronal data. Our results show that cortical motion processing in V1 and in MT is highly nonlinear and stimulus dependent. They cast considerable doubt on the ability of simple oriented filter models to account for the output of direction-selective neurons in a general manner. Finally, they suggest that spike rate tuning functions may miss important aspects of the neural coding of motion for stimulus conditions that evoke low firing rates. PMID:15317857

  18. 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.

  19. 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%. PMID:22346724

  20. 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

  1. Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

    SciTech Connect

    Slagmolen, Pieter; Hermans, Jeroen; Maes, Frederik; Budiharto, Tom; Haustermans, Karin; Heuvel, Frank van den

    2010-04-15

    Purpose: A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion. Methods: Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth. Results: The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4{+-}1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images

  2. 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

  3. 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.

  4. Osseous adaptation and range of motion at the glenohumeral joint in professional baseball pitchers.

    PubMed

    Crockett, Heber C; Gross, Lyndon B; Wilk, Kevin E; Schwartz, Martin L; Reed, Jamie; O'Mara, Jay; Reilly, Michael T; Dugas, Jeffery R; Meister, Keith; Lyman, Stephen; Andrews, James R

    2002-01-01

    The throwing shoulder in pitchers frequently exhibits a paradox of glenohumeral joint motion, in which excessive external rotation is present at the expense of decreased internal rotation. The object of this study was to determine the role of humeral head retroversion in relation to increased glenohumeral external rotation. Glenohumeral joint range of motion and laxity along with humeral head and glenoid version of the dominant versus nondominant shoulders were studied in 25 professional pitchers and 25 nonthrowing subjects. Each subject underwent a computed tomography scan to determine bilateral humeral head and glenoid version. The throwing group demonstrated a significant increase in the dominant shoulder versus the nondominant shoulder in humeral head retroversion, glenoid retroversion, external rotation at 90 degrees, and external rotation in the scapular plane. Internal rotation was decreased in the dominant shoulder. Total range of motion, anterior glenohumeral laxity, and posterior glenohumeral laxity were found to be equal bilaterally. The nonthrowing group demonstrated no significant difference in humeral head retroversion, glenoid retroversion, external rotation at 90 degrees or external rotation in the scapular plane between shoulders, and no difference in internal rotation at 90 degrees, total motion, or laxity. A comparison of the dominant shoulders of the two groups indicated that both external rotation at 90 degrees and humeral head retroversion were significantly greater in the throwing group.

  5. Quality Assurance Challenges for Motion-Adaptive Radiation Therapy: Gating, Breath Holding, and Four-Dimensional Computed Tomography

    SciTech Connect

    Jiang, Steve B. Wolfgang, John; Mageras, Gig S.

    2008-05-01

    Compared with conventional three-dimensional (3D) conformal radiation therapy and intensity-modulated radiation therapy treatments, quality assurance (QA) for motion-adaptive radiation therapy involves various challenges because of the added temporal dimension. Here we discuss those challenges for three specific techniques related to motion-adaptive therapy: namely respiratory gating, breath holding, and four-dimensional computed tomography. Similar to the introduction of any other new technologies in clinical practice, typical QA measures should be taken for these techniques also, including initial testing of equipment and clinical procedures, as well as frequent QA examinations during the early stage of implementation. Here, rather than covering every QA aspect in depth, we focus on some major QA challenges. The biggest QA challenge for gating and breath holding is how to ensure treatment accuracy when internal target position is predicted using external surrogates. Recommended QA measures for each component of treatment, including simulation, planning, patient positioning, and treatment delivery and verification, are discussed. For four-dimensional computed tomography, some major QA challenges have also been discussed.

  6. 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.

  7. Space motion sickness preflight adaptation training Preliminary studies with prototype trainers

    NASA Technical Reports Server (NTRS)

    Parker, D. E.; Ouyang, L.; Rock, J. C.; Von Gierke, H. E.; Reschke, M. F.

    1985-01-01

    Based on the otolith tilt-translation reinterpretation hypothesis (Parker et al., 1985), preflight adaptation procedures and several preflight adaptation trainers (PATs) have been developed. Two PAT prototypes, the Miami University Seesaw (MUS) and the Dynamic Environmental Simulator (DES), include a physical room that is moved relative to the restrained subject. Results from the MUS and DES PAT experiments indicate that exposure to the produced sensory rearrangement can change eye movement reflexes. The changes persisted for a period longer than the training exposure period, indicating similarity with the eye-movement reflexes observed immediately postflight in weightlessness-adapted astronauts. It is concluded that the apparatus and procedures to preadapt astronauts to the sensory rearrangement of weightless space flight can be developed on the basis of the reported PATs and procedures. The third PAT prototype tested, which employs a computer-generated scene, failed to produce changes similar to those recorded in the MUS and DES experiments.

  8. 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

  9. 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…

  10. 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.

  11. 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

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

    SciTech Connect

    Pin, Francois G.

    2002-06-01

    Robotic tasks are typically defined in Task Space (e.g., the 3-D World), whereas robots are controlled in Joint Space (motors). The transformation from Task Space to Joint Space must consider the task objectives (e.g., high precision, strength optimization, torque optimization), the task constraints (e.g., obstacles, joint limits, non-holonomic constraints, contact or tool task constraints), and the robot kinematics configuration (e.g., tools, type of joints, mobile platform, manipulator, modular additions, locked joints). Commercially available robots are optimized for a specific set of tasks, objectives and constraints and, therefore, their control codes are extremely specific to a particular set of conditions. Thus, there exist a multiplicity of codes, each handling a particular set of conditions, but none suitable for use on robots with widely varying tasks, objectives, constraints, or environments. On the other hand, most DOE missions and tasks are typically ''batches of one''. Attempting to use commercial codes for such work requires significant personnel and schedule costs for re-programming or adding code to the robots whenever a change in task objective, robot configuration, number and type of constraint, etc. occurs. The objective of our project is to develop a ''generic code'' to implement this Task-space to Joint-Space transformation that would allow robot behavior adaptation, in real time (at loop rate), to changes in task objectives, number and type of constraints, modes of controls, kinematics configuration (e.g., new tools, added module). Our specific goal is to develop a single code for the general solution of under-specified systems of algebraic equations that is suitable for solving the inverse kinematics of robots, is useable for all types of robots (mobile robots, manipulators, mobile manipulators, etc.) with no limitation on the number of joints and the number of controlled Task-Space variables, can adapt to real time changes in number and

  13. Motion detection and adaptation in crayfish photoreceptors. A spatiotemporal analysis of linear movement sensitivity

    PubMed Central

    1991-01-01

    Impulse and sine wave responses of crayfish photoreceptors were examined to establish the limits and the parameters of linear behavior. These receptors exhibit simple low pass behavior which is well described by the transfer function of a linear resistor-capacitor cascade of three to five stages, each with the same time constant (tau). Additionally, variations in mean light intensity modify tau twofold and the contrast sensitivity by fourfold. The angular sensitivity profile is Gaussian and the acceptance angle (phi) increases 3.2-fold with dark adaptation. The responses to moving stripes of positive and negative contrast were measured over a 100-fold velocity range. The amplitude, phase, and waveform of these responses were predicted from the convolution of the receptor's impulse response and angular sensitivity profile. A theoretical calculation based on the convolution of a linear impulse response and a Gaussian sensitivity profile indicates that the sensitivity to variations in stimulus velocity is determined by the ratio phi/tau. These two parameters are sufficient to predict the velocity of the half-maximal response over a wide range of ambient illumination levels. Because phi and tau vary in parallel during light adaptation, it is inferred that many arthropods can maintain approximately constant velocity sensitivity during large shifts in mean illumination and receptor time constant. The results are discussed relative to other arthropod and vertebrate receptors and the strategies that have evolved for movement detection in varying ambient illumination. PMID:2056307

  14. 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.

  15. 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.

  16. 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.

  17. Ambulatory human motion tracking by fusion of inertial and magnetic sensing with adaptive actuation.

    PubMed

    Schepers, H Martin; Roetenberg, Daniel; Veltink, Peter H

    2010-01-01

    Over the last years, inertial sensing has proven to be a suitable ambulatory alternative to traditional human motion tracking based on optical position measurement systems, which are generally restricted to a laboratory environment. Besides many advantages, a major drawback is the inherent drift caused by integration of acceleration and angular velocity to obtain position and orientation. In addition, inertial sensing cannot be used to estimate relative positions and orientations of sensors with respect to each other. In order to overcome these drawbacks, this study presents an Extended Kalman Filter for fusion of inertial and magnetic sensing that is used to estimate relative positions and orientations. In between magnetic updates, change of position and orientation are estimated using inertial sensors. The system decides to perform a magnetic update only if the estimated uncertainty associated with the relative position and orientation exceeds a predefined threshold. The filter is able to provide a stable and accurate estimation of relative position and orientation for several types of movements, as indicated by the average rms error being 0.033 m for the position and 3.6 degrees for the orientation. PMID:20016949

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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. PMID:27157849

  5. 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

  6. Robust DTC Based on Adaptive Fuzzy Control of Double Star Synchronous Machine Drive with Fixed Switching Frequency

    NASA Astrophysics Data System (ADS)

    Boudana, Djamel; Nezli, Lazhari; Tlemçani, Abdelhalim; Mahmoudi, Mohand Oulhadj; Tadjine, Mohamed

    2012-05-01

    The double star synchronous machine (DSSM) is widely used for high power traction drives. It possesses several advantages over the conventional three phase machine. To reduce the torque ripple the DSSM are supplied with source voltage inverter (VSI). The model of the system DSSM-VSI is high order, multivariable and nonlinear. Further, big harmonic currents are generated. The aim of this paper is to develop a new direct torque adaptive fuzzy logic control in order to control DSSM and minimize the harmonics currents. Simulations results are given to show the effectiveness of our approach.

  7. Sterile inflammation induced by Carbopol elicits robust adaptive immune responses in the absence of pathogen-associated molecular patterns

    PubMed Central

    Gartlan, Kate H.; Krashias, George; Wegmann, Frank; Hillson, William R.; Scherer, Erin M.; Greenberg, Philip D.; Eisenbarth, Stephanie C.; Moghaddam, Amin E.; Sattentau, Quentin J.

    2016-01-01

    Carbopol is a polyanionic carbomer used in man for topical application and drug delivery purposes. However parenteral administration of Carbopol in animal models results in systemic adjuvant activity including strong pro-inflammatory type-1 T-cell (Th1) polarization. Here we investigated potential pathways of immune activation by Carbopol by comparison with other well-characterized adjuvants. Carbopol administration triggered rapid and robust leukocyte recruitment, pro-inflammatory cytokine secretion and antigen capture largely by inflammatory monocytes. The induction of antigen specific Th1 cells by Carbopol was found to occur via a non-canonical pathway, independent of MyD88/TRIF signaling and in the absence of pattern-recognition-receptor (PRR) activation typically associated with Th1/Ig2a induction. Using multispectral fluorescence imaging (Imagestream) and electron microscopy we demonstrated that phagocytic uptake of Carbopol particles followed by entry into the phagosomal/lysosomal pathway elicited conformational changes to the polymer and reactive oxygen species (ROS) production. We therefore conclude that Carbopol may mediate its adjuvant activity via novel mechanisms of antigen presenting cell activation and Th1 induction, leading to enhanced IgG2a responses independent of microbial pattern recognition. PMID:27005810

  8. 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.

  9. Robust adaptive integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Duan, Guang-Ren

    2014-05-01

    This paper tackles the problem of integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property. Due to the system natural couplings, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment and unknown mass property are taken into account. By solving an equivalent designated trajectory tracking problem via backstepping philosophy, a robust adaptive integrated finite-time control scheme is proposed to enable the spacecraft track command position and attitude in a pre-determined time, despite of external disturbance, unknown mass property and thruster misalignment. The finite-time closed-loop stability is guaranteed within the Lyapunov framework. Two scenario numerical simulations demonstrate the effect of the designed controller.

  10. Development of a Synthetic Adaptive Neuro-Fuzzy Prediction Model for Tumor Motion Tracking in External Radiotherapy by Evaluating Various Data Clustering Algorithms.

    PubMed

    Ghorbanzadeh, Leila; Torshabi, Ahmad Esmaili; Nabipour, Jamshid Soltani; Arbatan, Moslem Ahmadi

    2016-04-01

    In image guided radiotherapy, in order to reach a prescribed uniform dose in dynamic tumors at thorax region while minimizing the amount of additional dose received by the surrounding healthy tissues, tumor motion must be tracked in real-time. Several correlation models have been proposed in recent years to provide tumor position information as a function of time in radiotherapy with external surrogates. However, developing an accurate correlation model is still a challenge. In this study, we proposed an adaptive neuro-fuzzy based correlation model that employs several data clustering algorithms for antecedent parameters construction to avoid over-fitting and to achieve an appropriate performance in tumor motion tracking compared with the conventional models. To begin, a comparative assessment is done between seven nuero-fuzzy correlation models each constructed using a unique data clustering algorithm. Then, each of the constructed models are combined within an adaptive sevenfold synthetic model since our tumor motion database has high degrees of variability and that each model has its intrinsic properties at motion tracking. In the proposed sevenfold synthetic model, best model is selected adaptively at pre-treatment. The model also updates the steps for each patient using an automatic model selectivity subroutine. We tested the efficacy of the proposed synthetic model on twenty patients (divided equally into two control and worst groups) treated with CyberKnife synchrony system. Compared to Cyberknife model, the proposed synthetic model resulted in 61.2% and 49.3% reduction in tumor tracking error in worst and control group, respectively. These results suggest that the proposed model selection program in our synthetic neuro-fuzzy model can significantly reduce tumor tracking errors. Numerical assessments confirmed that the proposed synthetic model is able to track tumor motion in real time with high accuracy during treatment. PMID:25765021

  11. Simple adaptive tracking control for mobile robots

    NASA Astrophysics Data System (ADS)

    Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton

    2014-12-01

    The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.

  12. 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.

  13. Case of Yellow Fever Vaccine–Associated Viscerotropic Disease with Prolonged Viremia, Robust Adaptive Immune Responses, and Polymorphisms in CCR5 and RANTES Genes

    PubMed Central

    Pulendran, Bali; Miller, Joseph; Querec, Troy D.; Akondy, Rama; Moseley, Nelson; Laur, Oscar; Glidewell, John; Monson, Nathan; Zhu, Tuofu; Zhu, Haiying; Staprans, Sylvija; Lee, David; Brinton, Margo A.; Perelygin, Andrey A.; Vellozzi, Claudia; Brachman, Philip; Lalor, Susan; Teuwen, Dirk; Eidex, Rachel B.; Cetron, Marty; Priddy, Frances; del Rio, Carlos; Altman, John; Ahmed, Rafi

    2013-01-01

    Background The live attenuated yellow fever vaccine 17D (YF-17D) is one of the most effective vaccines. Despite its excellent safety record, some cases of viscerotropic adverse events develop, which are sometimes fatal. The mechanisms underlying such events remain a mystery. Here, we present an analysis of the immunologic and genetic factors driving disease in a 64-year-old male who developed viscerotropic symptoms. Methods We obtained clinical, serologic, virologic, immunologic and genetic data on this case patient. Results Viral RNA was detected in the blood 33 days after vaccination, in contrast to the expected clearance of virus by day 7 after vaccination in healthy vaccinees. Vaccination induced robust antigen-specific T and B cell responses, which suggested that persistent virus was not due to adaptive immunity of suboptimal magnitude. The genes encoding OAS1, OAS2, TLR3, and DC-SIGN, which mediate antiviral innate immunity, were wild type. However, there were heterozygous genetic polymorphisms in chemokine receptor CCR5, and its ligand RANTES, which influence the migration of effector T cells and CD14+CD16bright monocytes to tissues. Consistent with this, there was a 200-fold increase in the number of CD14+CD16bright monocytes in the blood during viremia and even several months after virus clearance. Conclusion; In this patient, viscerotropic disease was not due to the impaired magnitude of adaptive immunity but instead to anomalies in the innate immune system and a possible disruption of the CCR5-RANTES axis. PMID:18598196

  14. 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.

  15. An adaptable pentaloop defines a robust neomycin-B RNA aptamer with conditional ligand-bound structures

    PubMed Central

    Ilgu, Muslum; Fulton, D. Bruce; Yennamalli, Ragothaman M.; Lamm, Monica H.; Sen, Taner Z.; Nilsen-Hamilton, Marit

    2014-01-01

    Aptamers can be highly specific for their targets, which implies precise molecular recognition between aptamer and target. However, as small polymers, their structures are more subject to environmental conditions than the more constrained longer RNAs such as those that constitute the ribosome. To understand the balance between structural and environmental factors in establishing ligand specificity of aptamers, we examined the RNA aptamer (NEO1A) previously reported as specific for neomycin-B. We show that NEO1A can recognize other aminoglycosides with similar affinities as for neomycin-B and its aminoglycoside specificity is strongly influenced by ionic strength and buffer composition. NMR and 2-aminopurine (2AP) fluorescence studies of the aptamer identified a flexible pentaloop and a stable binding pocket. Consistent with a well-structured binding pocket, docking analysis results correlated with experimental measures of the binding energy for most ligands. Steady state fluorescence studies of 2AP-substituted aptamers confirmed that A16 moves to a more solvent accessible position upon ligand binding while A14 moves to a less solvent accessible position, which is most likely a base stack. Analysis of binding affinities of NEO1A sequence variants showed that the base in position 16 interacts differently with each ligand and the interaction is a function of the buffer constituents. Our results show that the pentaloop provides NEO1A with the ability to adapt to external influences on its structure, with the critical base at position 16 adjusting to incorporate each ligand into a stable pocket by hydrophobic interactions and/or hydrogen bonds depending on the ligand and the ionic environment. PMID:24757168

  16. Robust Adaptation? Assessing the sensitivity of safety margins in flood defences to uncertainty in future simulations - a case study from Ireland.

    NASA Astrophysics Data System (ADS)

    Murphy, Conor; Bastola, Satish; Sweeney, John

    2013-04-01

    Climate change impact and adaptation assessments have traditionally adopted a 'top-down' scenario based approach, where information from different Global Climate Models (GCMs) and emission scenarios are employed to develop impacts led adaptation strategies. Due to the tradeoffs in the computational cost and need to include a wide range of GCMs for fuller characterization of uncertainties, scenarios are better used for sensitivity testing and adaptation options appraisal. One common approach to adaptation that has been defined as robust is the use of safety margins. In this work the sensitivity of safety margins that have been adopted by the agency responsible for flood risk management in Ireland, to the uncertainty in future projections are examined. The sensitivity of fluvial flood risk to climate change is assessed for four Irish catchments using a large number of GCMs (17) forced with three emissions scenarios (SRES A1B, A2, B1) as input to four hydrological models. Both uncertainty within and between hydrological models is assessed using the GLUE framework. Regionalisation is achieved using a change factor method to infer changes in the parameters of a weather generator using monthly output from the GCMs, while flood frequency analysis is conducted using the method of probability weighted moments to fit the Generalised Extreme Value distribution to ~20,000 annual maxima series. The sensitivity of design margins to the uncertainty space considered is visualised using risk response surfaces. The hydrological sensitivity is measured as the percentage change in flood peak for specified recurrence intervals. Results indicate that there is a considerable residual risk associated with allowances of +20% when uncertainties are accounted for and that the risk of exceedence of design allowances is greatest for more extreme, low frequency events with considerable implication for critical infrastructure, e.g., culverts, bridges, flood defences whose designs are normally

  17. 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

  18. 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.

  19. 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.

  20. Peak muscle activation, joint kinematics, and kinetics during elliptical and stepping movement pattern on a Precor Adaptive Motion Trainer.

    PubMed

    Rogatzki, Matthew J; Kernozek, Thomas W; Willson, John D; Greany, John F; Hong, Di-An; Porcari, John R

    2012-06-01

    Kinematic, kinetic, and electromyography data were collected from the biceps femoris, rectus femoris (RF), gluteus maximus, and erector spinae (ES) during a step and elliptical exercise at a standardized workload with no hand use. Findings depicted 95% greater ankle plantar flexion (p = .01), 29% more knee extension (p = .003), 101% higher peak knee flexor moments (p < .001) 54% greater hip extensor moments (p < .001), 268% greater anterior joint reaction force (p = .009), 37% more RF activation (p < .001), and 200 % more ES activation (p <. 001) for the elliptical motion. Sixteen percent more hip flexion (p < .001), 42% higher knee extensor moments (p < .001), and 54% greater hip flexor moments (p = .041) occurred during the step motion. Biomechanical differences between motions should be considered when planning an exercise regimen. PMID:22808700

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Robust control of accelerators

    SciTech Connect

    Johnson, W.J.D. ); Abdallah, C.T. )

    1990-01-01

    The problem of controlling the variations in the rf power system can be effectively cast as an application of modern control theory. Two components of this theory are obtaining a model and a feedback structure. The model inaccuracies influence the choice of a particular controller structure. Because of the modeling uncertainty, one has to design either a variable, adaptive controller or a fixed, robust controller to achieve the desired objective. The adaptive control scheme usually results in very complex hardware; and, therefore, shall not be pursued in this research. In contrast, the robust control methods leads to simpler hardware. However, robust control requires a more accurate mathematical model of the physical process than is required by adaptive control. Our research at the Los Alamos National Laboratory (LANL) and the University of New Mexico (UNM) has led to the development and implementation of a new robust rf power feedback system. In this paper, we report on our research progress. In section one, the robust control problem for the rf power system and the philosophy adopted for the beginning phase of our research is presented. In section two, the results of our proof-of-principle experiments are presented. In section three, we describe the actual controller configuration that is used in LANL FEL physics experiments. The novelty of our approach is that the control hardware is implemented directly in rf without demodulating, compensating, and then remodulating.

  6. The Zigbee wireless ECG measurement system design with a motion artifact remove algorithm by using adaptive filter and moving weighted factor

    NASA Astrophysics Data System (ADS)

    Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

    2012-04-01

    The Electrocardiogram(ECG) signal is one of the bio-signals to check body status. Traditionally, the ECG signal was checked in the hospital. In these days, as the number of people who is interesting with periodic their health check increase, the requirement of self-diagnosis system development is being increased as well. Ubiquitous concept is one of the solutions of the self-diagnosis system. Zigbee wireless sensor network concept is a suitable technology to satisfy the ubiquitous concept. In measuring ECG signal, there are several kinds of methods in attaching electrode on the body called as Lead I, II, III, etc. In addition, several noise components occurred by different measurement situation such as experimenter's respiration, sensor's contact point movement, and the wire movement attached on sensor are included in pure ECG signal. Therefore, this paper is based on the two kinds of development concept. The first is the Zibee wireless communication technology, which can provide convenience and simpleness, and the second is motion artifact remove algorithm, which can detect clear ECG signal from measurement subject. The motion artifact created by measurement subject's movement or even respiration action influences to distort ECG signal, and the frequency distribution of the noises is around from 0.2Hz to even 30Hz. The frequencies are duplicated in actual ECG signal frequency, so it is impossible to remove the artifact without any distortion of ECG signal just by using low-pass filter or high-pass filter. The suggested algorithm in this paper has two kinds of main parts to extract clear ECG signal from measured original signal through an electrode. The first part is to extract motion noise signal from measured signal, and the second part is to extract clear ECG by using extracted motion noise signal and measured original signal. The paper suggests several techniques in order to extract motion noise signal such as predictability estimation theory, low pass filter

  7. 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.

  8. 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.

  9. Polar motion as boundary condition in an adaptive Kalman filter approach for the determination of period and damping of the Chandler oscillation

    NASA Astrophysics Data System (ADS)

    Seitz, F.; Kirschner, S.; Neubersch, D.

    2012-12-01

    Earth rotation has been monitored using space geodetic techniques since many decades. The geophysical interpretation of observed time series of Earth rotation parameters (ERP) polar motion and length-of-day is commonly based on numerical models that describe and balance variations of angular momentum in various subsystems of the Earth. Naturally, models are dependent on geometrical, rheological and physical parameters. Many of these are weakly determined from other models or observations. In our study we present an adaptive Kalman filter approach for the improvement of parameters of the dynamic Earth system model DyMEG which acts as a simulator of ERP. In particular we focus on the improvement of the pole tide Love number k2. In the frame of a sensitivity analysis k2 has been identified as one of the most crucial parameters of DyMEG since it directly influences the modeled Chandler oscillation. At the same time k2 is one of the most uncertain parameters in the model. Our simulations with DyMEG cover a period of 60 years after which a steady state of k2 is reached. The estimate for k2, accounting for the anelastic response of the Earth's mantle and the ocean, is 0.3531 + 0.0030i. We demonstrate that the application of the improved parameter k2 in DyMEG leads to significantly better results for polar motion than the original value taken from the Conventions of the International Earth Rotation and Reference Systems Service (IERS).

  10. 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

  11. 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.

  12. 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.

  13. Determination of the Earth's pole tide Love number k2 from observations of polar motion using an adaptive Kalman filter approach

    NASA Astrophysics Data System (ADS)

    Seitz, F.; Kirschner, S.; Neubersch, D.

    2012-09-01

    The geophysical interpretation of observed time series of Earth rotation parameters (ERP) is commonly based on numerical models that describe and balance variations of angular momentum in various subsystems of the Earth. Naturally, models are dependent on geometrical, rheological and physical parameters. Many of these are weakly determined from other models or observations. In our study we present an adaptive Kalman filter approach for the improvement of parameters of the dynamic Earth system model DyMEG which acts as a simulator of ERP. In particular we focus on the improvement of the pole tide Love number k2. In the frame of a sensitivity analysis k2 has been identified as one of the most crucial parameters of DyMEG since it directly influences the modeled Chandler oscillation. At the same time k2 is one of the most uncertain parameters in the model. Our simulations with DyMEG cover a period of 60 years after which a steady state of k2 is reached. The estimate for k2, accounting for the anelastic response of the Earth's mantle and the ocean, is 0.3531 + 0.0030i. We demonstrate that the application of the improved parameter k2 in DyMEG leads to significantly better results for polar motion than the original value taken from the Conventions of the International Earth Rotation and Reference Systems Service (IERS).

  14. 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.

  15. 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.

  16. Proper Motions of the Arches Cluster with Keck Laser Guide Star Adaptive Optics: The First Kinematic Mass Measurement of the Arches

    NASA Astrophysics Data System (ADS)

    Clarkson, W. I.; Ghez, A. M.; Morris, M. R.; Lu, J. R.; Stolte, A.; McCrady, N.; Do, T.; Yelda, S.

    2012-06-01

    We report the first detection of the intrinsic velocity dispersion of the Arches cluster—a young (~2 Myr), massive (104 M ⊙) starburst cluster located only 26 pc in projection from the Galactic center. This was accomplished using proper motion measurements within the central 10'' × 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 ~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-1, which corresponds to 5.4 ± 0.4 km s-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+0.74 -0.60 × 104 M ⊙. 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+0.40 -0.35 × 104 M ⊙ at formal 3σ 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 (Γ0 = 1.35, or Γ ~ 1.0 at present, where dN/d(log M)vpropM Γ) suggest a total cluster mass M cl ~ (4-6) × 104 M ⊙ and projected mass (~ 2 <= M(R < 0.4 pc) <= 3) × 104 M ⊙. Photometric mass estimates assuming a globally top-heavy or strongly truncated present-day mass function (PDMF; with Γ ~ 0.6) yield mass estimates closer to M(R < 0.4 pc) ~ 1-1.2 × 104 M ⊙. Consequently, our results support a PDMF that is either top-heavy or truncated at low

  17. 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

  18. 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

  19. Robust Regression.

    PubMed

    Huang, Dong; Cabral, Ricardo; De la Torre, Fernando

    2016-02-01

    Discriminative methods (e.g., kernel regression, SVM) have been extensively used to solve problems such as object recognition, image alignment and pose estimation from images. These methods typically map image features ( X) to continuous (e.g., pose) or discrete (e.g., object category) values. A major drawback of existing discriminative methods is that samples are directly projected onto a subspace and hence fail to account for outliers common in realistic training sets due to occlusion, specular reflections or noise. It is important to notice that existing discriminative approaches assume the input variables X to be noise free. Thus, discriminative methods experience significant performance degradation when gross outliers are present. Despite its obvious importance, the problem of robust discriminative learning has been relatively unexplored in computer vision. This paper develops the theory of robust regression (RR) and presents an effective convex approach that uses recent advances on rank minimization. The framework applies to a variety of problems in computer vision including robust linear discriminant analysis, regression with missing data, and multi-label classification. Several synthetic and real examples with applications to head pose estimation from images, image and video classification and facial attribute classification with missing data are used to illustrate the benefits of RR. PMID:26761740

  20. 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.

  1. Robust acoustic object detection

    NASA Astrophysics Data System (ADS)

    Amit, Yali; Koloydenko, Alexey; Niyogi, Partha

    2005-10-01

    We consider a novel approach to the problem of detecting phonological objects like phonemes, syllables, or words, directly from the speech signal. We begin by defining local features in the time-frequency plane with built in robustness to intensity variations and time warping. Global templates of phonological objects correspond to the coincidence in time and frequency of patterns of the local features. These global templates are constructed by using the statistics of the local features in a principled way. The templates have clear phonetic interpretability, are easily adaptable, have built in invariances, and display considerable robustness in the face of additive noise and clutter from competing speakers. We provide a detailed evaluation of the performance of some diphone detectors and a word detector based on this approach. We also perform some phonetic classification experiments based on the edge-based features suggested here.

  2. 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.

  3. Motion Sickness

    MedlinePlus

    ... people traveling by car, train, airplanes and especially boats. Motion sickness can start suddenly, with a queasy ... motion sickness. For example, down below on a boat, your inner ear senses motion, but your eyes ...

  4. 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

  5. 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.

  6. 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.

  7. Symmetry-adapted-cluster configuration-interaction and equation-of-motion coupled-cluster studies of electronically excited states of copper tetrachloride and copper tetrabromide dianions

    NASA Astrophysics Data System (ADS)

    Ehara, Masahiro; Piecuch, Piotr; Lutz, Jesse J.; Gour, Jeffrey R.

    2012-05-01

    The valence excitation spectra of the copper tetrachloride and copper tetrabromide open-shell dianions, CuCl42- and CuBr42-, respectively, are investigated by a variety of symmetry-adapted-cluster configuration-interaction (SAC-CI) and equation-of-motion coupled-cluster (EOMCC) methods. The valence excited states of the CuCl42- and CuBr42- species that correspond to transitions from doubly occupied molecular orbitals (MOs) to a singly occupied MO (SOMO), for which experimental spectra are available, are examined with the ionized (IP) variants of the SAC-CI and EOMCC methods. The higher-energy excited states of CuCl42- and CuBr42- that correspond to transitions from SOMO to unoccupied MOs, which have not been characterized experimentally, are determined using the electron-attached (EA) SAC-CI and EOMCC approaches. An emphasis is placed on the scalar relativistic SAC-CI and EOMCC calculations based on the spin-free part of the second-order Douglass-Kroll-Hess Hamiltonian (DKH2) and on a comparison of the results of the IP and EA SAC-CI and EOMCC calculations with up to 2-hole-1-particle (2h-1p) and 2-particle-1-hole (2p-1h) excitations, referred to as the IP-SAC-CI SD-R and IP-EOMCCSD(2h-1p) methods in the IP case and EA-SAC-CI SD-R and EA-EOMCCSD(2p-1h) approaches in the EA case, with those obtained with the higher-level IP-EOMCC and EA-EOMCC theories with up to 3-hole-2-particle (3h-2p) and 3-particle-2-hole (3p-2h) excitations treated via active orbitals, abbreviated as IP-EOMCCSD(3h-2p) and EA-EOMCCSD(3p-2h), respectively, as well as with the available experimental data. It is demonstrated that all of the employed DKH2-based IP-SAC-CI and IP-EOMCC methods offer a reliable description of the valence excited states of the CuCl42- and CuBr42- complexes that correspond to transitions from doubly occupied MOs to SOMO, accurately reproducing the observed UV-vis absorption spectra in both peak positions and intensities, which enables a rigorous assignment of the

  8. Computational Motion Phantoms and Statistical Models of Respiratory Motion

    NASA Astrophysics Data System (ADS)

    Ehrhardt, Jan; Klinder, Tobias; Lorenz, Cristian

    Breathing motion is not a robust and 100 % reproducible process, and inter- and intra-fractional motion variations form an important problem in radiotherapy of the thorax and upper abdomen. A widespread consensus nowadays exists that it would be useful to use prior knowledge about respiratory organ motion and its variability to improve radiotherapy planning and treatment delivery. This chapter discusses two different approaches to model the variability of respiratory motion. In the first part, we review computational motion phantoms, i.e. computerized anatomical and physiological models. Computational phantoms are excellent tools to simulate and investigate the effects of organ motion in radiation therapy and to gain insight into methods for motion management. The second part of this chapter discusses statistical modeling techniques to describe the breathing motion and its variability in a population of 4D images. Population-based models can be generated from repeatedly acquired 4D images of the same patient (intra-patient models) and from 4D images of different patients (inter-patient models). The generation of those models is explained and possible applications of those models for motion prediction in radiotherapy are exemplified. Computational models of respiratory motion and motion variability have numerous applications in radiation therapy, e.g. to understand motion effects in simulation studies, to develop and evaluate treatment strategies or to introduce prior knowledge into the patient-specific treatment planning.

  9. 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.

  10. Chaotic neural network applied to two-dimensional motion control.

    PubMed

    Yoshida, Hiroyuki; Kurata, Shuhei; Li, Yongtao; Nara, Shigetoshi

    2010-03-01

    Chaotic dynamics generated in a chaotic neural network model are applied to 2-dimensional (2-D) motion control. The change of position of a moving object in each control time step is determined by a motion function which is calculated from the firing activity of the chaotic neural network. Prototype attractors which correspond to simple motions of the object toward four directions in 2-D space are embedded in the neural network model by designing synaptic connection strengths. Chaotic dynamics introduced by changing system parameters sample intermediate points in the high-dimensional state space between the embedded attractors, resulting in motion in various directions. By means of adaptive switching of the system parameters between a chaotic regime and an attractor regime, the object is able to reach a target in a 2-D maze. In computer experiments, the success rate of this method over many trials not only shows better performance than that of stochastic random pattern generators but also shows that chaotic dynamics can be useful for realizing robust, adaptive and complex control function with simple rules.

  11. How do long-offset oceanic transforms adapt to plate motion changes? The example of the Western Pacific-Antarctic plate boundary

    NASA Astrophysics Data System (ADS)

    Lodolo, Emanuele; Coren, Franco; Ben-Avraham, Zvi

    2013-03-01

    Oceanic transform faults respond to changes in the direction of relative plate motion. Studies have shown that short-offset transforms generally adjust with slight bends near the ridge axis, while long-offset ones have a remarkably different behavior. The western Pacific-Antarctic plate boundary highlights these differences. A set of previously unpublished seismic profiles, in combination with magnetic anomaly identifications, shows how across a former, ~1250 km long transform (the Emerald Fracture Zone), plate motion changes have produced a complex geometric readjustment. Three distinct sections are recognized along this plate boundary: an eastern section, characterized by parallel, multiple fault strand lineaments; a central section, shallower than the rest of the ridge system, overprinted by a mantle plume track; and a western section, organized in a cascade of short spreading axes/transform lineaments. This configuration was produced by changes that occurred since 30 Ma in the Australia-Pacific relative plate motion, combined with a gradual clockwise change in Pacific-Antarctic plate motion. These events caused extension along the former Emerald Fracture Zone, originally linking the Pacific-Antarctic spreading ridge system with the Southeast Indian ridge. Then an intra-transform propagating ridge started to develop in response to a ~6 Ma change in the Pacific-Antarctic spreading direction. The close proximity of the Euler poles of rotation amplified the effects of the geometric readjustments that occurred along the transform system. This analysis shows that when a long-offset transform older than 20 Ma is pulled apart by changes in spreading velocity vectors, it responds with the development of multiple discrete, parallel fault strands, whereas in younger lithosphere, locally modified by thermal anisotropies, tensional stresses generate an array of spreading axes offset by closely spaced transforms.

  12. 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.

  13. 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.

  14. Robust multiplatform RF emitter localization

    NASA Astrophysics Data System (ADS)

    Al Issa, Huthaifa; Ordóñez, Raúl

    2012-06-01

    In recent years, position based services has increase. Thus, recent developments in communications and RF technology have enabled system concept formulations and designs for low-cost radar systems using state-of-the-art software radio modules. This research is done to investigate a novel multi-platform RF emitter localization technique denoted as Position-Adaptive RF Direction Finding (PADF). The formulation is based on the investigation of iterative path-loss (i.e., Path Loss Exponent, or PLE) metrics estimates that are measured across multiple platforms in order to autonomously adapt (i.e. self-adjust) of the location of each distributed/cooperative platform. Experiments conducted at the Air-Force Research laboratory (AFRL) indicate that this position-adaptive approach exhibits potential for accurate emitter localization in challenging embedded multipath environments such as in urban environments. The focus of this paper is on the robustness of the distributed approach to RF-based location tracking. In order to localize the transmitter, we use the Received Signal Strength Indicator (RSSI) data to approximate distance from the transmitter to the revolving receivers. We provide an algorithm for on-line estimation of the Path Loss Exponent (PLE) that is used in modeling the distance based on Received Signal Strength (RSS) measurements. The emitter position estimation is calculated based on surrounding sensors RSS values using Least-Square Estimation (LSE). The PADF has been tested on a number of different configurations in the laboratory via the design and implementation of four IRIS wireless sensor nodes as receivers and one hidden sensor as a transmitter during the localization phase. The robustness of detecting the transmitters position is initiated by getting the RSSI data through experiments and then data manipulation in MATLAB will determine the robustness of each node and ultimately that of each configuration. The parameters that are used in the functions are

  15. Motion sickness.

    PubMed

    Golding, J F

    2016-01-01

    Over 2000 years ago the Greek physician Hippocrates wrote, "sailing on the sea proves that motion disorders the body." Indeed, the word "nausea" derives from the Greek root word naus, hence "nautical," meaning a ship. The primary signs and symptoms of motion sickness are nausea and vomiting. Motion sickness can be provoked by a wide variety of transport environments, including land, sea, air, and space. The recent introduction of new visual technologies may expose more of the population to visually induced motion sickness. This chapter describes the signs and symptoms of motion sickness and different types of provocative stimuli. The "how" of motion sickness (i.e., the mechanism) is generally accepted to involve sensory conflict, for which the evidence is reviewed. New observations concern the identification of putative "sensory conflict" neurons and the underlying brain mechanisms. But what reason or purpose does motion sickness serve, if any? This is the "why" of motion sickness, which is analyzed from both evolutionary and nonfunctional maladaptive theoretic perspectives. Individual differences in susceptibility are great in the normal population and predictors are reviewed. Motion sickness susceptibility also varies dramatically between special groups of patients, including those with different types of vestibular disease and in migraineurs. Finally, the efficacy and relative advantages and disadvantages of various behavioral and pharmacologic countermeasures are evaluated. PMID:27638085

  16. 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.

  17. Adaptive mean-shift tracking with auxiliary particles.

    PubMed

    Wang, Junqiu; Yagi, Yasushi

    2009-12-01

    We present a new approach for robust and efficient tracking by incorporating the efficiency of the mean-shift algorithm with the multihypothesis characteristics of particle filtering in an adaptive manner. The aim of the proposed algorithm is to cope with problems that were brought about by sudden motions and distractions. The mean-shift tracking algorithm is robust and effective when the representation of a target is sufficiently discriminative, the target does not jump beyond the bandwidth, and no serious distractions exist. We propose a novel two-stage motion estimation method that is efficient and reliable. If a sudden motion is detected by the motion estimator, some particle-filtering-based trackers can be used to outperform the mean-shift algorithm, at the expense of using a large particle set. In our approach, the mean-shift algorithm is used, as long as it provides reasonable performance. Auxiliary particles are introduced to cope with distractions and sudden motions when such threats are detected. Moreover, discriminative features are selected according to the separation of the foreground and background distributions when threats do not exist. This strategy is important, because it is dangerous to update the target model when the tracking is in an unsteady state. We demonstrate the performance of our approach by comparing it with other trackers in tracking several challenging image sequences.

  18. Fast robust correlation.

    PubMed

    Fitch, Alistair J; Kadyrov, Alexander; Christmas, William J; Kittler, Josef

    2005-08-01

    A new, fast, statistically robust, exhaustive, translational image-matching technique is presented: fast robust correlation. Existing methods are either slow or non-robust, or rely on optimization. Fast robust correlation works by expressing a robust matching surface as a series of correlations. Speed is obtained by computing correlations in the frequency domain. Computational cost is analyzed and the method is shown to be fast. Speed is comparable to conventional correlation and, for large images, thousands of times faster than direct robust matching. Three experiments demonstrate the advantage of the technique over standard correlation.

  19. Visual motion detection sensitivity is enhanced by an orthogonal motion aftereffect.

    PubMed

    Takemura, Hiromasa; Murakami, Ikuya

    2010-09-09

    A recent study (H. Takemura & I. Murakami, 2010) showed enhancement of motion detection sensitivity by an orthogonal induced motion, suggesting that a weak motion component can combine with an orthogonal motion component to generate stronger oblique motion perception. Here we examined how an orthogonal motion aftereffect (MAE) affects motion detection sensitivity. After adaptation to vertical motion, a Gabor patch barely moving leftward or rightward was presented. As a result of an interaction between horizontal physical motion and a vertical MAE, subjects perceived the stimulus as moving obliquely. Subjects were asked to judge the horizontal direction of motion irrespective of the vertical MAE. The performance was enhanced when the Gabor patch was perceived as moving obliquely as the result of a weak MAE. The enhancement effect depended on the strength of the MAE for each subject rather than on the temporal frequency of the adapting stimulus. These results suggest that weak motion information that is hard to detect can interact with orthogonal adaptation and yield stronger oblique motion perception, making directional judgment easier. Moreover, the present results indicate that the enhancement effect of orthogonal motion involves general motion integration mechanisms rather than a specific mechanism only applicable to a particular type of illusory motion.

  20. Lossless and near-lossless digital angiography coding using a two-stage motion compensation approach.

    PubMed

    dos Santos, Rafael A P; Scharcanski, Jacob

    2008-07-01

    This paper presents a two-stage motion compensation coding scheme for image sequences in hemodynamics. The first stage of the proposed method implements motion compensation, and the second stage corrects local pixel intensity distortions with a context adaptive linear predictor. The proposed method is robust to the local intensity distortions and the noise that often degrades these image sequences, providing lossless and near-lossless quality. Our experiments with lossless compression of 12bits/pixel studies indicate that, potentially, our approach can perform 3.8%, 2% and 1.6% better than JPEG-2000, JPEG-LS and the method proposed by Scharcanski [1], respectively. The performance tends to improve for near-lossless compression. Therefore, this work presents experimental evidence that for coding image sequences in hemodynamics, an adequate motion compensation scheme can be more efficient than the still-image coding methods often used nowadays.

  1. Opponent backgrounds reduce discrimination sensitivity to competing motions: effects of different vertical motions on horizontal motion perception.

    PubMed

    Silva, Andrew E; Liu, Zili

    2015-08-01

    We examined the relationship between two distinct motion phenomena. First, locally balanced stimuli in which opposing motion signals are presented spatially near one another fail to cause a robust firing pattern in brain area MT. The brain's response to this motion is effectively suppressed, a phenomenon known as opponency. Second, past research has found that discrimination sensitivity to a target motion is negatively affected by a superimposed irrelevant motion signal - a process we call "perceptual suppression." In the current study, we examined how opponency affects the strength of perceptual suppression. We found unexpected results: a target motion embedded within an opponent background was harder to discriminate than a target motion embedded within a non-opponent background. We argue that this pattern of results runs contrary to the clear prediction stemming from the current understanding of the role of opponency in motion processing and tentatively offer an explanation based on recent MT physiology.

  2. 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.

  3. Robust parametric estimation over optimal support of fluid flow structure in multispectral image sequences

    NASA Astrophysics Data System (ADS)

    Rougon, Nicolas F.; Brossard-Pailleux, M. A.; Preteux, Francoise J.

    2000-10-01

    This article presents a methodology for analyzing the Lagrangian structure of fluid flows generated by the evolution of cloud systems in meteorological multispectral image sequences. The correlation between the orientation of cloud texture and the underlying motion field Lagrangian component allows to adopt a static strategy. Following a scale-space approach, we therefore first construct a non-local robust estimator for the locally dominant orientation field in an image. This estimator, which is derived from the image structure tensor, is relevant in both mono- and multisprectral contexts. In a second step, the Lagrangian component of the flow is estimated over some bounded image region by robustly fitting a hierarchical vector parametric model to the dominant orientation field. Here, a recurrent problem deals with adaptating the geometry of the model support to obtain unbiased estimates. To tackle this classic issue, we introduce a novel variational, semi-parametric approach which allows the joint optimization of model parameters and support. This approach is generic and, in particular, can be readily applied to motion estimation yielding robust measurement of the Eulerian structure of the flow. Finally, a structural characterization of the reflecting vector field is derived by means of classic differential geometry techniques. This methodology is applied to the analysis of temperated latitude depressions in Meteosat images.

  4. 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

  5. Robustness: confronting lessons from physics and biology.

    PubMed

    Lesne, Annick

    2008-11-01

    The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems. PMID:18823391

  6. 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

  7. Environmental change makes robust ecological networks fragile.

    PubMed

    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

  8. 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.

  9. Biological Robustness: Paradigms, Mechanisms, and Systems Principles

    PubMed Central

    Whitacre, James Michael

    2012-01-01

    Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g., mutational, environmental) are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior. PMID:22593762

  10. Biological robustness: paradigms, mechanisms, and systems principles.

    PubMed

    Whitacre, James Michael

    2012-01-01

    Robustness has been studied through the analysis of data sets, simulations, and a variety of experimental techniques that each have their own limitations but together confirm the ubiquity of biological robustness. Recent trends suggest that different types of perturbation (e.g., mutational, environmental) are commonly stabilized by similar mechanisms, and system sensitivities often display a long-tailed distribution with relatively few perturbations representing the majority of sensitivities. Conceptual paradigms from network theory, control theory, complexity science, and natural selection have been used to understand robustness, however each paradigm has a limited scope of applicability and there has been little discussion of the conditions that determine this scope or the relationships between paradigms. Systems properties such as modularity, bow-tie architectures, degeneracy, and other topological features are often positively associated with robust traits, however common underlying mechanisms are rarely mentioned. For instance, many system properties support robustness through functional redundancy or through response diversity with responses regulated by competitive exclusion and cooperative facilitation. Moreover, few studies compare and contrast alternative strategies for achieving robustness such as homeostasis, adaptive plasticity, environment shaping, and environment tracking. These strategies share similarities in their utilization of adaptive and self-organization processes that are not well appreciated yet might be suggestive of reusable building blocks for generating robust behavior. PMID:22593762

  11. 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.

  12. 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.

  13. Low-level motion analysis of color and luminance for perception of 2D and 3D motion.

    PubMed

    Shioiri, Satoshi; Yoshizawa, Masanori; Ogiya, Mistuharu; Matsumiya, Kazumichi; Yaguchi, Hirohisa

    2012-01-01

    We investigated the low-level motion mechanisms for color and luminance and their integration process using 2D and 3D motion aftereffects (MAEs). The 2D and 3D MAEs obtained in equiluminant color gratings showed that the visual system has the low-level motion mechanism for color motion as well as for luminance motion. The 3D MAE is an MAE for motion in depth after monocular motion adaptation. Apparent 3D motion can be perceived after prolonged exposure of one eye to lateral motion because the difference in motion signal between the adapted and unadapted eyes generates interocular velocity differences (IOVDs). Since IOVDs cannot be analyzed by the high-level motion mechanism of feature tracking, we conclude that a low-level motion mechanism is responsible for the 3D MAE. Since we found different temporal frequency characteristics between the color and luminance stimuli, MAEs in the equiluminant color stimuli cannot be attributed to a residual luminance component in the color stimulus. Although a similar MAE was found with a luminance and a color test both for 2D and 3D motion judgments after adapting to either color or luminance motion, temporal frequency characteristics were different between the color and luminance adaptation. The visual system must have a low-level motion mechanism for color signals as for luminance ones. We also found that color and luminance motion signals are integrated monocularly before IOVD analysis, showing a cross adaptation effect between color and luminance stimuli. This was supported by an experiment with dichoptic presentations of color and luminance tests. In the experiment, color and luminance tests were presented in the different eyes dichoptically with four different combinations of test and adaptation: color or luminance test in the adapted eye after color or luminance adaptation. Findings of little or no influence of the adaptation/test combinations indicate the integration of color and luminance motion signals prior to the

  14. 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.

  15. Fast motion deblurring using sensor-aided motion trajectory estimation.

    PubMed

    Lee, Eunsung; Chae, Eunjung; Cheong, Hejin; Paik, Joonki

    2014-01-01

    This paper presents an image deblurring algorithm to remove motion blur using analysis of motion trajectories and local statistics based on inertial sensors. The proposed method estimates a point-spread-function (PSF) of motion blur by accumulating reweighted projections of the trajectory. A motion blurred image is then adaptively restored using the estimated PSF and spatially varying activity map to reduce both restoration artifacts and noise amplification. Experimental results demonstrate that the proposed method outperforms existing PSF estimation-based motion deconvolution methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed in various imaging devices because of its efficient implementation without an iterative computational structure.

  16. 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

  17. 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.

  18. Context adaptive lossless and near-lossless coding for digital angiographies.

    PubMed

    dos Santos, Rafael A P; Scharcanski, Jacob

    2007-01-01

    This paper presents a context adaptive coding method for image sequences in hemodynamics. The proposed method implements motion compensation through of a two-stage context adaptive linear predictor. It is robust to the local intensity changes and the noise that often degrades these image sequences, and provides lossless and near-lossless quality. Our preliminary experiments with lossless compression of 12 bits/pixel studies indicate that, potentially, our approach can perform 3.8%, 2% and 1.6% better than JPEG-2000, JPEG-LS and the method proposed in [1], respectively. The performance tends to improve for near-lossless compression.

  19. Dynamic engagement of human motion detectors across space-time coordinates.

    PubMed

    Neri, Peter

    2014-06-18

    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.

  20. Dynamic engagement of human motion detectors across space-time coordinates.

    PubMed

    Neri, Peter

    2014-06-18

    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

  1. A dynamic human motion: coordination analysis.

    PubMed

    Pchelkin, Stepan; Shiriaev, Anton S; Freidovich, Leonid B; Mettin, Uwe; Gusev, Sergei V; Kwon, Woong; Paramonov, Leonid

    2015-02-01

    This article is concerned with the generic structure of the motion coordination system resulting from the application of the method of virtual holonomic constraints (VHCs) to the problem of the generation and robust execution of a dynamic humanlike motion by a humanoid robot. The motion coordination developed using VHCs is based on a motion generator equation, which is a scalar nonlinear differential equation of second order. It can be considered equivalent in function to a central pattern generator in living organisms. The relative time evolution of the degrees of freedom of a humanoid robot during a typical motion are specified by a set of coordination functions that uniquely define the overall pattern of the motion. This is comparable to a hypothesis on the existence of motion patterns in biomechanics. A robust control is derived based on a transverse linearization along the configuration manifold defined by the coordination functions. It is shown that the derived coordination and control architecture possesses excellent robustness properties. The analysis is performed on an example of a real human motion recorded in test experiments.

  2. Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

    PubMed Central

    Brinkworth, Russell S. A.; O'Carroll, David C.

    2009-01-01

    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. PMID:19893631

  3. Biological Form is Sufficient to Create a Biological Motion Sex Aftereffect.

    PubMed

    Hiris, Eric; Mirenzi, Aaron; Janis, Katie

    2016-10-01

    In a series of five experiments we sought to determine what causes the biological motion sex aftereffect-adaptation of a general representation of the stimulus sex, adaptation to the motion in the stimulus, or adaptation to the form in the stimulus. The experiments showed that (a) adaptation to gendered faces and gendered full body images did not create a biological motion sex aftereffect; (b) adaptation to moving partial biological motion displays containing the most important motion cues for sex discrimination (shoulders and hips or shoulders, hips, and feet) did not create a biological motion sex aftereffect; and (c) adaptation to a static frame or shapes derived from a static frame did create a biological motion sex aftereffect. These results suggest that form information is sufficient to create a biological motion sex aftereffect and suggests that biological motion sex aftereffects may be a result of lower level rather than higher level adaptation in the visual system.

  4. What's Motion Sickness?

    MedlinePlus

    ... Homework? Here's Help White House Lunch Recipes What's Motion Sickness? KidsHealth > For Kids > What's Motion Sickness? Print ... motion sickness might get even worse. continue Avoiding Motion Sickness To avoid motion sickness: Put your best ...

  5. 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)

  6. Respiratory Motion Prediction in Radiation Therapy

    NASA Astrophysics Data System (ADS)

    Vedam, Sastry

    Active respiratory motion management has received increasing attention in the past decade as a means to reduce the internal margin (IM) component of the clinical target volume (CTV)—planning target volume (PTV) margin typically added around the gross tumor volume (GTV) during radiation therapy of thoracic and abdominal tumors. Engineering and technical developments in linear accelerator design and respiratory motion monitoring respectively have made the delivery of motion adaptive radiation therapy possible through real-time control of either dynamic multileaf collimator (MLC) motion (gantry based linear accelerator design) or robotic arm motion (robotic arm mounted linear accelerator design).

  7. Motion restraining device

    NASA Technical Reports Server (NTRS)

    Ford, A. G. (Inventor)

    1977-01-01

    A motion-restraining device for dissipating at a controlled rate the force of a moving body is discussed. The device is characterized by a drive shaft adapted to be driven in rotation by a moving body connected to a tape wound about a reel mounted on the drive shaft, and an elongated pitman link having one end pivotally connected to the crankshaft and the opposite end thereof connected with the mass through an energy dissipating linkage. A shuttle is disposed within a slot and guided by rectilinear motion between a pair of spaced impact surfaces. Reaction forces applied at impact of the shuttle with the impact surfaces include oppositely projected force components angularly related to the direction of the applied impact forces.

  8. 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.

  9. Motion correction in MRI of the brain.

    PubMed

    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.

  10. 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.

  11. 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…

  12. 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.

  13. 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.

  14. 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.

  15. [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.

  16. 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

  17. Robust Methods in Qsar

    NASA Astrophysics Data System (ADS)

    Walczak, Beata; Daszykowski, Michał; Stanimirova, Ivana

    A large progress in the development of robust methods as an efficient tool for processing of data contaminated with outlying objects has been made over the last years. Outliers in the QSAR studies are usually the result of an improper calculation of some molecular descriptors and/or experimental error in determining the property to be modelled. They influence greatly any least square model, and therefore the conclusions about the biological activity of a potential component based on such a model are misleading. With the use of robust approaches, one can solve this problem building a robust model describing the data majority well. On the other hand, the proper identification of outliers may pinpoint a new direction of a drug development. The outliers' assessment can exclusively be done with robust methods and these methods are to be described in this chapter

  18. Robustness of airline alliance route networks

    NASA Astrophysics Data System (ADS)

    Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

    2015-05-01

    The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

  19. A system for learning statistical motion patterns.

    PubMed

    Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

    2006-09-01

    Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction. PMID:16929731

  20. 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.

  1. 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.

  2. Adaptive feature annotation for large video sensor networks

    NASA Astrophysics Data System (ADS)

    Cai, Yang; Bunn, Andrew; Liang, Peter; Yang, Bing

    2013-10-01

    We present an adaptive feature extraction and annotation algorithm for articulating traffic events from surveillance cameras. We use approximate median filter for moving object detection, motion energy image and convex hull for lane detection, and adaptive proportion models for vehicle classification. It is found that our approach outperforms three-dimensional modeling and scale-independent feature transformation algorithms in terms of robustness. The multiresolution-based video codec algorithm enables a quality-of-service-aware video streaming according to the data traffic. Furthermore, our empirical data shows that it is feasible to use the metadata to facilitate the real-time communication between an infrastructure and a vehicle for safer and more efficient traffic control.

  3. 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.

  4. 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.

  5. 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.

  6. MotionExplorer: exploratory search in human motion capture data based on hierarchical aggregation.

    PubMed

    Bernard, Jürgen; Wilhelm, Nils; Krüger, Björn; May, Thorsten; Schreck, Tobias; Kohlhammer, Jörn

    2013-12-01

    We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work. PMID:24051792

  7. FPGA implementation of robust Capon beamformer

    NASA Astrophysics Data System (ADS)

    Guan, Xin; Zmuda, Henry; Li, Jian; Du, Lin; Sheplak, Mark

    2012-03-01

    The Capon Beamforming algorithm is an optimal spatial filtering algorithm used in various signal processing applications where excellent interference rejection performance is required, such as Radar and Sonar systems, Smart Antenna systems for wireless communications. Its lack of robustness, however, means that it is vulnerable to array calibration errors and other model errors. To overcome this problem, numerous robust Capon Beamforming algorithms have been proposed, which are much more promising for practical applications. In this paper, an FPGA implementation of a robust Capon Beamforming algorithm is investigated and presented. This realization takes an array output with 4 channels, computes the complex-valued adaptive weight vectors for beamforming with an 18 bit fixed-point representation and runs at a 100 MHz clock on Xilinx V4 FPGA. This work will be applied in our medical imaging project for breast cancer detection.

  8. 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.

  9. Robust neural-network control of rigid-link electrically driven robots.

    PubMed

    Kwan, C; Lewis, F L; Dawson, D M

    1998-01-01

    A robust neural-network (NN) controller is proposed for the motion control of rigid-link electrically driven (RLED) robots. Two-layer NN's are used to approximate two very complicated nonlinear functions. The main advantage of our approach is that the NN weights are tuned on-line, with no off-line learning phase required. Most importantly, we can guarantee the uniformly ultimately bounded (UUB) stability of tracking errors and NN weights. When compared with standard adaptive robot controllers, we do not require lengthy and tedious preliminary analysis to determine a regression matrix. The controller can be regarded as a universal reusable controller because the same controller can be applied to any type of RLED robots without any modifications.

  10. Robust laser-based detection of Lamb waves using photo-EMF sensors

    NASA Astrophysics Data System (ADS)

    Klein, Marvin B.; Bacher, Gerald D.

    1998-03-01

    Lamb waves are easily generated and detected using laser techniques. It has been shown that both symmetric and antisymmetric modes can be produced, using single-spot and phased array generation. Detection has been demonstrated with Michelson interferometers, but these instruments can not function effectively on rough surfaces. By contrast, the confocal Fabry-Perot interferometer can interrogate rough surfaces, but generally is not practical for operation below 300 kHz. In this paper we will present Lamb wave data on a number of parts using a robust, adaptive receiver based on photo-emf detection. This receiver has useful sensitivity down to at least 100 kHz, can process speckled beams and can be easily configured to measure both out-of-plane and in- plane motion with a single probe beam.

  11. 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

  12. 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.

  13. 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.

  14. Motion feature extraction scheme for content-based video retrieval

    NASA Astrophysics Data System (ADS)

    Wu, Chuan; He, Yuwen; Zhao, Li; Zhong, Yuzhuo

    2001-12-01

    This paper proposes the extraction scheme of global motion and object trajectory in a video shot for content-based video retrieval. Motion is the key feature representing temporal information of videos. And it is more objective and consistent compared to other features such as color, texture, etc. Efficient motion feature extraction is an important step for content-based video retrieval. Some approaches have been taken to extract camera motion and motion activity in video sequences. When dealing with the problem of object tracking, algorithms are always proposed on the basis of known object region in the frames. In this paper, a whole picture of the motion information in the video shot has been achieved through analyzing motion of background and foreground respectively and automatically. 6-parameter affine model is utilized as the motion model of background motion, and a fast and robust global motion estimation algorithm is developed to estimate the parameters of the motion model. The object region is obtained by means of global motion compensation between two consecutive frames. Then the center of object region is calculated and tracked to get the object motion trajectory in the video sequence. Global motion and object trajectory are described with MPEG-7 parametric motion and motion trajectory descriptors and valid similar measures are defined for the two descriptors. Experimental results indicate that our proposed scheme is reliable and efficient.

  15. 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

  16. 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

  17. Ultrasound image-based respiratory motion tracking

    NASA Astrophysics Data System (ADS)

    Hwang, Youngkyoo; Kim, Jung-Bae; Kim, Yong Sun; Bang, Won-Chul; Kim, James D. K.; Kim, ChangYeong

    2012-03-01

    Respiratory motion tracking has been issues for MR/CT imaging and noninvasive surgery such as HIFU and radiotherapy treatment when we apply these imaging or therapy technologies to moving organs such as liver, kidney or pancreas. Currently, some bulky and burdensome devices are placed externally on skin to estimate respiratory motion of an organ. It estimates organ motion indirectly using skin motion, not directly using organ itself. In this paper, we propose a system that measures directly the motion of organ itself only using ultrasound image. Our system has automatically selected a window in image sequences, called feature window, which is able to measure respiratory motion robustly even to noisy ultrasound images. The organ's displacement on each ultrasound image has been directly calculated through the feature window. It is very convenient to use since it exploits a conventional ultrasound probe. In this paper, we show that our proposed method can robustly extract respiratory motion signal with regardless of reference frame. It is superior to other image based method such as Mutual Information (MI) or Correlation Coefficient (CC). They are sensitive to what the reference frame is selected. Furthermore, our proposed method gives us clear information of the phase of respiratory cycle such as during inspiration or expiration and so on since it calculate not similarity measurement like MI or CC but actual organ's displacement.

  18. 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.

  19. 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…

  20. 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.

  1. Robust atomic force microscopy using multiple sensors.

    PubMed

    Baranwal, Mayank; Gorugantu, Ram S; Salapaka, Srinivasa M

    2016-08-01

    Atomic force microscopy typically relies on high-resolution high-bandwidth cantilever deflection measurements based control for imaging and estimating sample topography and properties. More precisely, in amplitude-modulation atomic force microscopy (AM-AFM), the control effort that regulates deflection amplitude is used as an estimate of sample topography; similarly, contact-mode AFM uses regulation of deflection signal to generate sample topography. In this article, a control design scheme based on an additional feedback mechanism that uses vertical z-piezo motion sensor, which augments the deflection based control scheme, is proposed and evaluated. The proposed scheme exploits the fact that the piezo motion sensor, though inferior to the cantilever deflection signal in terms of resolution and bandwidth, provides information on piezo actuator dynamics that is not easily retrievable from the deflection signal. The augmented design results in significant improvements in imaging bandwidth and robustness, especially in AM-AFM, where the complicated underlying nonlinear dynamics inhibits estimating piezo motions from deflection signals. In AM-AFM experiments, the two-sensor based design demonstrates a substantial improvement in robustness to modeling uncertainties by practically eliminating the peak in the sensitivity plot without affecting the closed-loop bandwidth when compared to a design that does not use the piezo-position sensor based feedback. The contact-mode imaging results, which use proportional-integral controllers for cantilever-deflection regulation, demonstrate improvements in bandwidth and robustness to modeling uncertainties, respectively, by over 30% and 20%. The piezo-sensor based feedback is developed using H∞ control framework. PMID:27587128

  2. Robust atomic force microscopy using multiple sensors

    NASA Astrophysics Data System (ADS)

    Baranwal, Mayank; Gorugantu, Ram S.; Salapaka, Srinivasa M.

    2016-08-01

    Atomic force microscopy typically relies on high-resolution high-bandwidth cantilever deflection measurements based control for imaging and estimating sample topography and properties. More precisely, in amplitude-modulation atomic force microscopy (AM-AFM), the control effort that regulates deflection amplitude is used as an estimate of sample topography; similarly, contact-mode AFM uses regulation of deflection signal to generate sample topography. In this article, a control design scheme based on an additional feedback mechanism that uses vertical z-piezo motion sensor, which augments the deflection based control scheme, is proposed and evaluated. The proposed scheme exploits the fact that the piezo motion sensor, though inferior to the cantilever deflection signal in terms of resolution and bandwidth, provides information on piezo actuator dynamics that is not easily retrievable from the deflection signal. The augmented design results in significant improvements in imaging bandwidth and robustness, especially in AM-AFM, where the complicated underlying nonlinear dynamics inhibits estimating piezo motions from deflection signals. In AM-AFM experiments, the two-sensor based design demonstrates a substantial improvement in robustness to modeling uncertainties by practically eliminating the peak in the sensitivity plot without affecting the closed-loop bandwidth when compared to a design that does not use the piezo-position sensor based feedback. The contact-mode imaging results, which use proportional-integral controllers for cantilever-deflection regulation, demonstrate improvements in bandwidth and robustness to modeling uncertainties, respectively, by over 30% and 20%. The piezo-sensor based feedback is developed using H∞ control framework.

  3. Robustness analysis of elastoplastic structure subjected to double impulse

    NASA Astrophysics Data System (ADS)

    Kanno, Yoshihiro; Takewaki, Izuru

    2016-11-01

    The double impulse has extensively been used to evaluate the critical response of an elastoplastic structure against a pulse-type input, including near-fault earthquake ground motions. In this paper, we propose a robustness assessment method for elastoplastic single-degree-of-freedom structures subjected to the double impulse input. Uncertainties in the initial velocity of the input, as well as the natural frequency and the strength of the structure, are considered. As fundamental properties of the structural robustness, we show monotonicity of the robustness measure with respect to the natural frequency. In contrast, we show that robustness is not necessarily improved even if the structural strength is increased. Moreover, the robustness preference between two structures with different values of structural strength can possibly reverse when the performance requirement is changed.

  4. Perceptual shrinkage of a one-way motion path with high-speed motion.

    PubMed

    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

  5. Perceptual shrinkage of a one-way motion path with high-speed motion.

    PubMed

    Nakajima, Yutaka; Sakaguchi, Yutaka

    2016-07-28

    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.

  6. 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

  7. 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.

  8. Higher-order motion sensitivity in fly visual circuits

    PubMed Central

    Lee, Yu-Jen; Nordström, Karin

    2012-01-01

    In higher-order motion stimuli, the direction of object motion does not follow the direction of luminance change. Such stimuli could be generated by the wing movements of a flying butterfly and further complicated by its motion in and out of shadows. Human subjects readily perceive the direction of higher-order motion, although this stands in stark contrast to prevailing motion vision models. Flies and humans compute motion in similar ways, and because flies behaviorally track bars containing higher-order motion cues, they become an attractive model system for investigating the neurophysiology underlying higher-order motion sensitivity. We here use intracellular electrophysiology of motion-vision–sensitive neurons in the hoverfly lobula plate to quantify responses to stimuli containing higher-order motion. We show that motion sensitivity can be broken down into two separate streams, directionally coding for elementary motion and figure motion, respectively, and that responses to Fourier and theta motion can be predicted from these. The sensitivity is affected both by the stimulus’ time course and by the neuron’s underlying receptive field. Responses to preferred-direction theta motion are sexually dimorphic and particularly robust along the visual midline. PMID:22586123

  9. Auditory motion affects visual biological motion processing.

    PubMed

    Brooks, A; van der Zwan, R; Billard, A; Petreska, B; Clarke, S; Blanke, O

    2007-02-01

    The processing of biological motion is a critical, everyday task performed with remarkable efficiency by human sensory systems. Interest in this ability has focused to a large extent on biological motion processing in the visual modality (see, for example, Cutting, J. E., Moore, C., & Morrison, R. (1988). Masking the motions of human gait. Perception and Psychophysics, 44(4), 339-347). In naturalistic settings, however, it is often the case that biological motion is defined by input to more than one sensory modality. For this reason, here in a series of experiments we investigate behavioural correlates of multisensory, in particular audiovisual, integration in the processing of biological motion cues. More specifically, using a new psychophysical paradigm we investigate the effect of suprathreshold auditory motion on perceptions of visually defined biological motion. Unlike data from previous studies investigating audiovisual integration in linear motion processing [Meyer, G. F. & Wuerger, S. M. (2001). Cross-modal integration of auditory and visual motion signals. Neuroreport, 12(11), 2557-2560; Wuerger, S. M., Hofbauer, M., & Meyer, G. F. (2003). The integration of auditory and motion signals at threshold. Perception and Psychophysics, 65(8), 1188-1196; Alais, D. & Burr, D. (2004). No direction-specific bimodal facilitation for audiovisual motion detection. Cognitive Brain Research, 19, 185-194], we report the existence of direction-selective effects: relative to control (stationary) auditory conditions, auditory motion in the same direction as the visually defined biological motion target increased its detectability, whereas auditory motion in the opposite direction had the inverse effect. Our data suggest these effects do not arise through general shifts in visuo-spatial attention, but instead are a consequence of motion-sensitive, direction-tuned integration mechanisms that are, if not unique to biological visual motion, at least not common to all types of

  10. 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.

  11. 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. PMID:26529374

  12. The tactile motion aftereffect suggests an intensive code for speed in neurons sensitive to both speed and direction of motion.

    PubMed

    McIntyre, S; Birznieks, I; Vickery, R M; Holcombe, A O; Seizova-Cajic, T

    2016-03-01

    Neurophysiological studies in primates have found that direction-sensitive neurons in the primary somatosensory cortex (SI) generally increase their response rate with increasing speed of object motion across the skin and show little evidence of speed tuning. We employed psychophysics to determine whether human perception of motion direction could be explained by features of such neurons and whether evidence can be found for a speed-tuned process. After adaptation to motion across the skin, a subsequently presented dynamic test stimulus yields an impression of motion in the opposite direction. We measured the strength of this tactile motion aftereffect (tMAE) induced with different combinations of adapting and test speeds. Distal-to-proximal or proximal-to-distal adapting motion was applied to participants' index fingers using a tactile array, after which participants reported the perceived direction of a bidirectional test stimulus. An intensive code for speed, like that observed in SI neurons, predicts greater adaptation (and a stronger tMAE) the faster the adapting speed, regardless of the test speed. In contrast, speed tuning of direction-sensitive neurons predicts the greatest tMAE when the adapting and test stimuli have matching speeds. We found that the strength of the tMAE increased monotonically with adapting speed, regardless of the test speed, showing no evidence of speed tuning. Our data are consistent with neurophysiological findings that suggest an intensive code for speed along the motion processing pathways comprising neurons sensitive both to speed and direction of motion. PMID:26823511

  13. The "motion silencing" illusion results from global motion and crowding.

    PubMed

    Turi, Marco; Burr, David

    2013-04-18

    Suchow and Alvarez (2011) recently devised a striking illusion, where objects changing in color, luminance, size, or shape appear to stop changing when they move. They refer to the illusion as "motion silencing of awareness to visual change." Here we present evidence that the illusion results from two perceptual processes: global motion and crowding. We adapted Suchow and Alvarez's stimulus to three concentric rings of dots, a central ring of "target dots" flanked on either side by similarly moving flanker dots. Subjects had to identify in which of two presentations the target dots were continuously changing (sinusoidally) in size, as distinct from the other interval in which size was constant. The results show: (a) Motion silencing depends on target speed, with a threshold around 0.2 rotations per second (corresponding to about 10°/s linear motion). (b) Silencing depends on both target-flanker spacing and eccentricity, with critical spacing about half eccentricity, consistent with Bouma's law. (c) The critical spacing was independent of stimulus size, again consistent with Bouma's law. (d) Critical spacing depended strongly on contrast polarity. All results imply that the "motion silencing" illusion may result from crowding.

  14. Doubly robust survival trees.

    PubMed

    Steingrimsson, Jon Arni; Diao, Liqun; Molinaro, Annette M; Strawderman, Robert L

    2016-09-10

    Estimating a patient's mortality risk is important in making treatment decisions. Survival trees are a useful tool and employ recursive partitioning to separate patients into different risk groups. Existing 'loss based' recursive partitioning procedures that would be used in the absence of censoring have previously been extended to the setting of right censored outcomes using inverse probability censoring weighted estimators of loss functions. In this paper, we propose new 'doubly robust' extensions of these loss estimators motivated by semiparametric efficiency theory for missing data that better utilize available data. Simulations and a data analysis demonstrate strong performance of the doubly robust survival trees compared with previously used methods. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27037609

  15. Adaptive attitude control and momentum management for large-angle spacecraft maneuvers

    NASA Technical Reports Server (NTRS)

    Parlos, Alexander G.; Sunkel, John W.

    1992-01-01

    The fully coupled equations of motion are systematically linearized around an equilibrium point of a gravity gradient stabilized spacecraft, controlled by momentum exchange devices. These equations are then used for attitude control system design of an early Space Station Freedom flight configuration, demonstrating the errors caused by the improper approximation of the spacecraft dynamics. A full state feedback controller, incorporating gain-scheduled adaptation of the attitude gains, is developed for use during spacecraft on-orbit assembly or operations characterized by significant mass properties variations. The feasibility of the gain adaptation is demonstrated via a Space Station Freedom assembly sequence case study. The attitude controller stability robustness and transient performance during gain adaptation appear satisfactory.

  16. Robust reinforcement learning.

    PubMed

    Morimoto, Jun; Doya, Kenji

    2005-02-01

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

  17. 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.

  18. 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.

  19. On the Robustness Properties of M-MRAC

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram

    2012-01-01

    The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.

  20. 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.

  1. Measure of robustness for complex networks

    NASA Astrophysics Data System (ADS)

    Youssef, Mina Nabil

    to the spread of susceptible/infected/recovered (SIR) epidemics. To compute VCSIR, we propose a novel individual-based approach to model the spread of SIR epidemics in networks, which captures the infection size for a given effective infection rate. Thus, VCSIR quantitatively integrates the infection strength with the corresponding infection size. To optimize the VCSIR metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation

  2. Lost-motion valve actuator

    SciTech Connect

    Burris, W.J. III; Ringgenberg, P.D.

    1987-04-07

    A lost-motion valve actuator is described for a bore closure valve employed in a well bore, comprising: operating connector means adapted to move the bore closure valve between open and closed positions through longitudinal movement of the operating connector means. The operating connector means comprises an operating connector and a connector insert defining a recess therebetween; locking dog means comprising at least one locking dog received in the recess and spring biasing means adapted to urge at least one locking dog radially inwardly; and mandrel means slidably received within the operating connector means and including dog slot means associated therewith. The dog slot means comprises an annular slot on the exterior of the mandrel means adapted to lockingly receive at least one inwardly biased locking dog when proximate thereto, whereby longitudinal movement of the mandrel means is transmitted to the operating connector means.

  3. 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

  4. Robust Systems Test Framework

    2003-01-01

    The Robust Systems Test Framework (RSTF) provides a means of specifying and running test programs on various computation platforms. RSTF provides a level of specification above standard scripting languages. During a set of runs, standard timing information is collected. The RSTF specification can also gather job-specific information, and can include ways to classify test outcomes. All results and scripts can be stored into and retrieved from an SQL database for later data analysis. RSTF alsomore » provides operations for managing the script and result files, and for compiling applications and gathering compilation information such as optimization flags.« less

  5. Robust quantum spatial search

    NASA Astrophysics Data System (ADS)

    Tulsi, Avatar

    2016-07-01

    Quantum spatial search has been widely studied with most of the study focusing on quantum walk algorithms. We show that quantum walk algorithms are extremely sensitive to systematic errors. We present a recursive algorithm which offers significant robustness to certain systematic errors. To search N items, our recursive algorithm can tolerate errors of size O(1{/}√{ln N}) which is exponentially better than quantum walk algorithms for which tolerable error size is only O(ln N{/}√{N}). Also, our algorithm does not need any ancilla qubit. Thus our algorithm is much easier to implement experimentally compared to quantum walk algorithms.

  6. Robust Kriged Kalman Filtering

    SciTech Connect

    Baingana, Brian; Dall'Anese, Emiliano; Mateos, Gonzalo; Giannakis, Georgios B.

    2015-11-11

    Although the kriged Kalman filter (KKF) has well-documented merits for prediction of spatial-temporal processes, its performance degrades in the presence of outliers due to anomalous events, or measurement equipment failures. This paper proposes a robust KKF model that explicitly accounts for presence of measurement outliers. Exploiting outlier sparsity, a novel l1-regularized estimator that jointly predicts the spatial-temporal process at unmonitored locations, while identifying measurement outliers is put forth. Numerical tests are conducted on a synthetic Internet protocol (IP) network, and real transformer load data. Test results corroborate the effectiveness of the novel estimator in joint spatial prediction and outlier identification.

  7. Robust Systems Test Framework

    SciTech Connect

    Ballance, Robert A.

    2003-01-01

    The Robust Systems Test Framework (RSTF) provides a means of specifying and running test programs on various computation platforms. RSTF provides a level of specification above standard scripting languages. During a set of runs, standard timing information is collected. The RSTF specification can also gather job-specific information, and can include ways to classify test outcomes. All results and scripts can be stored into and retrieved from an SQL database for later data analysis. RSTF also provides operations for managing the script and result files, and for compiling applications and gathering compilation information such as optimization flags.

  8. Robust telescope scheduling

    NASA Technical Reports Server (NTRS)

    Swanson, Keith; Bresina, John; Drummond, Mark

    1994-01-01

    This paper presents a technique for building robust telescope schedules that tend not to break. The technique is called Just-In-Case (JIC) scheduling and it implements the common sense idea of being prepared for likely errors, just in case they should occur. The JIC algorithm analyzes a given schedule, determines where it is likely to break, reinvokes a scheduler to generate a contingent schedule for each highly probable break case, and produces a 'multiply contingent' schedule. The technique was developed for an automatic telescope scheduling problem, and the paper presents empirical results showing that Just-In-Case scheduling performs extremely well for this problem.

  9. Robust Photon Locking

    SciTech Connect

    Bayer, T.; Wollenhaupt, M.; Sarpe-Tudoran, C.; Baumert, T.

    2009-01-16

    We experimentally demonstrate a strong-field coherent control mechanism that combines the advantages of photon locking (PL) and rapid adiabatic passage (RAP). Unlike earlier implementations of PL and RAP by pulse sequences or chirped pulses, we use shaped pulses generated by phase modulation of the spectrum of a femtosecond laser pulse with a generalized phase discontinuity. The novel control scenario is characterized by a high degree of robustness achieved via adiabatic preparation of a state of maximum coherence. Subsequent phase control allows for efficient switching among different target states. We investigate both properties by photoelectron spectroscopy on potassium atoms interacting with the intense shaped light field.

  10. Robust control for uncertain structures

    NASA Technical Reports Server (NTRS)

    Douglas, Joel; Athans, Michael

    1991-01-01

    Viewgraphs on robust control for uncertain structures are presented. Topics covered include: robust linear quadratic regulator (RLQR) formulas; mismatched LQR design; RLQR design; interpretations of RLQR design; disturbance rejection; and performance comparisons: RLQR vs. mismatched LQR.

  11. Motion analysis and removal in intensity variation based OCT angiography.

    PubMed

    Liu, Xuan; Kirby, Mitchell; Zhao, Feng

    2014-11-01

    In this work, we investigated how bulk motion degraded the quality of optical coherence tomography (OCT) angiography that was obtained through calculating interframe signal variation, i.e., interframe signal variation based optical coherence angiography (isvOCA). We demonstrated theoretically and experimentally that the spatial average of isvOCA signal had an explicit functional dependency on bulk motion. Our result suggested that the bulk motion could lead to an increased background in angiography image. Based on our motion analysis, we proposed to reduce image artifact induced by transient bulk motion in isvOCA through adaptive thresholding. The motion artifact reduced angiography was demonstrated in a 1.3μm spectral domain OCT system. We implemented signal processing using graphic processing unit for real-time imaging and conducted in vivo microvasculature imaging on human skin. Our results clearly showed that the adaptive thresholding method was highly effective in the motion artifact removal for OCT angiography.

  12. Autonomous robotic capture of non-cooperative target by adaptive extended Kalman filter based visual servo

    NASA Astrophysics Data System (ADS)

    Dong, Gangqi; Zhu, Zheng H.

    2016-05-01

    This paper presents a real-time, vision-based algorithm for the pose and motion estimation of non-cooperative targets and its application in visual servo robotic manipulator to perform autonomous capture. A hybrid approach of adaptive extended Kalman filter and photogrammetry is developed for the real-time pose and motion estimation of non-cooperative targets. Based on the pose and motion estimates, the desired pose and trajectory of end-effector is defined and the corresponding desired joint angles of the robotic manipulator are derived by inverse kinematics. A close-loop visual servo control scheme is then developed for the robotic manipulator to track, approach and capture the target. Validating experiments are designed and performed on a custom-built six degrees of freedom robotic manipulator with an eye-in-hand configuration. The experimental results demonstrate the feasibility, effectiveness and robustness of the proposed adaptive extended Kalman filter enabled pose and motion estimation and visual servo strategy.

  13. SimPACE: generating simulated motion corrupted BOLD data with synthetic-navigated acquisition for the development and evaluation of SLOMOCO: a new, highly effective slicewise motion correction.

    PubMed

    Beall, Erik B; Lowe, Mark J

    2014-11-01

    Head motion in functional MRI and resting-state MRI is a major problem. Existing methods do not robustly reflect the true level of motion artifact for in vivo fMRI data. The primary issue is that current methods assume that motion is synchronized to the volume acquisition and thus ignore intra-volume motion. This manuscript covers three sections in the use of gold-standard motion-corrupted data to pursue an intra-volume motion correction. First, we present a way to get motion corrupted data with accurately known motion at the slice acquisition level. This technique simulates important data acquisition-related motion artifacts while acquiring real BOLD MRI data. It is based on a novel motion-injection pulse sequence that introduces known motion independently for every slice: Simulated Prospective Acquisition CorrEction (SimPACE). Secondly, with data acquired using SimPACE, we evaluate several motion correction and characterization techniques, including several commonly used BOLD signal- and motion parameter-based metrics. Finally, we introduce and evaluate a novel, slice-based motion correction technique. Our novel method, SLice-Oriented MOtion COrrection (SLOMOCO) performs better than the volumetric methods and, moreover, accurately detects the motion of independent slices, in this case equivalent to the known injected motion. We demonstrate that SLOMOCO can model and correct for nearly all effects of motion in BOLD data. Also, none of the commonly used motion metrics was observed to robustly identify motion corrupted events, especially in the most realistic scenario of sudden head movement. For some popular metrics, performance was poor even when using the ideal known slice motion instead of volumetric parameters. This has negative implications for methods relying on these metrics, such as recently proposed motion correction methods such as data censoring and global signal regression.

  14. Robust control algorithms for Mars aerobraking

    NASA Technical Reports Server (NTRS)

    Shipley, Buford W., Jr.; Ward, Donald T.

    1992-01-01

    Four atmospheric guidance concepts have been adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. The first two offer improvements to the Analytic Predictor Corrector (APC) to increase its robustness to density variations. The second two are variations of a new Liapunov tracking exit phase algorithm, developed to guide the vehicle along a reference trajectory. These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. MARSGRAM is used to develop realistic atmospheres for the study. When square wave density pulses perturb the atmosphere all four controllers are successful. The algorithms are tested against atmospheres where the inbound and outbound density functions are different. Square wave density pulses are again used, but only for the outbound leg of the trajectory. Additionally, sine waves are used to perturb the density function. The new algorithms are found to be more robust than any previously tested and a Liapunov controller is selected as the most robust control algorithm overall examined.

  15. Neurohumoral mechanism of space motion sickness

    NASA Astrophysics Data System (ADS)

    Grigoriev, A. I.; Egorov, A. D.; Nichiporuk, I. A.

    This paper reviews existing hypotheses concerning the mechanisms of adaptation of the vestibular apparatus and related somatosensory systems to microgravity with reference to the flight data. Having in view theoretical concepts and experimental data accumulated in space flights, a conceptual model of the development of a functional system responsible for the termination of vestibular dysfunction and space motion sickness manifestations is presented. It is also shown that changes in the hormonal status during motion sickness induced by vestibular stimulation give evidence that endocrine regulation of certain functions can be involved in adaptive responses.

  16. Robust omniphobic surfaces

    PubMed Central

    Tuteja, Anish; Choi, Wonjae; Mabry, Joseph M.; McKinley, Gareth H.; Cohen, Robert E.

    2008-01-01

    Superhydrophobic surfaces display water contact angles greater than 150° in conjunction with low contact angle hysteresis. Microscopic pockets of air trapped beneath the water droplets placed on these surfaces lead to a composite solid-liquid-air interface in thermodynamic equilibrium. Previous experimental and theoretical studies suggest that it may not be possible to form similar fully-equilibrated, composite interfaces with drops of liquids, such as alkanes or alcohols, that possess significantly lower surface tension than water (γlv = 72.1 mN/m). In this work we develop surfaces possessing re-entrant texture that can support strongly metastable composite solid-liquid-air interfaces, even with very low surface tension liquids such as pentane (γlv = 15.7 mN/m). Furthermore, we propose four design parameters that predict the measured contact angles for a liquid droplet on a textured surface, as well as the robustness of the composite interface, based on the properties of the solid surface and the contacting liquid. These design parameters allow us to produce two different families of re-entrant surfaces— randomly-deposited electrospun fiber mats and precisely fabricated microhoodoo surfaces—that can each support a robust composite interface with essentially any liquid. These omniphobic surfaces display contact angles greater than 150° and low contact angle hysteresis with both polar and nonpolar liquids possessing a wide range of surface tensions. PMID:19001270

  17. Blink detection robust to various facial poses.

    PubMed

    Lee, Won Oh; Lee, Eui Chul; Park, Kang Ryoung

    2010-11-30

    Applications based on eye-blink detection have increased, as a result of which it is essential for eye-blink detection to be robust and non-intrusive irrespective of the changes in the user's facial pose. However, most previous studies on camera-based blink detection have the disadvantage that their performances were affected by the facial pose. They also focused on blink detection using only frontal facial images. To overcome these disadvantages, we developed a new method for blink detection, which maintains its accuracy despite changes in the facial pose of the subject. This research is novel in the following four ways. First, the face and eye regions are detected by using both the AdaBoost face detector and a Lucas-Kanade-Tomasi (LKT)-based method, in order to achieve robustness to facial pose. Secondly, the determination of the state of the eye (being open or closed), needed for blink detection, is based on two features: the ratio of height to width of the eye region in a still image, and the cumulative difference of the number of black pixels of the eye region using an adaptive threshold in successive images. These two features are robustly extracted irrespective of the lighting variations by using illumination normalization. Thirdly, the accuracy of determining the eye state - open or closed - is increased by combining the above two features on the basis of the support vector machine (SVM). Finally, the SVM classifier for determining the eye state is adaptively selected according to the facial rotation. Experimental results using various databases showed that the blink detection by the proposed method is robust to various facial poses. PMID:20826183

  18. Perceived causality influences brain activity evoked by biological motion.

    PubMed

    Morris, James P; Pelphrey, Kevin A; McCarthy, Gregory

    2008-01-01

    Using functional magnetic resonance imaging (fMRI), we investigated brain activity in an observer who watched the hand and arm motions of an individual when that individual was, or was not, the cause of the motion. Subjects viewed a realistic animated 3D character who sat at a table containing four pistons. On Intended Motion trials, the character raised his hand and arm upwards. On Unintended Motion trials, the piston under one of the character's hands pushed the hand and arm upward with the same motion. Finally, during Non-Biological Motion control trials, a piston pushed a coffee mug upward in the same smooth motion. Hand and arm motions, regardless of intention, evoked significantly more activity than control trials in a bilateral region that extended ventrally from the posterior superior temporal sulcus (pSTS) region and which was more spatially extensive in the right hemisphere. The left pSTS near the temporal-parietal junction, robustly differentiated between the Intended Motion and Unintended Motion conditions. Here, strong activity was observed for Intended Motion trials, while Unintended Motion trials evoked similar activity as the coffee mug trials. Our results demonstrate a strong hemispheric bias in the role of the pSTS in the perception of causality of biological motion. PMID:18633843

  19. Transformational adaptation when incremental adaptations to climate change are insufficient

    PubMed Central

    Kates, Robert W.; Travis, William R.; Wilbanks, Thomas J.

    2012-01-01

    All human–environment systems adapt to climate and its natural variation. Adaptation to human-induced change in climate has largely been envisioned as increments of these adaptations intended to avoid disruptions of systems at their current locations. In some places, for some systems, however, vulnerabilities and risks may be so sizeable that they require transformational rather than incremental adaptations. Three classes of transformational adaptations are those that are adopted at a much larger scale, that are truly new to a particular region or resource system, and that transform places and shift locations. We illustrate these with examples drawn from Africa, Europe, and North America. Two conditions set the stage for transformational adaptation to climate change: large vulnerability in certain regions, populations, or resource systems; and severe climate change that overwhelms even robust human use systems. However, anticipatory transformational adaptation may be difficult to implement because of uncertainties about climate change risks and adaptation benefits, the high costs of transformational actions, and institutional and behavioral actions that tend to maintain existing resource systems and policies. Implementing transformational adaptation requires effort to initiate it and then to sustain the effort over time. In initiating transformational adaptation focusing events and multiple stresses are important, combined with local leadership. In sustaining transformational adaptation, it seems likely that supportive social contexts and the availability of acceptable options and resources for actions are key enabling factors. Early steps would include incorporating transformation adaptation into risk management and initiating research to expand the menu of innovative transformational adaptations. PMID:22509036

  20. Transformational adaptation when incremental adaptations to climate change are insufficient.

    PubMed

    Kates, Robert W; Travis, William R; Wilbanks, Thomas J

    2012-05-01

    All human-environment systems adapt to climate and its natural variation. Adaptation to human-induced change in climate has largely been envisioned as increments of these adaptations intended to avoid disruptions of systems at their current locations. In some places, for some systems, however, vulnerabilities and risks may be so sizeable that they require transformational rather than incremental adaptations. Three classes of transformational adaptations are those that are adopted at a much larger scale, that are truly new to a particular region or resource system, and that transform places and shift locations. We illustrate these with examples drawn from Africa, Europe, and North America. Two conditions set the stage for transformational adaptation to climate change: large vulnerability in certain regions, populations, or resource systems; and severe climate change that overwhelms even robust human use systems. However, anticipatory transformational adaptation may be difficult to implement because of uncertainties about climate change risks and adaptation benefits, the high costs of transformational actions, and institutional and behavioral actions that tend to maintain existing resource systems and policies. Implementing transformational adaptation requires effort to initiate it and then to sustain the effort over time. In initiating transformational adaptation focusing events and multiple stresses are important, combined with local leadership. In sustaining transformational adaptation, it seems likely that supportive social contexts and the availability of acceptable options and resources for actions are key enabling factors. Early steps would include incorporating transformation adaptation into risk management and initiating research to expand the menu of innovative transformational adaptations.