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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

A Five-Dimensional Mathematical Model for Regional and Global Changes in Cardiac Uptake and Motion

NASA Astrophysics Data System (ADS)

Pretorius, P. H.; King, M. A.; Gifford, H. C.

2004-10-01

The objective of this work was to simultaneously introduce known regional changes in contraction pattern and perfusion to the existing gated Mathematical Cardiac Torso (MCAT) phantom heart model. We derived a simple integral to calculate the fraction of the ellipsoidal volume that makes up the left ventricle (LV), taking into account the stationary apex and the moving base. After calculating the LV myocardium volume of the existing beating heart model, we employed the property of conservation of mass to manipulate the LV ejection fraction to values ranging between 13.5% and 68.9%. Multiple dynamic heart models that differ in degree of LV wall thickening, base-to-apex motion, and ejection fraction, are thus available for use with the existing MCAT methodology. To introduce more complex regional LV contraction and perfusion patterns, we used composites of dynamic heart models to create a central region with little or no motion or perfusion, surrounded by a region in which the motion and perfusion gradually reverts to normal. To illustrate this methodology, the following gated cardiac acquisitions for different clinical situations were simulated analytically: 1) reduced regional motion and perfusion; 2) same perfusion as in (1) without motion intervention; and 3) washout from the normal and diseased myocardial regions. Both motion and perfusion can change dynamically during a single rotation or multiple rotations of a simulated single-photon emission computed tomography acquisition system.

Motion transparency: making models of motion perception transparent.

PubMed

Snowden; Verstraten

1999-10-01

In daily life our visual system is bombarded with motion information. We see cars driving by, flocks of birds flying in the sky, clouds passing behind trees that are dancing in the wind. Vision science has a good understanding of the first stage of visual motion processing, that is, the mechanism underlying the detection of local motions. Currently, research is focused on the processes that occur beyond the first stage. At this level, local motions have to be integrated to form objects, define the boundaries between them, construct surfaces and so on. An interesting, if complicated case is known as motion transparency: the situation in which two overlapping surfaces move transparently over each other. In that case two motions have to be assigned to the same retinal location. Several researchers have tried to solve this problem from a computational point of view, using physiological and psychophysical results as a guideline. We will discuss two models: one uses the traditional idea known as 'filter selection' and the other a relatively new approach based on Bayesian inference. Predictions from these models are compared with our own visual behaviour and that of the neural substrates that are presumed to underlie these perceptions.

Global Motions of the Nuclear Pore Complex: Insights from Elastic Network Models

PubMed Central

Lezon, Timothy R.; Sali, Andrej; Bahar, Ivet

2009-01-01

The nuclear pore complex (NPC) is the gate to the nucleus. Recent determination of the configuration of proteins in the yeast NPC at ∼5 nm resolution permits us to study the NPC global dynamics using coarse-grained structural models. We investigate these large-scale motions by using an extended elastic network model (ENM) formalism applied to several coarse-grained representations of the NPC. Two types of collective motions (global modes) are predicted by the ENMs to be intrinsically favored by the NPC architecture: global bending and extension/contraction from circular to elliptical shapes. These motions are shown to be robust against tested variations in the representation of the NPC, and are largely captured by a simple model of a toroid with axially varying mass density. We demonstrate that spoke multiplicity significantly affects the accessible number of symmetric low-energy modes of motion; the NPC-like toroidal structures composed of 8 spokes have access to highly cooperative symmetric motions that are inaccessible to toroids composed of 7 or 9 spokes. The analysis reveals modes of motion that may facilitate macromolecular transport through the NPC, consistent with previous experimental observations. PMID:19730674

Global motions of the nuclear pore complex: insights from elastic network models.

PubMed

Lezon, Timothy R; Sali, Andrej; Bahar, Ivet

2009-09-01

The nuclear pore complex (NPC) is the gate to the nucleus. Recent determination of the configuration of proteins in the yeast NPC at approximately 5 nm resolution permits us to study the NPC global dynamics using coarse-grained structural models. We investigate these large-scale motions by using an extended elastic network model (ENM) formalism applied to several coarse-grained representations of the NPC. Two types of collective motions (global modes) are predicted by the ENMs to be intrinsically favored by the NPC architecture: global bending and extension/contraction from circular to elliptical shapes. These motions are shown to be robust against tested variations in the representation of the NPC, and are largely captured by a simple model of a toroid with axially varying mass density. We demonstrate that spoke multiplicity significantly affects the accessible number of symmetric low-energy modes of motion; the NPC-like toroidal structures composed of 8 spokes have access to highly cooperative symmetric motions that are inaccessible to toroids composed of 7 or 9 spokes. The analysis reveals modes of motion that may facilitate macromolecular transport through the NPC, consistent with previous experimental observations.

Model for the computation of self-motion in biological systems

NASA Technical Reports Server (NTRS)

Perrone, John A.

1992-01-01

A technique is presented by which direction- and speed-tuned cells, such as those commonly found in the middle temporal region of the primate brain, can be utilized to analyze the patterns of retinal image motion that are generated during observer movement through the environment. The developed model determines heading by finding the peak response in a population of detectors or neurons each tuned to a particular heading direction. It is suggested that a complex interaction of multiple cell networks is required for the solution of the self-motion problem in the primate brain.

Modeling depth from motion parallax with the motion/pursuit ratio

PubMed Central

Nawrot, Mark; Ratzlaff, Michael; Leonard, Zachary; Stroyan, Keith

2014-01-01

The perception of unambiguous scaled depth from motion parallax relies on both retinal image motion and an extra-retinal pursuit eye movement signal. The motion/pursuit ratio represents a dynamic geometric model linking these two proximal cues to the ratio of depth to viewing distance. An important step in understanding the visual mechanisms serving the perception of depth from motion parallax is to determine the relationship between these stimulus parameters and empirically determined perceived depth magnitude. Observers compared perceived depth magnitude of dynamic motion parallax stimuli to static binocular disparity comparison stimuli at three different viewing distances, in both head-moving and head-stationary conditions. A stereo-viewing system provided ocular separation for stereo stimuli and monocular viewing of parallax stimuli. For each motion parallax stimulus, a point of subjective equality (PSE) was estimated for the amount of binocular disparity that generates the equivalent magnitude of perceived depth from motion parallax. Similar to previous results, perceived depth from motion parallax had significant foreshortening. Head-moving conditions produced even greater foreshortening due to the differences in the compensatory eye movement signal. An empirical version of the motion/pursuit law, termed the empirical motion/pursuit ratio, which models perceived depth magnitude from these stimulus parameters, is proposed. PMID:25339926

Animal models in motion sickness research

NASA Technical Reports Server (NTRS)

Daunton, Nancy G.

1990-01-01

Practical information on candidate animal models for motion sickness research and on methods used to elicit and detect motion sickness in these models is provided. Four good potential models for use in motion sickness experiments include the dog, cat, squirrel monkey, and rat. It is concluded that the appropriate use of the animal models, combined with exploitation of state-of-the-art biomedical techniques, should generate a great step forward in the understanding of motion sickness mechanisms and in the development of efficient and effective approaches to its prevention and treatment in humans.

Reliability of psychophysiological responses across multiple motion sickness stimulation tests

NASA Technical Reports Server (NTRS)

Stout, C. S.; Toscano, W. B.; Cowings, P. S.

1995-01-01

Although there is general agreement that a high degree of variability exists between subjects in their autonomic nervous system responses to motion sickness stimulation, very little evidence exists that examines the reproducibility of autonomic responses within subjects during motion sickness stimulation. Our objectives were to examine the reliability of autonomic responses and symptom levels across five testing occasions using the (1) final minute of testing, (2) change in autonomic response and the change in symptom level, and (3) strength of the relationship between the change in symptom level and the change in autonomic responses across the entire motion sickness test. The results indicate that, based on the final minute of testing, the autonomic responses of heart rate, blood volume pulse, and respiration rate are moderately stable across multiple tests. Changes in heart rate, blood volume pulse, respiration rate, and symptoms throughout the test duration are less stable across the tests. Finally, autonomic responses and symptom levels are significantly related across the entire motion sickness test.

Motion laws synthesis for cam mechanisms with multiple follower displacement

NASA Astrophysics Data System (ADS)

Podgornyj, Yu I.; Skeeba, V. Yu; Kirillov, A. V.; Martynova, T. G.; Skeeba, P. Yu

2018-03-01

The research discusses the cam mechanisms design. The analysis of specialized literature indicates that the synthesis of the cam mechanisms laws of motion is currently done mainly by a standard set of acceleration curves. In some cases, the designer needs to synthesize a new acceleration law which should be task-specific and enforce a certain production step. The values of the technological loads and inertia forces loads generated by the mechanism are calculated to analyze the slay mechanism behavior in the production of closely woven fabrics. Mathematical packages MathCad and SolidWorks are used in calculations. As a result of the research, the authors propose the methodology for synthesizing the slay mechanism with multiple follower displacements for the point of contact between the reed and the fabric edge. Theoretical studies have been tested on a specific machine model (STB loom). The authors have synthesized the motion law of the filling threads beat-up mechanism for the production of strong fabrics. New basic and closing cam profiles are proposed. The results are designed to enhance the possibilities of the looms and to recommend the most efficient equipment operation modes for the producers.

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.

On a PCA-based lung motion model

PubMed Central

Li, Ruijiang; Lewis, John H; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A; Jiang, Steve B

2014-01-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772–81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921–9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within

On a PCA-based lung motion model

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A.; Jiang, Steve B.

2011-09-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772-81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921-9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1

Multiple model cardinalized probability hypothesis density filter

NASA Astrophysics Data System (ADS)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Strong ground motion simulation of the 2016 Kumamoto earthquake of April 16 using multiple point sources

NASA Astrophysics Data System (ADS)

Nagasaka, Yosuke; Nozu, Atsushi

2017-02-01

The pseudo point-source model approximates the rupture process on faults with multiple point sources for simulating strong ground motions. A simulation with this point-source model is conducted by combining a simple source spectrum following the omega-square model with a path spectrum, an empirical site amplification factor, and phase characteristics. Realistic waveforms can be synthesized using the empirical site amplification factor and phase models even though the source model is simple. The Kumamoto earthquake occurred on April 16, 2016, with M JMA 7.3. Many strong motions were recorded at stations around the source region. Some records were considered to be affected by the rupture directivity effect. This earthquake was suitable for investigating the applicability of the pseudo point-source model, the current version of which does not consider the rupture directivity effect. Three subevents (point sources) were located on the fault plane, and the parameters of the simulation were determined. The simulated results were compared with the observed records at K-NET and KiK-net stations. It was found that the synthetic Fourier spectra and velocity waveforms generally explained the characteristics of the observed records, except for underestimation in the low frequency range. Troughs in the observed Fourier spectra were also well reproduced by placing multiple subevents near the hypocenter. The underestimation is presumably due to the following two reasons. The first is that the pseudo point-source model targets subevents that generate strong ground motions and does not consider the shallow large slip. The second reason is that the current version of the pseudo point-source model does not consider the rupture directivity effect. Consequently, strong pulses were not reproduced enough at stations northeast of Subevent 3 such as KMM004, where the effect of rupture directivity was significant, while the amplitude was well reproduced at most of the other stations. This

Inter-fraction variations in respiratory motion models

NASA Astrophysics Data System (ADS)

McClelland, J. R.; Hughes, S.; Modat, M.; Qureshi, A.; Ahmad, S.; Landau, D. B.; Ourselin, S.; Hawkes, D. J.

2011-01-01

Respiratory motion can vary dramatically between the planning stage and the different fractions of radiotherapy treatment. Motion predictions used when constructing the radiotherapy plan may be unsuitable for later fractions of treatment. This paper presents a methodology for constructing patient-specific respiratory motion models and uses these models to evaluate and analyse the inter-fraction variations in the respiratory motion. The internal respiratory motion is determined from the deformable registration of Cine CT data and related to a respiratory surrogate signal derived from 3D skin surface data. Three different models for relating the internal motion to the surrogate signal have been investigated in this work. Data were acquired from six lung cancer patients. Two full datasets were acquired for each patient, one before the course of radiotherapy treatment and one at the end (approximately 6 weeks later). Separate models were built for each dataset. All models could accurately predict the respiratory motion in the same dataset, but had large errors when predicting the motion in the other dataset. Analysis of the inter-fraction variations revealed that most variations were spatially varying base-line shifts, but changes to the anatomy and the motion trajectories were also observed.

Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: Structure-based molecular dynamics simulations

PubMed Central

Okazaki, Kei-ichi; Koga, Nobuyasu; Takada, Shoji; Onuchic, Jose N.; Wolynes, Peter G.

2006-01-01

Biomolecules often undergo large-amplitude motions when they bind or release other molecules. Unlike macroscopic machines, these biomolecular machines can partially disassemble (unfold) and then reassemble (fold) during such transitions. Here we put forward a minimal structure-based model, the “multiple-basin model,” that can directly be used for molecular dynamics simulation of even very large biomolecular systems so long as the endpoints of the conformational change are known. We investigate the model by simulating large-scale motions of four proteins: glutamine-binding protein, S100A6, dihydrofolate reductase, and HIV-1 protease. The mechanisms of conformational transition depend on the protein basin topologies and change with temperature near the folding transition. The conformational transition rate varies linearly with driving force over a fairly large range. This linearity appears to be a consequence of partial unfolding during the conformational transition. PMID:16877541

Relative motions of fragments of the split comets. III - A test of splitting and comets with suspected multiple nuclei

NASA Technical Reports Server (NTRS)

Sekanina, Z.

1979-01-01

A quantitative test of splitting for comets with suspected multiple nuclei has been formulated using a model which assumes the motions of cometary fragments to be due primarily to outgassing. The model expresses the relative motion of the cometary fragments in terms of the time of splitting and the differential force, which are determined by measurements of the position angle and the separation distance between fragments. The test is applied to 18 comets suspected of having multiple nuclei, of which the comets Sawerthal 1888 I, Campbell 1914 IV, Whipple-Fedtke-Tevzadze 1943 I, Honda 1955 V, Wild 1968 III and Tago-Sato-Kosaka 1969 IX were found to be clear cases of split comets and Davidson 1889 IV and Periodic Giacobini 1896 V were judged to be likely candidates. At least three of the secondary nuclei confirmed can be classified as short-lived companions, while only two appear to be persistent.

Modeling absolute plate and plume motions

NASA Astrophysics Data System (ADS)

Bodinier, G. P.; Wessel, P.; Conrad, C. P.

2016-12-01

Paleomagnetic evidence for plume drift has made modeling of absolute plate motions challenging, especially since direct observations of plume drift are lacking. Predictions of plume drift arising from mantle convection models and broadly satisfying observed paleolatitudes have so far provided the only framework for deriving absolute plate motions over moving hotspots. However, uncertainties in mantle rheology, temperature, and initial conditions make such models nonunique. Using simulated and real data, we will show that age progressions along Pacific hotspot trails provide strong constraints on plume motions for all major trails, and furthermore that it is possible to derive models for relative plume drift from these data alone. Relative plume drift depends on the inter-hotspot distances derived from age progressions but lacks a fixed reference point and orientation. By incorporating paleolatitude histories for the Hawaii and Louisville chains we add further constraints on allowable plume motions, yet one unknown parameter remains: a longitude shift that applies equally to all plumes. To obtain a solution we could restrict either the Hawaii or Louisville plume to have latitudinal motion only, thus satisfying paleolatitude constraints. Yet, restricting one plume to latitudinal motion while all others move freely is not realistic. Consequently, it is only possible to resolve the motion of hotspots relative to an overall and unknown longitudinal shift as a function of time. Our plate motions are therefore dependent on the same shift via an unknown rotation about the north pole. Yet, as plume drifts are consequences of mantle convection, our results place strong constraints on the pattern of convection. Other considerations, such as imposed limits on plate speed, plume speed, proximity to LLSVP edges, model smoothness, or relative plate motions via ridge-spotting may add further constraints that allow a unique model of Pacific absolute plate and plume motions to be

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

NASA Technical Reports Server (NTRS)

Smith, Phillip N.; Sridhar, Banavar; Suorsa, Raymond E.

1993-01-01

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Hamiltonian modelling of relative motion.

PubMed

Kasdin, N Jeremy; Gurfil, Pini

2004-05-01

This paper presents a Hamiltonian approach to modelling relative spacecraft motion based on derivation of canonical coordinates for the relative state-space dynamics. The Hamiltonian formulation facilitates the modelling of high-order terms and orbital perturbations while allowing us to obtain closed-form solutions to the relative motion problem. First, the Hamiltonian is partitioned into a linear term and a high-order term. The Hamilton-Jacobi equations are solved for the linear part by separation, and new constants for the relative motions are obtained, they are called epicyclic elements. The influence of higher order terms and perturbations, such as the oblateness of the Earth, are incorporated into the analysis by a variation of parameters procedure. Closed-form solutions for J(2-) and J(4-)invariant orbits and for periodic high-order unperturbed relative motion, in terms of the relative motion elements only, are obtained.

Hybrid Motion Planning with Multiple Destinations

NASA Technical Reports Server (NTRS)

Clouse, Jeffery

1998-01-01

In our initial proposal, we laid plans for developing a hybrid motion planning system that combines the concepts of visibility-based motion planning, artificial potential field based motion planning, evolutionary constrained optimization, and reinforcement learning. Our goal was, and still is, to produce a hybrid motion planning system that outperforms the best traditional motion planning systems on problems with dynamic environments. The proposed hybrid system will be in two parts the first is a global motion planning system and the second is a local motion planning system. The global system will take global information about the environment, such as the placement of the obstacles and goals, and produce feasible paths through those obstacles. We envision a system that combines the evolutionary-based optimization and visibility-based motion planning to achieve this end.

A Bio-Inspired, Motion-Based Analysis of Crowd Behavior Attributes Relevance to Motion Transparency, Velocity Gradients, and Motion Patterns

PubMed Central

Raudies, Florian; Neumann, Heiko

2012-01-01

The analysis of motion crowds is concerned with the detection of potential hazards for individuals of the crowd. Existing methods analyze the statistics of pixel motion to classify non-dangerous or dangerous behavior, to detect outlier motions, or to estimate the mean throughput of people for an image region. We suggest a biologically inspired model for the analysis of motion crowds that extracts motion features indicative for potential dangers in crowd behavior. Our model consists of stages for motion detection, integration, and pattern detection that model functions of the primate primary visual cortex area (V1), the middle temporal area (MT), and the medial superior temporal area (MST), respectively. This model allows for the processing of motion transparency, the appearance of multiple motions in the same visual region, in addition to processing opaque motion. We suggest that motion transparency helps to identify “danger zones” in motion crowds. For instance, motion transparency occurs in small exit passages during evacuation. However, motion transparency occurs also for non-dangerous crowd behavior when people move in opposite directions organized into separate lanes. Our analysis suggests: The combination of motion transparency and a slow motion speed can be used for labeling of candidate regions that contain dangerous behavior. In addition, locally detected decelerations or negative speed gradients of motions are a precursor of danger in crowd behavior as are globally detected motion patterns that show a contraction toward a single point. In sum, motion transparency, image speeds, motion patterns, and speed gradients extracted from visual motion in videos are important features to describe the behavioral state of a motion crowd. PMID:23300930

The Effects of Towfish Motion on Sidescan Sonar Images: Extension to a Multiple-Beam Device

DTIC Science & Technology

1994-02-01

simulation, the raw simulated sidescan image is formed from pixels G , which are the sum of energies E,", assigned to the nearest range- bin k as noted in...for stable motion at constant velocity V0, are applied to (divided into) the G ,, and the simulated sidescan image is ready to display. Maximal energy...limitation is likely to apply to all multiple-beam sonais of similar construction. The yaw correction was incorporated in the MBEAM model by an

Models of subjective response to in-flight motion data

NASA Technical Reports Server (NTRS)

Rudrapatna, A. N.; Jacobson, I. D.

1973-01-01

Mathematical relationships between subjective comfort and environmental variables in an air transportation system are investigated. As a first step in model building, only the motion variables are incorporated and sensitivities are obtained using stepwise multiple regression analysis. The data for these models have been collected from commercial passenger flights. Two models are considered. In the first, subjective comfort is assumed to depend on rms values of the six-degrees-of-freedom accelerations. The second assumes a Rustenburg type human response function in obtaining frequency weighted rms accelerations, which are used in a linear model. The form of the human response function is examined and the results yield a human response weighting function for different degrees of freedom.

Ground Motion Modeling in the Eastern Caucasus

DOE PAGES

Pitarka, Arben; Gok, Rengin; Yetirmishli, Gurban; ...

2016-05-13

In this paper, we analyzed the performance of a preliminary three-dimensional (3D) velocity model of the Eastern Caucasus covering most of the Azerbaijan. The model was developed in support to long-period ground motion simulations and seismic hazard assessment from regional earthquakes in Azerbaijan. The model’s performance was investigated by simulating ground motion from the damaging Mw 5.9, 2012 Zaqatala earthquake, which was well recorded throughout the region by broadband seismic instruments. In our simulations, we use a parallelized finite-difference method of fourth-order accuracy. The comparison between the simulated and recorded ground motion velocity in the modeled period range of 3–20more » s shows that in general, the 3D velocity model performs well. Areas in which the model needs improvements are located mainly in the central part of the Kura basin and in the Caspian Sea coastal areas. Comparisons of simulated ground motion using our 3D velocity model and corresponding 1D regional velocity model were used to locate areas with strong 3D wave propagation effects. In areas with complex underground structure, the 1D model fails to produce the observed ground motion amplitude and duration, and spatial extend of ground motion amplification caused by wave propagation effects.« less

Modeling respiratory motion for reducing motion artifacts in 4D CT images.

PubMed

Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei

2013-04-01

Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a

An MR-based Model for Cardio-Respiratory Motion Compensation of Overlays in X-Ray Fluoroscopy

PubMed Central

Fischer, Peter; Faranesh, Anthony; Pohl, Thomas; Maier, Andreas; Rogers, Toby; Ratnayaka, Kanishka; Lederman, Robert; Hornegger, Joachim

2017-01-01

In X-ray fluoroscopy, static overlays are used to visualize soft tissue. We propose a system for cardiac and respiratory motion compensation of these overlays. It consists of a 3-D motion model created from real-time MR imaging. Multiple sagittal slices are acquired and retrospectively stacked to consistent 3-D volumes. Slice stacking considers cardiac information derived from the ECG and respiratory information extracted from the images. Additionally, temporal smoothness of the stacking is enhanced. Motion is estimated from the MR volumes using deformable 3-D/3-D registration. The motion model itself is a linear direct correspondence model using the same surrogate signals as slice stacking. In X-ray fluoroscopy, only the surrogate signals need to be extracted to apply the motion model and animate the overlay in real time. For evaluation, points are manually annotated in oblique MR slices and in contrast-enhanced X-ray images. The 2-D Euclidean distance of these points is reduced from 3.85 mm to 2.75 mm in MR and from 3.0 mm to 1.8 mm in X-ray compared to the static baseline. Furthermore, the motion-compensated overlays are shown qualitatively as images and videos. PMID:28692969

Statistical prediction of space motion sickness

NASA Technical Reports Server (NTRS)

Reschke, Millard F.

1990-01-01

Studies designed to empirically examine the etiology of motion sickness to develop a foundation for enhancing its prediction are discussed. Topics addressed include early attempts to predict space motion sickness, multiple test data base that uses provocative and vestibular function tests, and data base subjects; reliability of provocative tests of motion sickness susceptibility; prediction of space motion sickness using linear discriminate analysis; and prediction of space motion sickness susceptibility using the logistic model.

Simulating intrafraction prostate motion with a random walk model.

PubMed

Pommer, Tobias; Oh, Jung Hun; Munck Af Rosenschöld, Per; Deasy, Joseph O

2017-01-01

Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively. A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm 2 /min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion. Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during

How Many Objects are You Worth? Quantification of the Self-Motion Load on Multiple Object Tracking

PubMed Central

Thomas, Laura E.; Seiffert, Adriane E.

2011-01-01

Perhaps walking and chewing gum is effortless, but walking and tracking moving objects is not. Multiple object tracking is impaired by walking from one location to another, suggesting that updating location of the self puts demands on object tracking processes. Here, we quantified the cost of self-motion in terms of the tracking load. Participants in a virtual environment tracked a variable number of targets (1–5) among distractors while either staying in one place or moving along a path that was similar to the objects’ motion. At the end of each trial, participants decided whether a probed dot was a target or distractor. As in our previous work, self-motion significantly impaired performance in tracking multiple targets. Quantifying tracking capacity for each individual under move versus stay conditions further revealed that self-motion during tracking produced a cost to capacity of about 0.8 (±0.2) objects. Tracking your own motion is worth about one object, suggesting that updating the location of the self is similar, but perhaps slightly easier, than updating locations of objects. PMID:21991259

Photo-consistency registration of a 4D cardiac motion model to endoscopic video for image guidance of robotic coronary artery bypass

NASA Astrophysics Data System (ADS)

Figl, Michael; Rueckert, Daniel; Edwards, Eddie

2009-02-01

The aim of the work described in this paper is registration of a 4D preoperative motion model of the heart to the video view of the patient through the intraoperative endoscope. The heart motion is cyclical and can be modelled using multiple reconstructions of cardiac gated coronary CT. We propose the use of photoconsistency between the two views through the da Vinci endoscope to align to the preoperative heart surface model from CT. The temporal alignment from the video to the CT model could in principle be obtained from the ECG signal. We propose averaging of the photoconsistency over the cardiac cycle to improve the registration compared to a single view. Though there is considerable motion of the heart, after correct temporal alignment we suggest that the remaining motion should be close to rigid. Results are presented for simulated renderings and for real video of a beating heart phantom. We found much smoother sections at the minimum when using multiple phases for the registration, furthermore convergence was found to be better when more phases are used.

Modeling Local Interactions during the Motion of Cyanobacteria

PubMed Central

Galante, Amanda; Wisen, Susanne; Bhaya, Devaki; Levy, Doron

2012-01-01

Synechocystis sp., a common unicellular freshwater cyanobacterium, has been used as a model organism to study phototaxis, an ability to move in the direction of a light source. This microorganism displays a number of additional characteristics such as delayed motion, surface dependence, and a quasi-random motion, where cells move in a seemingly disordered fashion instead of in the direction of the light source, a global force on the system. These unexplained motions are thought to be modulated by local interactions between cells such as intercellular communication. In this paper, we consider only local interactions of these phototactic cells in order to mathematically model this quasi-random motion. We analyze an experimental data set to illustrate the presence of quasi-random motion and then derive a stochastic dynamic particle system modeling interacting phototactic cells. The simulations of our model are consistent with experimentally observed phototactic motion. PMID:22713858

Representation of Reserves Through a Brownian Motion Model

NASA Astrophysics Data System (ADS)

Andrade, M.; Ferreira, M. A. M.; Filipe, J. A.

2012-11-01

The Brownian Motion is commonly used as an approximation for some Random Walks and also for the Classic Risk Process. As the Random Walks and the Classic Risk Process are used frequently as stochastic models to represent reserves, it is natural to consider the Brownian Motion with the same purpose. In this study a model, based on the Brownian Motion, is presented to represent reserves. The Brownian Motion is used in this study to estimate the ruin probability of a fund. This kind of models is considered often in the study of pensions funds.

Reliability of Autonomic Responses and Malaise Across Multiple Motion Sickness Stimulation Tests

NASA Technical Reports Server (NTRS)

Stout, Cynthia S.; Toscano, William B.; Cowings, Patricia S.

1993-01-01

There is general agreement that a high degree of variability exists between subjects in their autonomic nervous system responses to motion sickness stimulation. Additionally, a paucity of data exists that examines the variability within an individual across repeated motion sickness tests. Investigators have also examined the relationship of autonomic responses to motion sickness development. These investigations have used analyses at discrete points in time to describe this relationship. This approach fails to address the time course of autonomic responses and malaise development throughout the motion sickness test. Our objectives were to examine the reliability of autonomic responses and malaise using the final minute of the motion sickness test across five testing occasions, to examine the reliability of the change in autonomic responses and the change in malaise across five testing occasions, and to examine the relationship between changes in autonomic responses and changes in malaise level across the entire motion sickness test. Our results indicate that, based on the final minute of testing, the autonomic responses of heart rate, blood volume pulse, and respiration rate are moderately stable across multiple tests. Changes in heart rate, blood volume pulse, respiration rate, and malaise throughout the test duration were less stable across the tests. We attribute this instability to variations in individual susceptibility and the error associated with estimating a measure of autonomic gain.

Visual fatigue modeling for stereoscopic video shot based on camera motion

NASA Astrophysics Data System (ADS)

Shi, Guozhong; Sang, Xinzhu; Yu, Xunbo; Liu, Yangdong; Liu, Jing

2014-11-01

As three-dimensional television (3-DTV) and 3-D movie become popular, the discomfort of visual feeling limits further applications of 3D display technology. The cause of visual discomfort from stereoscopic video conflicts between accommodation and convergence, excessive binocular parallax, fast motion of objects and so on. Here, a novel method for evaluating visual fatigue is demonstrated. Influence factors including spatial structure, motion scale and comfortable zone are analyzed. According to the human visual system (HVS), people only need to converge their eyes to the specific objects for static cameras and background. Relative motion should be considered for different camera conditions determining different factor coefficients and weights. Compared with the traditional visual fatigue prediction model, a novel visual fatigue predicting model is presented. Visual fatigue degree is predicted using multiple linear regression method combining with the subjective evaluation. Consequently, each factor can reflect the characteristics of the scene, and the total visual fatigue score can be indicated according to the proposed algorithm. Compared with conventional algorithms which ignored the status of the camera, our approach exhibits reliable performance in terms of correlation with subjective test results.

Biomechanical interpretation of a free-breathing lung motion model

NASA Astrophysics Data System (ADS)

Zhao, Tianyu; White, Benjamin; Moore, Kevin L.; Lamb, James; Yang, Deshan; Lu, Wei; Mutic, Sasa; Low, Daniel A.

2011-12-01

The purpose of this paper is to develop a biomechanical model for free-breathing motion and compare it to a published heuristic five-dimensional (5D) free-breathing lung motion model. An ab initio biomechanical model was developed to describe the motion of lung tissue during free breathing by analyzing the stress-strain relationship inside lung tissue. The first-order approximation of the biomechanical model was equivalent to a heuristic 5D free-breathing lung motion model proposed by Low et al in 2005 (Int. J. Radiat. Oncol. Biol. Phys. 63 921-9), in which the motion was broken down to a linear expansion component and a hysteresis component. To test the biomechanical model, parameters that characterize expansion, hysteresis and angles between the two motion components were reported independently and compared between two models. The biomechanical model agreed well with the heuristic model within 5.5% in the left lungs and 1.5% in the right lungs for patients without lung cancer. The biomechanical model predicted that a histogram of angles between the two motion components should have two peaks at 39.8° and 140.2° in the left lungs and 37.1° and 142.9° in the right lungs. The data from the 5D model verified the existence of those peaks at 41.2° and 148.2° in the left lungs and 40.1° and 140° in the right lungs for patients without lung cancer. Similar results were also observed for the patients with lung cancer, but with greater discrepancies. The maximum-likelihood estimation of hysteresis magnitude was reported to be 2.6 mm for the lung cancer patients. The first-order approximation of the biomechanical model fit the heuristic 5D model very well. The biomechanical model provided new insights into breathing motion with specific focus on motion trajectory hysteresis.

Model of human visual-motion sensing

NASA Technical Reports Server (NTRS)

Watson, A. B.; Ahumada, A. J., Jr.

1985-01-01

A model of how humans sense the velocity of moving images is proposed. The model exploits constraints provided by human psychophysics, notably that motion-sensing elements appear tuned for two-dimensional spatial frequency, and by the frequency spectrum of a moving image, namely, that its support lies in the plane in which the temporal frequency equals the dot product of the spatial frequency and the image velocity. The first stage of the model is a set of spatial-frequency-tuned, direction-selective linear sensors. The temporal frequency of the response of each sensor is shown to encode the component of the image velocity in the sensor direction. At the second stage, these components are resolved in order to measure the velocity of image motion at each of a number of spatial locations and spatial frequencies. The model has been applied to several illustrative examples, including apparent motion, coherent gratings, and natural image sequences. The model agrees qualitatively with human perception.

Detecting and Analyzing Multiple Moving Objects in Crowded Environments with Coherent Motion Regions

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

Cheriyadat, Anil M.

Understanding the world around us from large-scale video data requires vision systems that can perform automatic interpretation. While human eyes can unconsciously perceive independent objects in crowded scenes and other challenging operating environments, automated systems have difficulty detecting, counting, and understanding their behavior in similar scenes. Computer scientists at ORNL have a developed a technology termed as "Coherent Motion Region Detection" that invloves identifying multiple indepedent moving objects in crowded scenes by aggregating low-level motion cues extracted from moving objects. Humans and other species exploit such low-level motion cues seamlessely to perform perceptual grouping for visual understanding. The algorithm detectsmore » and tracks feature points on moving objects resulting in partial trajectories that span coherent 3D region in the space-time volume defined by the video. In the case of multi-object motion, many possible coherent motion regions can be constructed around the set of trajectories. The unique approach in the algorithm is to identify all possible coherent motion regions, then extract a subset of motion regions based on an innovative measure to automatically locate moving objects in crowded environments.The software reports snapshot of the object, count, and derived statistics ( count over time) from input video streams. The software can directly process videos streamed over the internet or directly from a hardware device (camera).« less

Motion sickness: a negative reinforcement model.

PubMed

Bowins, Brad

2010-01-15

Theories pertaining to the "why" of motion sickness are in short supply relative to those detailing the "how." Considering the profoundly disturbing and dysfunctional symptoms of motion sickness, it is difficult to conceive of why this condition is so strongly biologically based in humans and most other mammalian and primate species. It is posited that motion sickness evolved as a potent negative reinforcement system designed to terminate motion involving sensory conflict or postural instability. During our evolution and that of many other species, motion of this type would have impaired evolutionary fitness via injury and/or signaling weakness and vulnerability to predators. The symptoms of motion sickness strongly motivate the individual to terminate the offending motion by early avoidance, cessation of movement, or removal of oneself from the source. The motion sickness negative reinforcement mechanism functions much like pain to strongly motivate evolutionary fitness preserving behavior. Alternative why theories focusing on the elimination of neurotoxins and the discouragement of motion programs yielding vestibular conflict suffer from several problems, foremost that neither can account for the rarity of motion sickness in infants and toddlers. The negative reinforcement model proposed here readily accounts for the absence of motion sickness in infants and toddlers, in that providing strong motivation to terminate aberrant motion does not make sense until a child is old enough to act on this motivation.

Impaired heel to toe progression during gait is related to reduced ankle range of motion in people with Multiple Sclerosis.

PubMed

Psarakis, Michael; Greene, David; Moresi, Mark; Baker, Michael; Stubbs, Peter; Brodie, Matthew; Lord, Stephen; Hoang, Phu

2017-11-01

Gait impairment in people with Multiple Sclerosis results from neurological impairment, muscle weakness and reduced range of motion. Restrictions in passive ankle range of motion can result in abnormal heel-to-toe progression (weight transfer) and inefficient gait patterns in people with Multiple Sclerosis. The purpose of this study was to determine the associations between gait impairment, heel-to-toe progression and ankle range of motion in people with Multiple Sclerosis. Twelve participants with Multiple Sclerosis and twelve healthy age-matched participants were assessed. Spatiotemporal parameters of gait and individual footprint data were used to investigate group differences. A pressure sensitive walkway was used to divide each footprint into three phases (contact, mid-stance, propulsive) and calculate the heel-to-toe progression during the stance phase of gait. Compared to healthy controls, people with Multiple Sclerosis spent relatively less time in contact phase (7.8% vs 25.1%) and more time in the mid stance phase of gait (57.3% vs 33.7%). Inter-limb differences were observed in people with Multiple Sclerosis between the affected and non-affected sides for contact (7.8% vs 15.3%) and mid stance (57.3% and 47.1%) phases. Differences in heel-to-toe progression remained significant after adjusting for walking speed and were correlated with walking distance and ankle range of motion. Impaired heel-to-toe progression was related to poor ankle range of motion in people with Multiple Sclerosis. Heel-to-toe progression provided a sensitive measure for assessing gait impairments that were not detectable using standard spatiotemporal gait parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.

Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy.

PubMed

Chen, Haibin; Zhong, Zichun; Yang, Yiwei; Chen, Jiawei; Zhou, Linghong; Zhen, Xin; Gu, Xuejun

2018-02-27

The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intra-fraction/inter-fraction tracking, respectively. The extensive validations have demonstrated the effectiveness and reliability of the proposed model in motion tracking for both the tumor and the lung in lung cancer radiotherapy.

4D-CT motion estimation using deformable image registration and 5D respiratory motion modeling.

PubMed

Yang, Deshan; Lu, Wei; Low, Daniel A; Deasy, Joseph O; Hope, Andrew J; El Naqa, Issam

2008-10-01

Four-dimensional computed tomography (4D-CT) imaging technology has been developed for radiation therapy to provide tumor and organ images at the different breathing phases. In this work, a procedure is proposed for estimating and modeling the respiratory motion field from acquired 4D-CT imaging data and predicting tissue motion at the different breathing phases. The 4D-CT image data consist of series of multislice CT volume segments acquired in ciné mode. A modified optical flow deformable image registration algorithm is used to compute the image motion from the CT segments to a common full volume 3D-CT reference. This reference volume is reconstructed using the acquired 4D-CT data at the end-of-exhalation phase. The segments are optimally aligned to the reference volume according to a proposed a priori alignment procedure. The registration is applied using a multigrid approach and a feature-preserving image downsampling maxfilter to achieve better computational speed and higher registration accuracy. The registration accuracy is about 1.1 +/- 0.8 mm for the lung region according to our verification using manually selected landmarks and artificially deformed CT volumes. The estimated motion fields are fitted to two 5D (spatial 3D+tidal volume+airflow rate) motion models: forward model and inverse model. The forward model predicts tissue movements and the inverse model predicts CT density changes as a function of tidal volume and airflow rate. A leave-one-out procedure is used to validate these motion models. The estimated modeling prediction errors are about 0.3 mm for the forward model and 0.4 mm for the inverse model.

Physiological motion modeling for organ-mounted robots.

PubMed

Wood, Nathan A; Schwartzman, David; Zenati, Marco A; Riviere, Cameron N

2017-12-01

Organ-mounted robots passively compensate heartbeat and respiratory motion. In model-guided procedures, this motion can be a significant source of information that can be used to aid in localization or to add dynamic information to static preoperative maps. Models for estimating periodic motion are proposed for both position and orientation. These models are then tested on animal data and optimal orders are identified. Finally, methods for online identification are demonstrated. Models using exponential coordinates and Euler-angle parameterizations are as accurate as models using quaternion representations, yet require a quarter fewer parameters. Models which incorporate more than four cardiac or three respiration harmonics are no more accurate. Finally, online methods estimate model parameters as accurately as offline methods within three respiration cycles. These methods provide a complete framework for accurately modelling the periodic deformation of points anywhere on the surface of the heart in a closed chest. Copyright © 2017 John Wiley & Sons, Ltd.

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.

A state-based probabilistic model for tumor respiratory motion prediction

NASA Astrophysics Data System (ADS)

Kalet, Alan; Sandison, George; Wu, Huanmei; Schmitz, Ruth

2010-12-01

This work proposes a new probabilistic mathematical model for predicting tumor motion and position based on a finite state representation using the natural breathing states of exhale, inhale and end of exhale. Tumor motion was broken down into linear breathing states and sequences of states. Breathing state sequences and the observables representing those sequences were analyzed using a hidden Markov model (HMM) to predict the future sequences and new observables. Velocities and other parameters were clustered using a k-means clustering algorithm to associate each state with a set of observables such that a prediction of state also enables a prediction of tumor velocity. A time average model with predictions based on average past state lengths was also computed. State sequences which are known a priori to fit the data were fed into the HMM algorithm to set a theoretical limit of the predictive power of the model. The effectiveness of the presented probabilistic model has been evaluated for gated radiation therapy based on previously tracked tumor motion in four lung cancer patients. Positional prediction accuracy is compared with actual position in terms of the overall RMS errors. Various system delays, ranging from 33 to 1000 ms, were tested. Previous studies have shown duty cycles for latencies of 33 and 200 ms at around 90% and 80%, respectively, for linear, no prediction, Kalman filter and ANN methods as averaged over multiple patients. At 1000 ms, the previously reported duty cycles range from approximately 62% (ANN) down to 34% (no prediction). Average duty cycle for the HMM method was found to be 100% and 91 ± 3% for 33 and 200 ms latency and around 40% for 1000 ms latency in three out of four breathing motion traces. RMS errors were found to be lower than linear and no prediction methods at latencies of 1000 ms. The results show that for system latencies longer than 400 ms, the time average HMM prediction outperforms linear, no prediction, and the more

Coupled grain boundary motion in aluminium: the effect of structural multiplicity

NASA Astrophysics Data System (ADS)

Cheng, Kuiyu; Zhang, Liang; Lu, Cheng; Tieu, Kiet

2016-05-01

The shear-induced coupled grain boundary motion plays an important role in the deformation of nanocrystalline (NC) materials. It has been known that the atomic structure of the grain boundary (GB) is not necessarily unique for a given set of misorientation and inclination of the boundary plane. However, the effect of the structural multiplicity of the GB on its coupled motion has not been reported. In the present study we investigated the structural multiplicity of the symmetric tilt Σ5(310) boundary in aluminium and its influence on the GB behaviour at a temperature range of 300 K-600 K using molecular dynamic simulations. Two starting atomic configurations were adopted in the simulations which resulted in three different GB structures at different temperatures. Under the applied shear deformation each GB structure exhibited its unique GB behaviour. A dual GB behaviour, namely the transformation of one GB behaviour to another during deformation, was observed for the second starting configuration at a temperature of 500 K. The atomistic mechanisms responsible for these behaviour were analysed in detail. The result of this study implicates a strong relationship between GB structures and their behaviour, and provides a further information of the grain boundary mediated plasticity in nanocrystalline materials.

Local discretization method for overdamped Brownian motion on a potential with multiple deep wells.

PubMed

Nguyen, P T T; Challis, K J; Jack, M W

2016-11-01

We present a general method for transforming the continuous diffusion equation describing overdamped Brownian motion on a time-independent potential with multiple deep wells to a discrete master equation. The method is based on an expansion in localized basis states of local metastable potentials that match the full potential in the region of each potential well. Unlike previous basis methods for discretizing Brownian motion on a potential, this approach is valid for periodic potentials with varying multiple deep wells per period and can also be applied to nonperiodic systems. We apply the method to a range of potentials and find that potential wells that are deep compared to five times the thermal energy can be associated with a discrete localized state while shallower wells are better incorporated into the local metastable potentials of neighboring deep potential wells.

Local discretization method for overdamped Brownian motion on a potential with multiple deep wells

NASA Astrophysics Data System (ADS)

Nguyen, P. T. T.; Challis, K. J.; Jack, M. W.

2016-11-01

We present a general method for transforming the continuous diffusion equation describing overdamped Brownian motion on a time-independent potential with multiple deep wells to a discrete master equation. The method is based on an expansion in localized basis states of local metastable potentials that match the full potential in the region of each potential well. Unlike previous basis methods for discretizing Brownian motion on a potential, this approach is valid for periodic potentials with varying multiple deep wells per period and can also be applied to nonperiodic systems. We apply the method to a range of potentials and find that potential wells that are deep compared to five times the thermal energy can be associated with a discrete localized state while shallower wells are better incorporated into the local metastable potentials of neighboring deep potential wells.

Modeling of earthquake ground motion in the frequency domain

NASA Astrophysics Data System (ADS)

Thrainsson, Hjortur

In recent years, the utilization of time histories of earthquake ground motion has grown considerably in the design and analysis of civil structures. It is very unlikely, however, that recordings of earthquake ground motion will be available for all sites and conditions of interest. Hence, there is a need for efficient methods for the simulation and spatial interpolation of earthquake ground motion. In addition to providing estimates of the ground motion at a site using data from adjacent recording stations, spatially interpolated ground motions can also be used in design and analysis of long-span structures, such as bridges and pipelines, where differential movement is important. The objective of this research is to develop a methodology for rapid generation of horizontal earthquake ground motion at any site for a given region, based on readily available source, path and site characteristics, or (sparse) recordings. The research includes two main topics: (i) the simulation of earthquake ground motion at a given site, and (ii) the spatial interpolation of earthquake ground motion. In topic (i), models are developed to simulate acceleration time histories using the inverse discrete Fourier transform. The Fourier phase differences, defined as the difference in phase angle between adjacent frequency components, are simulated conditional on the Fourier amplitude. Uniformly processed recordings from recent California earthquakes are used to validate the simulation models, as well as to develop prediction formulas for the model parameters. The models developed in this research provide rapid simulation of earthquake ground motion over a wide range of magnitudes and distances, but they are not intended to replace more robust geophysical models. In topic (ii), a model is developed in which Fourier amplitudes and Fourier phase angles are interpolated separately. A simple dispersion relationship is included in the phase angle interpolation. The accuracy of the interpolation

A novel CT acquisition and analysis technique for breathing motion modeling

NASA Astrophysics Data System (ADS)

Low, Daniel A.; White, Benjamin M.; Lee, Percy P.; Thomas, David H.; Gaudio, Sergio; Jani, Shyam S.; Wu, Xiao; Lamb, James M.

2013-06-01

To report on a novel technique for providing artifact-free quantitative four-dimensional computed tomography (4DCT) image datasets for breathing motion modeling. Commercial clinical 4DCT methods have difficulty managing irregular breathing. The resulting images contain motion-induced artifacts that can distort structures and inaccurately characterize breathing motion. We have developed a novel scanning and analysis method for motion-correlated CT that utilizes standard repeated fast helical acquisitions, a simultaneous breathing surrogate measurement, deformable image registration, and a published breathing motion model. The motion model differs from the CT-measured motion by an average of 0.65 mm, indicating the precision of the motion model. The integral of the divergence of one of the motion model parameters is predicted to be a constant 1.11 and is found in this case to be 1.09, indicating the accuracy of the motion model. The proposed technique shows promise for providing motion-artifact free images at user-selected breathing phases, accurate Hounsfield units, and noise characteristics similar to non-4D CT techniques, at a patient dose similar to or less than current 4DCT techniques.

Vestibular models for design and evaluation of flight simulator motion

NASA Technical Reports Server (NTRS)

Bussolari, S. R.; Sullivan, R. B.; Young, L. R.

1986-01-01

The use of spatial orientation models in the design and evaluation of control systems for motion-base flight simulators is investigated experimentally. The development of a high-fidelity motion drive controller using an optimal control approach based on human vestibular models is described. The formulation and implementation of the optimal washout system are discussed. The effectiveness of the motion washout system was evaluated by studying the response of six motion washout systems to the NASA/AMES Vertical Motion Simulator for a single dash-quick-stop maneuver. The effects of the motion washout system on pilot performance and simulator acceptability are examined. The data reveal that human spatial orientation models are useful for the design and evaluation of flight simulator motion fidelity.

Ground Motion Prediction Models for Caucasus Region

NASA Astrophysics Data System (ADS)

Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

2016-04-01

Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

Motion compensation via redundant-wavelet multihypothesis.

PubMed

Fowler, James E; Cui, Suxia; Wang, Yonghui

2006-10-01

Multihypothesis motion compensation has been widely used in video coding with previous attention focused on techniques employing predictions that are diverse spatially or temporally. In this paper, the multihypothesis concept is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding multiple-phase inverse transform implicitly combines the phase-diverse predictions into a single spatial-domain prediction for motion compensation. The performance advantage of this redundant-wavelet-multihypothesis approach is investigated analytically, invoking the fact that the multiple-phase inverse involves a projection that significantly reduces the power of a dense-motion residual modeled as additive noise. The analysis shows that redundant-wavelet multihypothesis is capable of up to a 7-dB reduction in prediction-residual variance over an equivalent single-phase, single-hypothesis approach. Experimental results substantiate the performance advantage for a block-based implementation.

Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction

PubMed Central

Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S.

2015-01-01

This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants’ specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive, and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants’ behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods. PMID:26557047

Multiple-time-scale motion in molecularly linked nanoparticle arrays.

PubMed

George, Christopher; Szleifer, Igal; Ratner, Mark

2013-01-22

We explore the transport of electrons between electrodes that encase a two-dimensional array of metallic quantum dots linked by molecular bridges (such as α,ω alkaline dithiols). Because the molecules can move at finite temperatures, the entire transport structure comprising the quantum dots and the molecules is in dynamical motion while the charge is being transported. There are then several physical processes (physical excursions of molecules and quantum dots, electronic migration, ordinary vibrations), all of which influence electronic transport. Each can occur on a different time scale. It is therefore not appropriate to use standard approaches to this sort of electron transfer problem. Instead, we present a treatment in which three different theoretical approaches-kinetic Monte Carlo, classical molecular dynamics, and quantum transport-are all employed. In certain limits, some of the dynamical effects are unimportant. But in general, the transport seems to follow a sort of dynamic bond percolation picture, an approach originally introduced as formal models and later applied to polymer electrolytes. Different rate-determining steps occur in different limits. This approach offers a powerful scheme for dealing with multiple time scale transport problems, as will exist in many situations with several pathways through molecular arrays or even individual molecules that are dynamically disordered.

A kinematic model to assess spinal motion during walking.

PubMed

Konz, Regina J; Fatone, Stefania; Stine, Rebecca L; Ganju, Aruna; Gard, Steven A; Ondra, Stephen L

2006-11-15

A 3-dimensional multi-segment kinematic spine model was developed for noninvasive analysis of spinal motion during walking. Preliminary data from able-bodied ambulators were collected and analyzed using the model. Neither the spine's role during walking nor the effect of surgical spinal stabilization on gait is fully understood. Typically, gait analysis models disregard the spine entirely or regard it as a single rigid structure. Data on regional spinal movements, in conjunction with lower limb data, associated with walking are scarce. KinTrak software (Motion Analysis Corp., Santa Rosa, CA) was used to create a biomechanical model for analysis of 3-dimensional regional spinal movements. Measuring known angles from a mechanical model and comparing them to the calculated angles validated the kinematic model. Spine motion data were collected from 10 able-bodied adults walking at 5 self-selected speeds. These results were compared to data reported in the literature. The uniaxial angles measured on the mechanical model were within 5 degrees of the calculated kinematic model angles, and the coupled angles were within 2 degrees. Regional spine kinematics from able-bodied subjects calculated with this model compared well to data reported by other authors. A multi-segment kinematic spine model has been developed and validated for analysis of spinal motion during walking. By understanding the spine's role during ambulation and the cause-and-effect relationship between spine motion and lower limb motion, preoperative planning may be augmented to restore normal alignment and balance with minimal negative effects on walking.

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

PubMed Central

Yuan, Amy; Wei, Jie; Gaebler, Carl P.; Huang, Hailiang; Olek, Devin; Li, Guang

2016-01-01

Purpose To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. Methods and Materials A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. Results The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm3 (−26% to 61%), and the ΔBP ranged from 0 to 0.2 (−71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P = .0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P = .72) predicted with the 5-dimensional model. Conclusions A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction

Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging

NASA Astrophysics Data System (ADS)

Kuai, Zi-Xiang; Liu, Wan-Yu; Zhu, Yue-Min

2017-11-01

The aim of this work was to investigate the effect of multiple perfusion components on the pseudo-diffusion coefficient D * in the bi-exponential intravoxel incoherent motion (IVIM) model. Simulations were first performed to examine how the presence of multiple perfusion components influences D *. The real data of livers (n  =  31), spleens (n  =  31) and kidneys (n  =  31) of 31 volunteers was then acquired using DWI for in vivo study and the number of perfusion components in these tissues was determined together with their perfusion fraction and D *, using an adaptive multi-exponential IVIM model. Finally, the bi-exponential model was applied to the real data and the mean, standard variance and coefficient of variation of D * as well as the fitting residual were calculated over the 31 volunteers for each of the three tissues and compared between them. The results of both the simulations and the in vivo study showed that, for the bi-exponential IVIM model, both the variance of D * and the fitting residual tended to increase when the number of perfusion components was increased or when the difference between perfusion components became large. In addition, it was found that the kidney presented the fewest perfusion components among the three tissues. The present study demonstrated that multi-component perfusion is a main factor that causes high variance of D * and the bi-exponential model should be used only when the tissues under investigation have few perfusion components, for example the kidney.

Model and parametric uncertainty in source-based kinematic models of earthquake ground motion

USGS Publications Warehouse

Hartzell, Stephen; Frankel, Arthur; Liu, Pengcheng; Zeng, Yuehua; Rahman, Shariftur

2011-01-01

Four independent ground-motion simulation codes are used to model the strong ground motion for three earthquakes: 1994 Mw 6.7 Northridge, 1989 Mw 6.9 Loma Prieta, and 1999 Mw 7.5 Izmit. These 12 sets of synthetics are used to make estimates of the variability in ground-motion predictions. In addition, ground-motion predictions over a grid of sites are used to estimate parametric uncertainty for changes in rupture velocity. We find that the combined model uncertainty and random variability of the simulations is in the same range as the variability of regional empirical ground-motion data sets. The majority of the standard deviations lie between 0.5 and 0.7 natural-log units for response spectra and 0.5 and 0.8 for Fourier spectra. The estimate of model epistemic uncertainty, based on the different model predictions, lies between 0.2 and 0.4, which is about one-half of the estimates for the standard deviation of the combined model uncertainty and random variability. Parametric uncertainty, based on variation of just the average rupture velocity, is shown to be consistent in amplitude with previous estimates, showing percentage changes in ground motion from 50% to 300% when rupture velocity changes from 2.5 to 2.9 km/s. In addition, there is some evidence that mean biases can be reduced by averaging ground-motion estimates from different methods.

A Fully Nonlinear, Dynamically Consistent Numerical Model for Solid-Body Ship Motion. I. Ship Motion with Fixed Heading

NASA Technical Reports Server (NTRS)

Lin, Ray-Quing; Kuang, Weijia

2011-01-01

In this paper, we describe the details of our numerical model for simulating ship solidbody motion in a given environment. In this model, the fully nonlinear dynamical equations governing the time-varying solid-body ship motion under the forces arising from ship wave interactions are solved with given initial conditions. The net force and moment (torque) on the ship body are directly calculated via integration of the hydrodynamic pressure over the wetted surface and the buoyancy effect from the underwater volume of the actual ship hull with a hybrid finite-difference/finite-element method. Neither empirical nor free parametrization is introduced in this model, i.e. no a priori experimental data are needed for modelling. This model is benchmarked with many experiments of various ship hulls for heave, roll and pitch motion. In addition to the benchmark cases, numerical experiments are also carried out for strongly nonlinear ship motion with a fixed heading. These new cases demonstrate clearly the importance of nonlinearities in ship motion modelling.

Typical motions in multiple systems

NASA Technical Reports Server (NTRS)

Anosova, Joanna P.

1990-01-01

In very old times, people counted - one, two, many. The author wants to show that they were right. Consider the motions of isolated bodies: (1) N = 1 - simple motion; (2) N = 2 - Keplerian orbits; and (3) N = 3 - this is the difficult problem. In general, this problem can be studied only by computer simulations. The author studied this problem over many years (see, e.g., Agekian and Anosova, 1967; Anosova, 1986, 1989 a,b). The principal result is that two basic types of dynamics take place in triple systems. The first special type is the stable hierarchical systems with two almost Keplerian orbits. The second general type is the unstable triple systems with complicated motions of the bodies. By random choice of the initial conditions, by the Monte-Carlo method, the stable systems comprised about approx. 10% of the examined cases; the unstable systems comprised the other approx. 90% of cases under consideration. In N greater than 3, the studies of dynamics of such systems by computer simulations show that we have in general also the motions roughly as at the cases 1 - 3 with the relative negative or positive energies of the bodies. In the author's picture, the typical trajectories of the bodies in unstable triple systems of the general type of dynamics are seen. Such systems are disrupted always after close triple approaches of the bodies. These approaches play a role like the gravitational slingshot. Often, the velocities of escapers are very large. On the other hand, the movie also shows the dynamical processes of a formation, dynamical evolution and disruption of the temporary wide binaries in triples and a formation of final hard massive binaries in the final evolution of triples.

Multilayer Joint Gait-Pose Manifolds for Human Gait Motion Modeling.

PubMed

Ding, Meng; Fan, Guolian

2015-11-01

We present new multilayer joint gait-pose manifolds (multilayer JGPMs) for complex human gait motion modeling, where three latent variables are defined jointly in a low-dimensional manifold to represent a variety of body configurations. Specifically, the pose variable (along the pose manifold) denotes a specific stage in a walking cycle; the gait variable (along the gait manifold) represents different walking styles; and the linear scale variable characterizes the maximum stride in a walking cycle. We discuss two kinds of topological priors for coupling the pose and gait manifolds, i.e., cylindrical and toroidal, to examine their effectiveness and suitability for motion modeling. We resort to a topologically-constrained Gaussian process (GP) latent variable model to learn the multilayer JGPMs where two new techniques are introduced to facilitate model learning under limited training data. First is training data diversification that creates a set of simulated motion data with different strides. Second is the topology-aware local learning to speed up model learning by taking advantage of the local topological structure. The experimental results on the Carnegie Mellon University motion capture data demonstrate the advantages of our proposed multilayer models over several existing GP-based motion models in terms of the overall performance of human gait motion modeling.

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

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

Yuan, Amy; Wei, Jie; Gaebler, Carl P.

Purpose: To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. Methods and Materials: A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2more » amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. Results: The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm{sup 3} (−26% to 61%), and the ΔBP ranged from 0 to 0.2 (−71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model. Conclusions: A novel physical RMP model was developed with an average accuracy of 1.2 ± 1

Annual Geocenter Motion from Space Geodesy and Models

NASA Astrophysics Data System (ADS)

Ries, J. C.

2013-12-01

Ideally, the origin of the terrestrial reference frame and the center of mass of the Earth are always coincident. By construction, the origin of the reference frame is coincident with the mean Earth center of mass, averaged over the time span of the satellite laser ranging (SLR) observations used in the reference frame solution, within some level of uncertainty. At shorter time scales, tidal and non-tidal mass variations result in an offset between the origin and geocenter, called geocenter motion. Currently, there is a conventional model for the tidally-coherent diurnal and semi-diurnal geocenter motion, but there is no model for the non-tidal annual variation. This annual motion reflects the largest-scale mass redistribution in the Earth system, so it essential to observe it for a complete description of the total mass transport. Failing to model it can also cause false signals in geodetic products such as sea height observations from satellite altimeters. In this paper, a variety of estimates for the annual geocenter motion are presented based on several different geodetic techniques and models, and a ';consensus' model from SLR is suggested.

Satellite attitude motion models for capture and retrieval investigations

NASA Technical Reports Server (NTRS)

Cochran, John E., Jr.; Lahr, Brian S.

1986-01-01

The primary purpose of this research is to provide mathematical models which may be used in the investigation of various aspects of the remote capture and retrieval of uncontrolled satellites. Emphasis has been placed on analytical models; however, to verify analytical solutions, numerical integration must be used. Also, for satellites of certain types, numerical integration may be the only practical or perhaps the only possible method of solution. First, to provide a basis for analytical and numerical work, uncontrolled satellites were categorized using criteria based on: (1) orbital motions, (2) external angular momenta, (3) internal angular momenta, (4) physical characteristics, and (5) the stability of their equilibrium states. Several analytical solutions for the attitude motions of satellite models were compiled, checked, corrected in some minor respects and their short-term prediction capabilities were investigated. Single-rigid-body, dual-spin and multi-rotor configurations are treated. To verify the analytical models and to see how the true motion of a satellite which is acted upon by environmental torques differs from its corresponding torque-free motion, a numerical simulation code was developed. This code contains a relatively general satellite model and models for gravity-gradient and aerodynamic torques. The spacecraft physical model for the code and the equations of motion are given. The two environmental torque models are described.

Ising model for collective decision making during group motion

NASA Astrophysics Data System (ADS)

Pinkoviezky, Itai; Gov, Nir; Couzin, Iain

Collective decision making is a key feature during natural motion of animal groups and is also crucial for human groups. This phenomenon can be exemplified by the scenario of two subgroups that hold conflicting preferred directions of motion. The constraint of group cohesion drives the motion either towards a compromise or towards one of the preferred targets. The transition between compromise and decision has been found in simulations of flock models, but the nature of this transition is not well understood. We present a minimal spin model for this system where we interpret the spin-spin interaction as a social force. This model exhibits both first and second order transitions. The group motion changes from size-dependent diffusion at high temperatures to run-and-tumble motion below the critical temperature. In the presence of minority and majority subgroups, we find that there is a trade-off between the speed of reaching a target and the accuracy. We then compare the results of the spin model to detailed simulations of a flock model, and find overall very similar dynamics, with the role of the temperature taken by the inverse of the number of uninformed individuals.

Modeling a space-variant cortical representation for apparent motion.

PubMed

Wurbs, Jeremy; Mingolla, Ennio; Yazdanbakhsh, Arash

2013-08-06

Receptive field sizes of neurons in early primate visual areas increase with eccentricity, as does temporal processing speed. The fovea is evidently specialized for slow, fine movements while the periphery is suited for fast, coarse movements. In either the fovea or periphery discrete flashes can produce motion percepts. Grossberg and Rudd (1989) used traveling Gaussian activity profiles to model long-range apparent motion percepts. We propose a neural model constrained by physiological data to explain how signals from retinal ganglion cells to V1 affect the perception of motion as a function of eccentricity. Our model incorporates cortical magnification, receptive field overlap and scatter, and spatial and temporal response characteristics of retinal ganglion cells for cortical processing of motion. Consistent with the finding of Baker and Braddick (1985), in our model the maximum flash distance that is perceived as an apparent motion (Dmax) increases linearly as a function of eccentricity. Baker and Braddick (1985) made qualitative predictions about the functional significance of both stimulus and visual system parameters that constrain motion perception, such as an increase in the range of detectable motions as a function of eccentricity and the likely role of higher visual processes in determining Dmax. We generate corresponding quantitative predictions for those functional dependencies for individual aspects of motion processing. Simulation results indicate that the early visual pathway can explain the qualitative linear increase of Dmax data without reliance on extrastriate areas, but that those higher visual areas may serve as a modulatory influence on the exact Dmax increase.

Joint image and motion reconstruction for PET using a B-spline motion model.

PubMed

Blume, Moritz; Navab, Nassir; Rafecas, Magdalena

2012-12-21

We present a novel joint image and motion reconstruction method for PET. The method is based on gated data and reconstructs an image together with a motion function. The motion function can be used to transform the reconstructed image to any of the input gates. All available events (from all gates) are used in the reconstruction. The presented method uses a B-spline motion model, together with a novel motion regularization procedure that does not need a regularization parameter (which is usually extremely difficult to adjust). Several image and motion grid levels are used in order to reduce the reconstruction time. In a simulation study, the presented method is compared to a recently proposed joint reconstruction method. While the presented method provides comparable reconstruction quality, it is much easier to use since no regularization parameter has to be chosen. Furthermore, since the B-spline discretization of the motion function depends on fewer parameters than a displacement field, the presented method is considerably faster and consumes less memory than its counterpart. The method is also applied to clinical data, for which a novel purely data-driven gating approach is presented.

Neural dynamics of motion perception: direction fields, apertures, and resonant grouping.

PubMed

Grossberg, S; Mingolla, E

1993-03-01

A neural network model of global motion segmentation by visual cortex is described. Called the motion boundary contour system (BCS), the model clarifies how ambiguous local movements on a complex moving shape are actively reorganized into a coherent global motion signal. Unlike many previous researchers, we analyze how a coherent motion signal is imparted to all regions of a moving figure, not only to regions at which unambiguous motion signals exist. The model hereby suggests a solution to the global aperture problem. The motion BCS describes how preprocessing of motion signals by a motion oriented contrast (MOC) filter is joined to long-range cooperative grouping mechanisms in a motion cooperative-competitive (MOCC) loop to control phenomena such as motion capture. The motion BCS is computed in parallel with the static BCS of Grossberg and Mingolla (1985a, 1985b, 1987). Homologous properties of the motion BCS and the static BCS, specialized to process motion directions and static orientations, respectively, support a unified explanation of many data about static form perception and motion form perception that have heretofore been unexplained or treated separately. Predictions about microscopic computational differences of the parallel cortical streams V1-->MT and V1-->V2-->MT are made--notably, the magnocellular thick stripe and parvocellular interstripe streams. It is shown how the motion BCS can compute motion directions that may be synthesized from multiple orientations with opposite directions of contrast. Interactions of model simple cells, complex cells, hyper-complex cells, and bipole cells are described, with special emphasis given to new functional roles in direction disambiguation for endstopping at multiple processing stages and to the dynamic interplay of spatially short-range and long-range interactions.

Global plate motion frames: Toward a unified model

NASA Astrophysics Data System (ADS)

Torsvik, Trond H.; Müller, R. Dietmar; van der Voo, Rob; Steinberger, Bernhard; Gaina, Carmen

2008-09-01

Plate tectonics constitutes our primary framework for understanding how the Earth works over geological timescales. High-resolution mapping of relative plate motions based on marine geophysical data has followed the discovery of geomagnetic reversals, mid-ocean ridges, transform faults, and seafloor spreading, cementing the plate tectonic paradigm. However, so-called "absolute plate motions," describing how the fragments of the outer shell of the Earth have moved relative to a reference system such as the Earth's mantle, are still poorly understood. Accurate absolute plate motion models are essential surface boundary conditions for mantle convection models as well as for understanding past ocean circulation and climate as continent-ocean distributions change with time. A fundamental problem with deciphering absolute plate motions is that the Earth's rotation axis and the averaged magnetic dipole axis are not necessarily fixed to the mantle reference system. Absolute plate motion models based on volcanic hot spot tracks are largely confined to the last 130 Ma and ideally would require knowledge about the motions within the convecting mantle. In contrast, models based on paleomagnetic data reflect plate motion relative to the magnetic dipole axis for most of Earth's history but cannot provide paleolongitudes because of the axial symmetry of the Earth's magnetic dipole field. We analyze four different reference frames (paleomagnetic, African fixed hot spot, African moving hot spot, and global moving hot spot), discuss their uncertainties, and develop a unifying approach for connecting a hot spot track system and a paleomagnetic absolute plate reference system into a "hybrid" model for the time period from the assembly of Pangea (˜320 Ma) to the present. For the last 100 Ma we use a moving hot spot reference frame that takes mantle convection into account, and we connect this to a pre-100 Ma global paleomagnetic frame adjusted 5° in longitude to smooth the reference

A true polar wander model for Neoproterozoic plate motions

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

Ripperdan, R.L.

1992-01-01

Recent paleogeographic reconstructions for the interval 750--500 Ma (Neoproterozoic to Late Cambrian) require rapid rates of plate motion and/or rotation around an equatorial Euler pole to accommodate reconstructions for the Early Paleozoic. Motions of this magnitude appear to be very uncommon during the Phanerozoic. A model for plate motions based on the hypothesis that discrete intervals of rapid true polar wander (RTPW) occurred during the Neoproterozoic can account for the paleogeographic changes with minimum amounts of plate motion. The model uses the paleogeographic reconstructions of Hoffman (1991). The following constraints were applied during derivation of the model: (1) relative motionsmore » between major continental units were restricted to be combinations of great circle or small circle translations with Euler poles of rotation = spin axis; (2) maximum rates of relative translational plate motion were 0.2 m/yr. Based on these constraints, two separate sets of synthetic plate motion trajectories were determined. The sequence of events in both can be summarized as: (1) A rapid true polar wander event of ca 90[degree] rafting a supercontinent to the spin axis; (2) breakup of the polar supercontinent into two fragments, one with the Congo, West Africa, Amazonia, and Baltica cratons, the other with the Laurentia, East Gondwana, and Kalahari cratons; (3) great circle motion of the blocks towards the equator; (4) small circle motion leading to amalgamation of Gondwana and separation of Laurentia and Baltica. In alternative 1, rifting initiates between East Antarctica and Laurentia and one episode of RTPW is required. Alternative 2 requires two episodes of RTPW; and that rifting occurred first along the eastern margin and later along the western margin of Laurentia. Synthetic plate motion trajectories are compared to existing paleomagnetic and geological data, and implications of the model for paleoclimatic changes during the Neoproterozoic are discussed.« less

A depictive neural model for the representation of motion verbs.

PubMed

Rao, Sunil; Aleksander, Igor

2011-11-01

In this paper, we present a depictive neural model for the representation of motion verb semantics in neural models of visual awareness. The problem of modelling motion verb representation is shown to be one of function application, mapping a set of given input variables defining the moving object and the path of motion to a defined output outcome in the motion recognition context. The particular function-applicative implementation and consequent recognition model design presented are seen as arising from a noun-adjective recognition model enabling the recognition of colour adjectives as applied to a set of shapes representing objects to be recognised. The presence of such a function application scheme and a separately implemented position identification and path labelling scheme are accordingly shown to be the primitives required to enable the design and construction of a composite depictive motion verb recognition scheme. Extensions to the presented design to enable the representation of transitive verbs are also discussed.

Attraction of posture and motion-trajectory elements of conspecific biological motion in medaka fish.

PubMed

Shibai, Atsushi; Arimoto, Tsunehiro; Yoshinaga, Tsukasa; Tsuchizawa, Yuta; Khureltulga, Dashdavaa; Brown, Zuben P; Kakizuka, Taishi; Hosoda, Kazufumi

2018-06-05

Visual recognition of conspecifics is necessary for a wide range of social behaviours in many animals. Medaka (Japanese rice fish), a commonly used model organism, are known to be attracted by the biological motion of conspecifics. However, biological motion is a composite of both body-shape motion and entire-field motion trajectory (i.e., posture or motion-trajectory elements, respectively), and it has not been revealed which element mediates the attractiveness. Here, we show that either posture or motion-trajectory elements alone can attract medaka. We decomposed biological motion of the medaka into the two elements and synthesized visual stimuli that contain both, either, or none of the two elements. We found that medaka were attracted by visual stimuli that contain at least one of the two elements. In the context of other known static visual information regarding the medaka, the potential multiplicity of information regarding conspecific recognition has further accumulated. Our strategy of decomposing biological motion into these partial elements is applicable to other animals, and further studies using this technique will enhance the basic understanding of visual recognition of conspecifics.

Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration.

PubMed

Ehrhardt, Jan; Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz

2011-02-01

Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

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

Yamazaki, Kazutoshi, E-mail: kyamazak@kansai-u.ac.jp

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and tomore » evaluate the efficiency of the algorithm.« less

A simple model for strong ground motions and response spectra

USGS Publications Warehouse

Safak, Erdal; Mueller, Charles; Boatwright, John

1988-01-01

A simple model for the description of strong ground motions is introduced. The model shows that response spectra can be estimated by using only four parameters of the ground motion, the RMS acceleration, effective duration and two corner frequencies that characterize the effective frequency band of the motion. The model is windowed band-limited white noise, and is developed by studying the properties of two functions, cumulative squared acceleration in the time domain, and cumulative squared amplitude spectrum in the frequency domain. Applying the methods of random vibration theory, the model leads to a simple analytical expression for the response spectra. The accuracy of the model is checked by using the ground motion recordings from the aftershock sequences of two different earthquakes and simulated accelerograms. The results show that the model gives a satisfactory estimate of the response spectra.

Volumetric display containing multiple two-dimensional color motion pictures

NASA Astrophysics Data System (ADS)

Hirayama, R.; Shiraki, A.; Nakayama, H.; Kakue, T.; Shimobaba, T.; Ito, T.

2014-06-01

We have developed an algorithm which can record multiple two-dimensional (2-D) gradated projection patterns in a single three-dimensional (3-D) object. Each recorded pattern has the individual projected direction and can only be seen from the direction. The proposed algorithm has two important features: the number of recorded patterns is theoretically infinite and no meaningful pattern can be seen outside of the projected directions. In this paper, we expanded the algorithm to record multiple 2-D projection patterns in color. There are two popular ways of color mixing: additive one and subtractive one. Additive color mixing used to mix light is based on RGB colors and subtractive color mixing used to mix inks is based on CMY colors. We made two coloring methods based on the additive mixing and subtractive mixing. We performed numerical simulations of the coloring methods, and confirmed their effectiveness. We also fabricated two types of volumetric display and applied the proposed algorithm to them. One is a cubic displays constructed by light-emitting diodes (LEDs) in 8×8×8 array. Lighting patterns of LEDs are controlled by a microcomputer board. The other one is made of 7×7 array of threads. Each thread is illuminated by a projector connected with PC. As a result of the implementation, we succeeded in recording multiple 2-D color motion pictures in the volumetric displays. Our algorithm can be applied to digital signage, media art and so forth.

Folded Elastic Strip-Based Triboelectric Nanogenerator for Harvesting Human Motion Energy for Multiple Applications.

PubMed

Kang, Yue; Wang, Bo; Dai, Shuge; Liu, Guanlin; Pu, Yanping; Hu, Chenguo

2015-09-16

A folded elastic strip-based triboelectric nanogenerator (FS-TENG) made from two folded double-layer elastic strips of Al/PET and PTFE/PET can achieve multiple functions by low frequency mechanical motion. A single FS-TENG with strip width of 3 cm and length of 27 cm can generate a maximum output current, open-circuit voltage, and peak power of 55 μA, 840 V, and 7.33 mW at deformation frequency of 4 Hz with amplitude of 2.5 cm, respectively. This FS-TENG can work as a weight sensor due to its good elasticity. An integrated generator assembled by four FS-TENGs (IFS-TENG) can harvest the energy of human motion like flapping hands and walking steps. In addition, the IFS-TENG combined with electromagnetically induced electricity can achieve a completely self-driven doorbell with flashing lights. Moreover, a box-like generator integrated by four IFS-TENGs inside can work in horizontal or random motion modes and can be improved to harvest energy in all directions. This work promotes the research of completely self-driven systems and energy harvesting of human motion for applications in our daily life.

Superintegrability of geodesic motion on the sausage model

NASA Astrophysics Data System (ADS)

Arutyunov, Gleb; Heinze, Martin; Medina-Rincon, Daniel

2017-06-01

Reduction of the η-deformed sigma model on AdS_5× S5 to the two-dimensional squashed sphere (S^2)η can be viewed as a special case of the Fateev sausage model where the coupling constant ν is imaginary. We show that geodesic motion in this model is described by a certain superintegrable mechanical system with four-dimensional phase space. This is done by means of explicitly constructing three integrals of motion which satisfy the sl(2) Poisson algebra relations, albeit being non-polynomial in momenta. Further, we find a canonical transformation which transforms the Hamiltonian of this mechanical system to the one describing the geodesic motion on the usual two-sphere. By inverting this transformation we map geodesics on this auxiliary two-sphere back to the sausage model. This paper is a tribute to the memory of Prof Petr Kulish.

A priori motion models for four-dimensional reconstruction in gated cardiac SPECT

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

Lalush, D.S.; Tsui, B.M.W.; Cui, Lin

1996-12-31

We investigate the benefit of incorporating a priori assumptions about cardiac motion in a fully four-dimensional (4D) reconstruction algorithm for gated cardiac SPECT. Previous work has shown that non-motion-specific 4D Gibbs priors enforcing smoothing in time and space can control noise while preserving resolution. In this paper, we evaluate methods for incorporating known heart motion in the Gibbs prior model. The new model is derived by assigning motion vectors to each 4D voxel, defining the movement of that volume of activity into the neighboring time frames. Weights for the Gibbs cliques are computed based on these {open_quotes}most likely{close_quotes} motion vectors.more » To evaluate, we employ the mathematical cardiac-torso (MCAT) phantom with a new dynamic heart model that simulates the beating and twisting motion of the heart. Sixteen realistically-simulated gated datasets were generated, with noise simulated to emulate a real Tl-201 gated SPECT study. Reconstructions were performed using several different reconstruction algorithms, all modeling nonuniform attenuation and three-dimensional detector response. These include ML-EM with 4D filtering, 4D MAP-EM without prior motion assumption, and 4D MAP-EM with prior motion assumptions. The prior motion assumptions included both the correct motion model and incorrect models. Results show that reconstructions using the 4D prior model can smooth noise and preserve time-domain resolution more effectively than 4D linear filters. We conclude that modeling of motion in 4D reconstruction algorithms can be a powerful tool for smoothing noise and preserving temporal resolution in gated cardiac studies.« less

Lung Motion Model Validation Experiments, Free-Breathing Tissue Densitometry, and Ventilation Mapping using Fast Helical CT Imaging

NASA Astrophysics Data System (ADS)

Dou, Hsiang-Tai

The uncertainties due to respiratory motion present significant challenges to accurate characterization of cancerous tissues both in terms of imaging and treatment. Currently available clinical lung imaging techniques are subject to inferior image quality and incorrect motion estimation, with consequences that can systematically impact the downstream treatment delivery and outcome. The main objective of this thesis is the development of the techniques of fast helical computed tomography (CT) imaging and deformable image registration for the radiotherapy applications in accurate breathing motion modeling, lung tissue density modeling and ventilation imaging. Fast helical CT scanning was performed on 64-slice CT scanner using the shortest available gantry rotation time and largest pitch value such that scanning of the thorax region amounts to just two seconds, which is less than typical breathing cycle in humans. The scanning was conducted under free breathing condition. Any portion of the lung anatomy undergoing such scanning protocol would be irradiated for only a quarter second, effectively removing any motion induced image artifacts. The resulting CT data were pristine volumetric images that record the lung tissue position and density in a fraction of the breathing cycle. Following our developed protocol, multiple fast helical CT scans were acquired to sample the tissue positions in different breathing states. To measure the tissue displacement, deformable image registration was performed that registers the non-reference images to the reference one. In modeling breathing motion, external breathing surrogate signal was recorded synchronously with the CT image slices. This allowed for the tissue-specific displacement to be modeled as parametrization of the recorded breathing signal using the 5D lung motion model. To assess the accuracy of the motion model in describing tissue position change, the model was used to simulate the original high-pitch helical CT scan

Moving from spatially segregated to transparent motion: a modelling approach

PubMed Central

Durant, Szonya; Donoso-Barrera, Alejandra; Tan, Sovira; Johnston, Alan

2005-01-01

Motion transparency, in which patterns of moving elements group together to give the impression of lacy overlapping surfaces, provides an important challenge to models of motion perception. It has been suggested that we perceive transparent motion when the shape of the velocity histogram of the stimulus is bimodal. To investigate this further, random-dot kinematogram motion sequences were created to simulate segregated (perceptually spatially separated) and transparent (perceptually overlapping) motion. The motion sequences were analysed using the multi-channel gradient model (McGM) to obtain the speed and direction at every pixel of each frame of the motion sequences. The velocity histograms obtained were found to be quantitatively similar and all were bimodal. However, the spatial and temporal properties of the velocity field differed between segregated and transparent stimuli. Transparent stimuli produced patches of rightward and leftward motion that varied in location over time. This demonstrates that we can successfully differentiate between these two types of motion on the basis of the time varying local velocity field. However, the percept of motion transparency cannot be based simply on the presence of a bimodal velocity histogram. PMID:17148338

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

A New Absolute Plate Motion Model for Africa

NASA Astrophysics Data System (ADS)

Maher, S. M.; Wessel, P.; Müller, D.; Harada, Y.

2013-12-01

The India-Eurasia collision, a change in relative plate motion between Australia and Antarctica, and the coeval ages of the Hawaiian Emperor Bend (HEB) and Louisville Bend of ~Chron 22-21 all provide convincing evidence of a global tectonic plate reorganization at ~50 Ma. Yet if it were a truly global event, then there should be a contemporaneous change in Africa absolute plate motion (APM) reflected by physical evidence somewhere on the Africa plate. This evidence might be visible in the Reunion-Mascarene bend, which exhibits many HEB-like features such as a large angular change close to ~50 Ma. Recently, the Reunion hotpot trail has been interpreted as a continental feature with incidental hotspot volcanism. Here we propose the alternative hypothesis that the northern portion of the chain between Saya de Malha and the Seychelles (Mascarene Plateau) formed as the Reunion hotspot was situated on the Carlsberg Ridge, contemporaneously forming the Chagos-Laccadive Ridge on the India plate. We have created a 4-stage model that explores how a simple APM model fitting the Mascarene Plateau can also satisfy the age progressions and geometry of other hotspot trails on the Africa plate. This type of model could explain the apparent bifurcation of the Tristan hotspot chain, the age reversals seen along the Walvis Ridge and the diffuse nature of the St. Helena chain. To test this hypothesis we have made a new African APM model that goes back to ~80 Ma using a modified version of the Hybrid Polygonal Finite Rotation Method. This method uses seamount chains and their associated hotspots as geometric constraints for the model, and seamount age dates to determine its motion through time. The positions of the hotspots can be moved to get the best fit for the model and to explore the possibility that the ~50 Ma bend in the Reunion-Mascarene chain reflects Africa plate motion. We will examine how well this model can predict the key features reflecting Africa plate motion and

Modelling the effect of race surface and racehorse limb parameters on in silico fetlock motion and propensity for injury.

PubMed

Symons, J E; Hawkins, D A; Fyhrie, D P; Upadhyaya, S K; Stover, S M

2017-09-01

The metacarpophalangeal joint (fetlock) is the most commonly affected site of racehorse injury, with multiple observed pathologies consistent with extreme fetlock dorsiflexion. Race surface mechanics affect musculoskeletal structure loading and injury risk because surface forces applied to the hoof affect limb motions. Race surface mechanics are a function of controllable factors. Thus, race surface design has the potential to reduce the incidence of musculoskeletal injury through modulation of limb motions. However, the relationship between race surface mechanics and racehorse limb motions is unknown. To determine the effect of changing race surface and racehorse limb model parameters on distal limb motions. Sensitivity analysis of in silico fetlock motion to changes in race surface and racehorse limb parameters using a validated, integrated racehorse and race surface computational model. Fetlock motions were determined during gallop stance from simulations on virtual surfaces with differing average vertical stiffness, upper layer (e.g. cushion) depth and linear stiffness, horizontal friction, tendon and ligament mechanics, as well as fetlock position at heel strike. Upper layer depth produced the greatest change in fetlock motion, with lesser depths yielding greater fetlock dorsiflexion. Lesser fetlock changes were observed for changes in lower layer (e.g. base or pad) mechanics (nonlinear), as well as palmar ligament and tendon stiffness. Horizontal friction and fetlock position contributed less than 1° change in fetlock motion. Simulated fetlock motions are specific to one horse's anatomy reflected in the computational model. Anatomical differences among horses may affect the magnitude of limb flexion, but will likely have similar limb motion responses to varied surface mechanics. Race surface parameters affected by maintenance produced greater changes in fetlock motion than other parameters studied. Simulations can provide evidence to inform race surface

Students' Mathematical Modeling of Motion

ERIC Educational Resources Information Center

Marshall, Jill A.; Carrejo, David J.

2008-01-01

We present results of an investigation of university students' development of mathematical models of motion in a physical science course for preservice teachers and graduate students in science and mathematics education. Although some students were familiar with the standard concepts of position, velocity, and acceleration from physics classes,…

Moving vehicles segmentation based on Gaussian motion model

NASA Astrophysics Data System (ADS)

Zhang, Wei; Fang, Xiang Z.; Lin, Wei Y.

2005-07-01

Moving objects segmentation is a challenge in computer vision. This paper focuses on the segmentation of moving vehicles in dynamic scene. We analyses the psychology of human vision and present a framework for segmenting moving vehicles in the highway. The proposed framework consists of two parts. Firstly, we propose an adaptive background update method in which the background is updated according to the change of illumination conditions and thus can adapt to the change of illumination sensitively. Secondly, we construct a Gaussian motion model to segment moving vehicles, in which the motion vectors of the moving pixels are modeled as a Gaussian model and an on-line EM algorithm is used to update the model. The Gaussian distribution of the adaptive model is elevated to determine which moving vectors result from moving vehicles and which from other moving objects such as waving trees. Finally, the pixels with motion vector result from the moving vehicles are segmented. Experimental results of several typical scenes show that the proposed model can detect the moving vehicles correctly and is immune from influence of the moving objects caused by the waving trees and the vibration of camera.

Neural dynamics of motion processing and speed discrimination.

PubMed

Chey, J; Grossberg, S; Mingolla, E

1998-09-01

A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-turned cell responses. These mechanisms use transient cell responses to moving stimuli, output thresholds that covary with filter size, and competition. These mechanisms are proposed to occur in the V1-->MT cortical processing stream. The model reproduces empirically derived speed discrimination curves and simulates data showing how visual speed perception and discrimination can be affected by stimulus contrast, duration, dot density and spatial frequency. Model motion mechanisms are analogous to mechanisms that have been used to model 3-D form and figure-ground perception. The model forms the front end of a larger motion processing system that has been used to simulate how global motion capture occurs, and how spatial attention is drawn to moving forms. It provides a computational foundation for an emerging neural theory of 3-D form and motion perception.

Classifying multiple types of hand motions using electrocorticography during intraoperative awake craniotomy and seizure monitoring processes—case studies

PubMed Central

Xie, Tao; Zhang, Dingguo; Wu, Zehan; Chen, Liang; Zhu, Xiangyang

2015-01-01

In this work, some case studies were conducted to classify several kinds of hand motions from electrocorticography (ECoG) signals during intraoperative awake craniotomy & extraoperative seizure monitoring processes. Four subjects (P1, P2 with intractable epilepsy during seizure monitoring and P3, P4 with brain tumor during awake craniotomy) participated in the experiments. Subjects performed three types of hand motions (Grasp, Thumb-finger motion and Index-finger motion) contralateral to the motor cortex covered with ECoG electrodes. Two methods were used for signal processing. Method I: autoregressive (AR) model with burg method was applied to extract features, and additional waveform length (WL) feature has been considered, finally the linear discriminative analysis (LDA) was used as the classifier. Method II: stationary subspace analysis (SSA) was applied for data preprocessing, and the common spatial pattern (CSP) was used for feature extraction before LDA decoding process. Applying method I, the three-class accuracy of P1~P4 were 90.17, 96.00, 91.77, and 92.95% respectively. For method II, the three-class accuracy of P1~P4 were 72.00, 93.17, 95.22, and 90.36% respectively. This study verified the possibility of decoding multiple hand motion types during an awake craniotomy, which is the first step toward dexterous neuroprosthetic control during surgical implantation, in order to verify the optimal placement of electrodes. The accuracy during awake craniotomy was comparable to results during seizure monitoring. This study also indicated that ECoG was a promising approach for precise identification of eloquent cortex during awake craniotomy, and might form a promising BCI system that could benefit both patients and neurosurgeons. PMID:26483627

Evaluating Effectiveness of Modeling Motion System Feedback in the Enhanced Hess Structural Model of the Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill; Cardullo, Frank; George, Gary; Kelly, Lon C.

2009-01-01

In order to use the Hess Structural Model to predict the need for certain cueing systems, George and Cardullo significantly expanded it by adding motion feedback to the model and incorporating models of the motion system dynamics, motion cueing algorithm and a vestibular system. This paper proposes a methodology to evaluate effectiveness of these innovations by performing a comparison analysis of the model performance with and without the expanded motion feedback. The proposed methodology is composed of two stages. The first stage involves fine-tuning parameters of the original Hess structural model in order to match the actual control behavior recorded during the experiments at NASA Visual Motion Simulator (VMS) facility. The parameter tuning procedure utilizes a new automated parameter identification technique, which was developed at the Man-Machine Systems Lab at SUNY Binghamton. In the second stage of the proposed methodology, an expanded motion feedback is added to the structural model. The resulting performance of the model is then compared to that of the original one. As proposed by Hess, metrics to evaluate the performance of the models include comparison against the crossover models standards imposed on the crossover frequency and phase margin of the overall man-machine system. Preliminary results indicate the advantage of having the model of the motion system and motion cueing incorporated into the model of the human operator. It is also demonstrated that the crossover frequency and the phase margin of the expanded model are well within the limits imposed by the crossover model.

Modeling rate sensitivity of exercise transient responses to limb motion.

PubMed

Yamashiro, Stanley M; Kato, Takahide

2014-10-01

Transient responses of ventilation (V̇e) to limb motion can exhibit predictive characteristics. In response to a change in limb motion, a rapid change in V̇e is commonly observed with characteristics different than during a change in workload. This rapid change has been attributed to a feed-forward or adaptive response. Rate sensitivity was explored as a specific hypothesis to explain predictive V̇e responses to limb motion. A simple model assuming an additive feed-forward summation of V̇e proportional to the rate of change of limb motion was studied. This model was able to successfully account for the adaptive phase correction observed during human sinusoidal changes in limb motion. Adaptation of rate sensitivity might also explain the reduction of the fast component of V̇e responses previously reported following sudden exercise termination. Adaptation of the fast component of V̇e response could occur by reduction of rate sensitivity. Rate sensitivity of limb motion was predicted by the model to reduce the phase delay between limb motion and V̇e response without changing the steady-state response to exercise load. In this way, V̇e can respond more quickly to an exercise change without interfering with overall feedback control. The asymmetry between responses to an incremental and decremental ramp change in exercise can also be accounted for by the proposed model. Rate sensitivity leads to predicted behavior, which resembles responses observed in exercise tied to expiratory reserve volume. Copyright © 2014 the American Physiological Society.

The proximal-to-distal sequence in upper-limb motions on multiple levels and time scales.

PubMed

Serrien, Ben; Baeyens, Jean-Pierre

2017-10-01

The proximal-to-distal sequence is a phenomenon that can be observed in a large variety of motions of the upper limbs in both humans and other mammals. The mechanisms behind this sequence are not completely understood and motor control theories able to explain this phenomenon are currently incomplete. The aim of this narrative review is to take a theoretical constraints-led approach to the proximal-to-distal sequence and provide a broad multidisciplinary overview of relevant literature. This sequence exists at multiple levels (brain, spine, muscles, kinetics and kinematics) and on multiple time scales (motion, motor learning and development, growth and possibly even evolution). We hypothesize that the proximodistal spatiotemporal direction on each time scale and level provides part of the organismic constraints that guide the dynamics at the other levels and time scales. The constraint-led approach in this review may serve as a first onset towards integration of evidence and a framework for further experimentation to reveal the dynamics of the proximal-to-distal sequence. Copyright © 2017 Elsevier B.V. All rights reserved.

A Bayesian model of stereopsis depth and motion direction discrimination.

PubMed

Read, J C A

2002-02-01

The extraction of stereoscopic depth from retinal disparity, and motion direction from two-frame kinematograms, requires the solution of a correspondence problem. In previous psychophysical work [Read and Eagle (2000) Vision Res 40: 3345-3358], we compared the performance of the human stereopsis and motion systems with correlated and anti-correlated stimuli. We found that, although the two systems performed similarly for narrow-band stimuli, broadband anti-correlated kinematograms produced a strong perception of reversed motion, whereas the stereograms appeared merely rivalrous. I now model these psychophysical data with a computational model of the correspondence problem based on the known properties of visual cortical cells. Noisy retinal images are filtered through a set of Fourier channels tuned to different spatial frequencies and orientations. Within each channel, a Bayesian analysis incorporating a prior preference for small disparities is used to assess the probability of each possible match. Finally, information from the different channels is combined to arrive at a judgement of stimulus disparity. Each model system--stereopsis and motion--has two free parameters: the amount of noise they are subject to, and the strength of their preference for small disparities. By adjusting these parameters independently for each system, qualitative matches are produced to psychophysical data, for both correlated and anti-correlated stimuli, across a range of spatial frequency and orientation bandwidths. The motion model is found to require much higher noise levels and a weaker preference for small disparities. This makes the motion model more tolerant of poor-quality reverse-direction false matches encountered with anti-correlated stimuli, matching the strong perception of reversed motion that humans experience with these stimuli. In contrast, the lower noise level and tighter prior preference used with the stereopsis model means that it performs close to chance with

Wave drift damping acting on multiple circular cylinders (model tests)

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

Kinoshita, Takeshi; Sunahara, Shunji; Bao, W.

1995-12-31

The wave drift damping for the slow drift motion of a four-column platform is experimentally investigated. The estimation of damping force of the slow drift motion of moored floating structures in ocean waves, is one of the most important topics. Bao et al. calculated an interaction of multiple circular cylinders based on the potential flow theory, and showed that the wave drift damping is significantly influenced by the interaction between cylinders. This calculation method assumes that the slow drift motion is approximately replaced by steady current, that is, structures on slow drift motion are supposed to be equivalent to onesmore » in both regular waves and slow current. To validate semi-analytical solutions of Bao et al., experiments were carried out. At first, added resistance due to waves acting on a structure composed of multiple (four) vertical circular cylinders fixed to a slowly moving carriage, was measured in regular waves. Next, the added resistance of the structure moored by linear spring to the slowly moving carriage were measured in regular waves. Furthermore, to validate the assumption that the slow drift motion is replaced by steady current, free decay tests in still water and in regular waves were compared with the simulation of the slow drift motion using the wave drift damping coefficient obtained by the added resistance tests.« less

Grouping and trajectory storage in multiple object tracking: impairments due to common item motions.

PubMed

Suganuma, Mutsumi; Yokosawa, Kazuhiko

2006-01-01

In our natural viewing, we notice that objects change their locations across space and time. However, there has been relatively little consideration of the role of motion information in the construction and maintenance of object representations. We investigated this question in the context of the multiple object tracking (MOT) paradigm, wherein observers must keep track of target objects as they move randomly amid featurally identical distractors. In three experiments, we observed impairments in tracking ability when the motions of the target and distractor items shared particular properties. Specifically, we observed impairments when the target and distractor items were in a chasing relationship or moved in a uniform direction. Surprisingly, tracking ability was impaired by these manipulations even when observers failed to notice them. Our results suggest that differentiable trajectory information is an important factor in successful performance of MOT tasks. More generally, these results suggest that various types of common motion can serve as cues to form more global object representations even in the absence of other grouping cues.

A high and low noise model for strong motion accelerometers

NASA Astrophysics Data System (ADS)

Clinton, J. F.; Cauzzi, C.; Olivieri, M.

2010-12-01

We present reference noise models for high-quality strong motion accelerometer installations. We use continuous accelerometer data acquired by the Swiss Seismological Service (SED) since 2006 and other international high-quality accelerometer network data to derive very broadband (50Hz-100s) high and low noise models. The proposed noise models are compared to the Peterson (1993) low and high noise models designed for broadband seismometers; the datalogger self-noise; background noise levels at existing Swiss strong motion stations; and typical earthquake signals recorded in Switzerland and worldwide. The standard strong motion station operated by the SED consists of a Kinemetrics Episensor (2g clip level; flat acceleration response from 200 Hz to DC; <155dB dynamic range) coupled with a 24-bit Nanometrics Taurus datalogger. The proposed noise models are based on power spectral density (PSD) noise levels for each strong motion station computed via PQLX (McNamara and Buland, 2004) from several years of continuous recording. The 'Accelerometer Low Noise Model', ALNM, is dominated by instrument noise from the sensor and datalogger. The 'Accelerometer High Noise Model', AHNM, reflects 1) at high frequencies the acceptable site noise in urban areas, 2) at mid-periods the peak microseismal energy, as determined by the Peterson High Noise Model and 3) at long periods the maximum noise observed from well insulated sensor / datalogger systems placed in vault quality sites. At all frequencies, there is at least one order of magnitude between the ALNM and the AHNM; at high frequencies (> 1Hz) this extends to 2 orders of magnitude. This study provides remarkable confirmation of the capability of modern strong motion accelerometers to record low-amplitude ground motions with seismic observation quality. In particular, an accelerometric station operating at the ALNM is capable of recording the full spectrum of near source earthquakes, out to 100 km, down to M2. Of particular

Lung tumor motion prediction during lung brachytherapy using finite element model

NASA Astrophysics Data System (ADS)

Shirzadi, Zahra; Sadeghi Naini, Ali; Samani, Abbas

2012-02-01

A biomechanical model is proposed to predict deflated lung tumor motion caused by diaphragm respiratory motion. This model can be very useful for targeting the tumor in tumor ablative procedures such as lung brachytherapy. To minimize motion within the target lung, these procedures are performed while the lung is deflated. However, significant amount of tissue deformation still occurs during respiration due to the diaphragm contact forces. In the absence of effective realtime image guidance, biomechanical models can be used to estimate tumor motion as a function of diaphragm's position. To develop this model, Finite Element Method (FEM) was employed. To demonstrate the concept, we conducted an animal study of an ex-vivo porcine deflated lung with a tumor phantom. The lung was deformed by compressing a diaphragm mimicking cylinder against it. Before compression, 3D-CT image of this lung was acquired, which was segmented and turned into FE mesh. The lung tissue was modeled as hyperelastic material with a contact loading to calculate the lung deformation and tumor motion during respiration. To validate the results from FE model, the motion of a small area on the surface close to the tumor was tracked while the lung was being loaded by the cylinder. Good agreement was demonstrated between the experiment results and simulation results. Furthermore, the impact of tissue hyperelastic parameters uncertainties in the FE model was investigated. For this purpose, we performed in-silico simulations with different hyperelastic parameters. This study demonstrated that the FEM was accurate and robust for tumor motion prediction.

A model describing vestibular detection of body sway motion.

NASA Technical Reports Server (NTRS)

Nashner, L. M.

1971-01-01

An experimental technique was developed which facilitated the formulation of a quantitative model describing vestibular detection of body sway motion in a postural response mode. All cues, except vestibular ones, which gave a subject an indication that he was beginning to sway, were eliminated using a specially designed two-degree-of-freedom platform; body sway was then induced and resulting compensatory responses at the ankle joints measured. Hybrid simulation compared the experimental results with models of the semicircular canals and utricular otolith receptors. Dynamic characteristics of the resulting canal model compared closely with characteristics of models which describe eye movement and subjective responses to body rotational motions. The average threshold level, in the postural response mode, however, was considerably lower. Analysis indicated that the otoliths probably play no role in the initial detection of body sway motion.

Stochastic point-source modeling of ground motions in the Cascadia region

USGS Publications Warehouse

Atkinson, G.M.; Boore, D.M.

1997-01-01

A stochastic model is used to develop preliminary ground motion relations for the Cascadia region for rock sites. The model parameters are derived from empirical analyses of seismographic data from the Cascadia region. The model is based on a Brune point-source characterized by a stress parameter of 50 bars. The model predictions are compared to ground-motion data from the Cascadia region and to data from large earthquakes in other subduction zones. The point-source simulations match the observations from moderate events (M 100 km). The discrepancy at large magnitudes suggests further work on modeling finite-fault effects and regional attenuation is warranted. In the meantime, the preliminary equations are satisfactory for predicting motions from events of M < 7 and provide conservative estimates of motions from larger events at distances less than 100 km.

Model Predictive Control Based Motion Drive Algorithm for a Driving Simulator

NASA Astrophysics Data System (ADS)

Rehmatullah, Faizan

In this research, we develop a model predictive control based motion drive algorithm for the driving simulator at Toronto Rehabilitation Institute. Motion drive algorithms exploit the limitations of the human vestibular system to formulate a perception of motion within the constrained workspace of a simulator. In the absence of visual cues, the human perception system is unable to distinguish between acceleration and the force of gravity. The motion drive algorithm determines control inputs to displace the simulator platform, and by using the resulting inertial forces and angular rates, creates the perception of motion. By using model predictive control, we can optimize the use of simulator workspace for every maneuver while simulating the vehicle perception. With the ability to handle nonlinear constraints, the model predictive control allows us to incorporate workspace limitations.

Whole-Motion Model of Perception during Forward- and Backward-Facing Centrifuge Runs

PubMed Central

Holly, Jan E.; Vrublevskis, Arturs; Carlson, Lindsay E.

2009-01-01

Illusory perceptions of motion and orientation arise during human centrifuge runs without vision. Asymmetries have been found between acceleration and deceleration, and between forward-facing and backward-facing runs. Perceived roll tilt has been studied extensively during upright fixed-carriage centrifuge runs, and other components have been studied to a lesser extent. Certain, but not all, perceptual asymmetries in acceleration-vs-deceleration and forward-vs-backward motion can be explained by existing analyses. The immediate acceleration-deceleration roll-tilt asymmetry can be explained by the three-dimensional physics of the external stimulus; in addition, longer-term data has been modeled in a standard way using physiological time constants. However, the standard modeling approach is shown in the present research to predict forward-vs-backward-facing symmetry in perceived roll tilt, contradicting experimental data, and to predict perceived sideways motion, rather than forward or backward motion, around a curve. The present work develops a different whole-motion-based model taking into account the three-dimensional form of perceived motion and orientation. This model predicts perceived forward or backward motion around a curve, and predicts additional asymmetries such as the forward-backward difference in roll tilt. This model is based upon many of the same principles as the standard model, but includes an additional concept of familiarity of motions as a whole. PMID:19208962

Dense motion estimation using regularization constraints on local parametric models.

PubMed

Patras, Ioannis; Worring, Marcel; van den Boomgaard, Rein

2004-11-01

This paper presents a method for dense optical flow estimation in which the motion field within patches that result from an initial intensity segmentation is parametrized with models of different order. We propose a novel formulation which introduces regularization constraints between the model parameters of neighboring patches. In this way, we provide the additional constraints for very small patches and for patches whose intensity variation cannot sufficiently constrain the estimation of their motion parameters. In order to preserve motion discontinuities, we use robust functions as a regularization mean. We adopt a three-frame approach and control the balance between the backward and forward constraints by a real-valued direction field on which regularization constraints are applied. An iterative deterministic relaxation method is employed in order to solve the corresponding optimization problem. Experimental results show that the proposed method deals successfully with motions large in magnitude, motion discontinuities, and produces accurate piecewise-smooth motion fields.

Cervical spine motion in manual versus Jackson table turning methods in a cadaveric global instability model.

PubMed

DiPaola, Matthew J; DiPaola, Christian P; Conrad, Bryan P; Horodyski, MaryBeth; Del Rossi, Gianluca; Sawers, Andrew; Bloch, David; Rechtine, Glenn R

2008-06-01

A study of spine biomechanics in a cadaver model. To quantify motion in multiple axes created by transfer methods from stretcher to operating table in the prone position in a cervical global instability model. Patients with an unstable cervical spine remain at high risk for further secondary injury until their spine is adequately surgically stabilized. Previous studies have revealed that collars have significant, but limited benefit in preventing cervical motion when manually transferring patients. The literature proposes multiple methods of patient transfer, although no one method has been universally adopted. To date, no study has effectively evaluated the relationship between spine motion and various patient transfer methods to an operating room table for prone positioning. A global instability was surgically created at C5-6 in 4 fresh cadavers with no history of spine pathology. All cadavers were tested both with and without a rigid cervical collar in the intact and unstable state. Three headrest permutations were evaluated Mayfield (SM USA Inc), Prone View (Dupaco, Oceanside, CA), and Foam Pillow (OSI, Union City, CA). A trained group of medical staff performed each of 2 transfer methods: the "manual" and the "Jackson table" transfer. The manual technique entailed performing a standard rotation of the supine patient on a stretcher to the prone position on the operating room table with in-line manual cervical stabilization. The "Jackson" technique involved sliding the supine patient to the Jackson table (OSI, Union City, CA) with manual in-line cervical stabilization, securing them to the table, then initiating the table's lock and turn mechanism and rotating them into a prone position. An electromagnetic tracking device captured angular motion between the C5 and C6 vertebral segments. Repeated measures statistical analysis was performed to evaluate the following conditions: collar use (2 levels), headrest (3 levels), and turning technique (2 levels). For all

Assessing the Validity of Multiple-Choice Questions in Measuring Fourth Graders' Ability to Interpret Graphs about Motion and Temperature

ERIC Educational Resources Information Center

Dulger, Mehmet; Deniz, Hasan

2017-01-01

The purpose of this paper is to assess the validity of multiple-choice questions in measuring fourth grade students' ability to interpret graphs related to physical science topics such as motion and temperature. We administered a test including 6 multiple-choice questions to 28 fourth grade students. Students were asked to explain their thinking…

Mathematical modelling of animate and intentional motion.

PubMed Central

Rittscher, Jens; Blake, Andrew; Hoogs, Anthony; Stein, Gees

2003-01-01

Our aim is to enable a machine to observe and interpret the behaviour of others. Mathematical models are employed to describe certain biological motions. The main challenge is to design models that are both tractable and meaningful. In the first part we will describe how computer vision techniques, in particular visual tracking, can be applied to recognize a small vocabulary of human actions in a constrained scenario. Mainly the problems of viewpoint and scale invariance need to be overcome to formalize a general framework. Hence the second part of the article is devoted to the question whether a particular human action should be captured in a single complex model or whether it is more promising to make extensive use of semantic knowledge and a collection of low-level models that encode certain motion primitives. Scene context plays a crucial role if we intend to give a higher-level interpretation rather than a low-level physical description of the observed motion. A semantic knowledge base is used to establish the scene context. This approach consists of three main components: visual analysis, the mapping from vision to language and the search of the semantic database. A small number of robust visual detectors is used to generate a higher-level description of the scene. The approach together with a number of results is presented in the third part of this article. PMID:12689374

Modelling motions within the organ of Corti

NASA Astrophysics Data System (ADS)

Ni, Guangjian; Baumgart, Johannes; Elliott, Stephen

2015-12-01

Most cochlear models used to describe the basilar membrane vibration along the cochlea are concerned with macromechanics, and often assume that the organ of Corti moves as a single unit, ignoring the individual motion of different components. New experimental technologies provide the opportunity to measure the dynamic behaviour of different components within the organ of Corti, but only for certain types of excitation. It is thus still difficult to directly measure every aspect of cochlear dynamics, particularly for acoustic excitation of the fully active cochlea. The present work studies the dynamic response of a model of the cross-section of the cochlea, at the microscopic level, using the finite element method. The elastic components are modelled with plate elements and the perilymph and endolymph are modelled with inviscid fluid elements. The individual motion of each component within the organ of Corti is calculated with dynamic pressure loading on the basilar membrane and the motions of the experimentally accessible parts are compared with measurements. The reticular lamina moves as a stiff plate, without much bending, and is pivoting around a point close to the region of the inner hair cells, as observed experimentally. The basilar membrane shows a slightly asymmetric mode shape, with maximum displacement occurring between the second-row and the third-row of the outer hair cells. The dynamics responses is also calculated, and compared with experiments, when driven by the outer hair cells. The receptance of the basilar membrane motion and of the deflection of the hair bundles of the outer hair cells is thus obtained, when driven either acoustically or electrically. In this way, the fully active linear response of the basilar membrane to acoustic excitation can be predicted by using a linear superposition of the calculated receptances and a defined gain function for the outer hair cell feedback.

Nonlinear dynamic modeling of a simple flexible rotor system subjected to time-variable base motions

NASA Astrophysics Data System (ADS)

Chen, Liqiang; Wang, Jianjun; Han, Qinkai; Chu, Fulei

2017-09-01

Rotor systems carried in transportation system or under seismic excitations are considered to have a moving base. To study the dynamic behavior of flexible rotor systems subjected to time-variable base motions, a general model is developed based on finite element method and Lagrange's equation. Two groups of Euler angles are defined to describe the rotation of the rotor with respect to the base and that of the base with respect to the ground. It is found that the base rotations would cause nonlinearities in the model. To verify the proposed model, a novel test rig which could simulate the base angular-movement is designed. Dynamic experiments on a flexible rotor-bearing system with base angular motions are carried out. Based upon these, numerical simulations are conducted to further study the dynamic response of the flexible rotor under harmonic angular base motions. The effects of base angular amplitude, rotating speed and base frequency on response behaviors are discussed by means of FFT, waterfall, frequency response curve and orbits of the rotor. The FFT and waterfall plots of the disk horizontal and vertical vibrations are marked with multiplications of the base frequency and sum and difference tones of the rotating frequency and the base frequency. Their amplitudes will increase remarkably when they meet the whirling frequencies of the rotor system.

Hydrological excitation of polar motion by different variables of the GLDAS models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.

Neural network-based motion control of an underactuated wheeled inverted pendulum model.

PubMed

Yang, Chenguang; Li, Zhijun; Cui, Rongxin; Xu, Bugong

2014-11-01

In this paper, automatic motion control is investigated for one of wheeled inverted pendulum (WIP) models, which have been widely applied for modeling of a large range of two wheeled modern vehicles. First, the underactuated WIP model is decomposed into a fully actuated second order subsystem Σa consisting of planar movement of vehicle forward and yaw angular motions, and a nonactuated first order subsystem Σb of pendulum motion. Due to the unknown dynamics of subsystem Σa and the universal approximation ability of neural network (NN), an adaptive NN scheme has been employed for motion control of subsystem Σa . The model reference approach has been used whereas the reference model is optimized by the finite time linear quadratic regulation technique. The pendulum motion in the passive subsystem Σb is indirectly controlled using the dynamic coupling with planar forward motion of subsystem Σa , such that satisfactory tracking of a set pendulum tilt angle can be guaranteed. Rigours theoretic analysis has been established, and simulation studies have been performed to demonstrate the developed method.

Detecting abandoned objects using interacting multiple models

NASA Astrophysics Data System (ADS)

Becker, Stefan; Münch, David; Kieritz, Hilke; Hübner, Wolfgang; Arens, Michael

2015-10-01

In recent years, the wide use of video surveillance systems has caused an enormous increase in the amount of data that has to be stored, monitored, and processed. As a consequence, it is crucial to support human operators with automated surveillance applications. Towards this end an intelligent video analysis module for real-time alerting in case of abandoned objects in public spaces is proposed. The overall processing pipeline consists of two major parts. First, person motion is modeled using an Interacting Multiple Model (IMM) filter. The IMM filter estimates the state of a person according to a finite-state, discrete-time Markov chain. Second, the location of persons that stay at a fixed position defines a region of interest, in which a nonparametric background model with dynamic per-pixel state variables identifies abandoned objects. In case of a detected abandoned object, an alarm event is triggered. The effectiveness of the proposed system is evaluated on the PETS 2006 dataset and the i-Lids dataset, both reflecting prototypical surveillance scenarios.

Research on motion model for the hypersonic boost-glide aircraft

NASA Astrophysics Data System (ADS)

Xu, Shenda; Wu, Jing; Wang, Xueying

2015-11-01

A motion model for the hypersonic boost-glide aircraft(HBG) was proposed in this paper, which also analyzed the precision of model through simulation. Firstly the trajectory of HBG was analyzed, and a scheme which divide the trajectory into two parts then build the motion model on each part. Secondly a restrained model of boosting stage and a restrained model of J2 perturbation were established, and set up the observe model. Finally the analysis of simulation results show the feasible and high-accuracy of the model, and raise a expectation for intensive research.

Multiple object, three-dimensional motion tracking using the Xbox Kinect sensor

NASA Astrophysics Data System (ADS)

Rosi, T.; Onorato, P.; Oss, S.

2017-11-01

In this article we discuss the capability of the Xbox Kinect sensor to acquire three-dimensional motion data of multiple objects. Two experiments regarding fundamental features of Newtonian mechanics are performed to test the tracking abilities of our setup. Particular attention is paid to check and visualise the conservation of linear momentum, angular momentum and energy. In both experiments, two objects are tracked while falling in the gravitational field. The obtained data is visualised in a 3D virtual environment to help students understand the physics behind the performed experiments. The proposed experiments were analysed with a group of university students who are aspirant physics and mathematics teachers. Their comments are presented in this paper.

Moving object detection using dynamic motion modelling from UAV aerial images.

PubMed

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

The use of vestibular models for design and evaluation of flight simulator motion

NASA Technical Reports Server (NTRS)

Bussolari, Steven R.; Young, Laurence R.; Lee, Alfred T.

1989-01-01

Quantitative models for the dynamics of the human vestibular system are applied to the design and evaluation of flight simulator platform motion. An optimal simulator motion control algorithm is generated to minimize the vector difference between perceived spatial orientation estimated in flight and in simulation. The motion controller has been implemented on the Vertical Motion Simulator at NASA Ames Research Center and evaluated experimentally through measurement of pilot performance and subjective rating during VTOL aircraft simulation. In general, pilot performance in a longitudinal tracking task (formation flight) did not appear to be sensitive to variations in platform motion condition as long as motion was present. However, pilot assessment of motion fidelity by means of a rating scale designed for this purpose, were sensitive to motion controller design. Platform motion generated with the optimal motion controller was found to be generally equivalent to that generated by conventional linear crossfeed washout. The vestibular models are used to evaluate the motion fidelity of transport category aircraft (Boeing 727) simulation in a pilot performance and simulator acceptability study at the Man-Vehicle Systems Research Facility at NASA Ames Research Center. Eighteen airline pilots, currently flying B-727, were given a series of flight scenarios in the simulator under various conditions of simulator motion. The scenarios were chosen to reflect the flight maneuvers that these pilots might expect to be given during a routine pilot proficiency check. Pilot performance and subjective rating of simulator fidelity was relatively insensitive to the motion condition, despite large differences in the amplitude of motion provided. This lack of sensitivity may be explained by means of the vestibular models, which predict little difference in the modeled motion sensations of the pilots when different motion conditions are imposed.

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.

Elements of an improved model of debris‐flow motion

USGS Publications Warehouse

Iverson, Richard M.

2009-01-01

A new depth‐averaged model of debris‐flow motion describes simultaneous evolution of flow velocity and depth, solid and fluid volume fractions, and pore‐fluid pressure. Non‐hydrostatic pore‐fluid pressure is produced by dilatancy, a state‐dependent property that links the depth‐averaged shear rate and volumetric strain rate of the granular phase. Pore‐pressure changes caused by shearing allow the model to exhibit rate‐dependent flow resistance, despite the fact that the basal shear traction involves only rate‐independent Coulomb friction. An analytical solution of simplified model equations shows that the onset of downslope motion can be accelerated or retarded by pore‐pressure change, contingent on whether dilatancy is positive or negative. A different analytical solution shows that such effects will likely be muted if downslope motion continues long enough, because dilatancy then evolves toward zero, and volume fractions and pore pressure concurrently evolve toward steady states.

Object Segmentation from Motion Discontinuities and Temporal Occlusions–A Biologically Inspired Model

PubMed Central

Beck, Cornelia; Ognibeni, Thilo; Neumann, Heiko

2008-01-01

Background Optic flow is an important cue for object detection. Humans are able to perceive objects in a scene using only kinetic boundaries, and can perform the task even when other shape cues are not provided. These kinetic boundaries are characterized by the presence of motion discontinuities in a local neighbourhood. In addition, temporal occlusions appear along the boundaries as the object in front covers the background and the objects that are spatially behind it. Methodology/Principal Findings From a technical point of view, the detection of motion boundaries for segmentation based on optic flow is a difficult task. This is due to the problem that flow detected along such boundaries is generally not reliable. We propose a model derived from mechanisms found in visual areas V1, MT, and MSTl of human and primate cortex that achieves robust detection along motion boundaries. It includes two separate mechanisms for both the detection of motion discontinuities and of occlusion regions based on how neurons respond to spatial and temporal contrast, respectively. The mechanisms are embedded in a biologically inspired architecture that integrates information of different model components of the visual processing due to feedback connections. In particular, mutual interactions between the detection of motion discontinuities and temporal occlusions allow a considerable improvement of the kinetic boundary detection. Conclusions/Significance A new model is proposed that uses optic flow cues to detect motion discontinuities and object occlusion. We suggest that by combining these results for motion discontinuities and object occlusion, object segmentation within the model can be improved. This idea could also be applied in other models for object segmentation. In addition, we discuss how this model is related to neurophysiological findings. The model was successfully tested both with artificial and real sequences including self and object motion. PMID:19043613

Hamilton-Jacobi modelling of relative motion for formation flying.

PubMed

Kolemen, Egemen; Kasdin, N Jeremy; Gurfil, Pini

2005-12-01

A precise analytic model for the relative motion of a group of satellites in slightly elliptic orbits is introduced. With this aim, we describe the relative motion of an object relative to a circular or slightly elliptic reference orbit in the rotating Hill frame via a low-order Hamiltonian, and solve the Hamilton-Jacobi equation. This results in a first-order solution to the relative motion identical to the Clohessy-Wiltshire approach; here, however, rather than using initial conditions as our constants of the motion, we utilize the canonical momenta and coordinates. This allows us to treat perturbations in an identical manner, as in the classical Delaunay formulation of the two-body problem. A precise analytical model for the base orbit is chosen with the included effect of zonal harmonics (J(2), J(3), J(4)). A Hamiltonian describing the real relative motion is formed and by differing this from the nominal Hamiltonian, the perturbing Hamiltonian is obtained. Using the Hamilton equations, the variational equations for the new constants are found. In a manner analogous to the center manifold reduction procedure, the non-periodic part of the motion is canceled through a magnitude analysis leading to simple boundedness conditions that cancel the drift terms due to the higher order perturbations. Using this condition, the variational equations are integrated to give periodic solutions that closely approximate the results from numerical integration (1 mm/per orbit for higher order and eccentricity perturbations and 30 cm/per orbit for zonal perturbations). This procedure provides a compact and insightful analytic description of the resulting relative motion.

Embodied learning of a generative neural model for biological motion perception and inference

PubMed Central

Schrodt, Fabian; Layher, Georg; Neumann, Heiko; Butz, Martin V.

2015-01-01

Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons. PMID:26217215

Embodied learning of a generative neural model for biological motion perception and inference.

PubMed

Schrodt, Fabian; Layher, Georg; Neumann, Heiko; Butz, Martin V

2015-01-01

Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons.

Segmenting Continuous Motions with Hidden Semi-markov Models and Gaussian Processes

PubMed Central

Nakamura, Tomoaki; Nagai, Takayuki; Mochihashi, Daichi; Kobayashi, Ichiro; Asoh, Hideki; Kaneko, Masahide

2017-01-01

Humans divide perceived continuous information into segments to facilitate recognition. For example, humans can segment speech waves into recognizable morphemes. Analogously, continuous motions are segmented into recognizable unit actions. People can divide continuous information into segments without using explicit segment points. This capacity for unsupervised segmentation is also useful for robots, because it enables them to flexibly learn languages, gestures, and actions. In this paper, we propose a Gaussian process-hidden semi-Markov model (GP-HSMM) that can divide continuous time series data into segments in an unsupervised manner. Our proposed method consists of a generative model based on the hidden semi-Markov model (HSMM), the emission distributions of which are Gaussian processes (GPs). Continuous time series data is generated by connecting segments generated by the GP. Segmentation can be achieved by using forward filtering-backward sampling to estimate the model's parameters, including the lengths and classes of the segments. In an experiment using the CMU motion capture dataset, we tested GP-HSMM with motion capture data containing simple exercise motions; the results of this experiment showed that the proposed GP-HSMM was comparable with other methods. We also conducted an experiment using karate motion capture data, which is more complex than exercise motion capture data; in this experiment, the segmentation accuracy of GP-HSMM was 0.92, which outperformed other methods. PMID:29311889

A multiple-shape memory polymer-metal composite actuator capable of programmable control, creating complex 3D motion of bending, twisting, and oscillation

NASA Astrophysics Data System (ADS)

Shen, Qi; Trabia, Sarah; Stalbaum, Tyler; Palmre, Viljar; Kim, Kwang; Oh, Il-Kwon

2016-04-01

Development of biomimetic actuators has been an essential motivation in the study of smart materials. However, few materials are capable of controlling complex twisting and bending deformations simultaneously or separately using a dynamic control system. Here, we report an ionic polymer-metal composite actuator having multiple-shape memory effect, and is able to perform complex motion by two external inputs, electrical and thermal. Prior to the development of this type of actuator, this capability only could be realized with existing actuator technologies by using multiple actuators or another robotic system. This paper introduces a soft multiple-shape-memory polymer-metal composite (MSMPMC) actuator having multiple degrees-of-freedom that demonstrates high maneuverability when controlled by two external inputs, electrical and thermal. These multiple inputs allow for complex motions that are routine in nature, but that would be otherwise difficult to obtain with a single actuator. To the best of the authors’ knowledge, this MSMPMC actuator is the first solitary actuator capable of multiple-input control and the resulting deformability and maneuverability.

A multiple-shape memory polymer-metal composite actuator capable of programmable control, creating complex 3D motion of bending, twisting, and oscillation

PubMed Central

Shen, Qi; Trabia, Sarah; Stalbaum, Tyler; Palmre, Viljar; Kim, Kwang; Oh, Il-Kwon

2016-01-01

Development of biomimetic actuators has been an essential motivation in the study of smart materials. However, few materials are capable of controlling complex twisting and bending deformations simultaneously or separately using a dynamic control system. Here, we report an ionic polymer-metal composite actuator having multiple-shape memory effect, and is able to perform complex motion by two external inputs, electrical and thermal. Prior to the development of this type of actuator, this capability only could be realized with existing actuator technologies by using multiple actuators or another robotic system. This paper introduces a soft multiple-shape-memory polymer-metal composite (MSMPMC) actuator having multiple degrees-of-freedom that demonstrates high maneuverability when controlled by two external inputs, electrical and thermal. These multiple inputs allow for complex motions that are routine in nature, but that would be otherwise difficult to obtain with a single actuator. To the best of the authors’ knowledge, this MSMPMC actuator is the first solitary actuator capable of multiple-input control and the resulting deformability and maneuverability. PMID:27080134

A multiple-shape memory polymer-metal composite actuator capable of programmable control, creating complex 3D motion of bending, twisting, and oscillation.

PubMed

Shen, Qi; Trabia, Sarah; Stalbaum, Tyler; Palmre, Viljar; Kim, Kwang; Oh, Il-Kwon

2016-04-15

Development of biomimetic actuators has been an essential motivation in the study of smart materials. However, few materials are capable of controlling complex twisting and bending deformations simultaneously or separately using a dynamic control system. Here, we report an ionic polymer-metal composite actuator having multiple-shape memory effect, and is able to perform complex motion by two external inputs, electrical and thermal. Prior to the development of this type of actuator, this capability only could be realized with existing actuator technologies by using multiple actuators or another robotic system. This paper introduces a soft multiple-shape-memory polymer-metal composite (MSMPMC) actuator having multiple degrees-of-freedom that demonstrates high maneuverability when controlled by two external inputs, electrical and thermal. These multiple inputs allow for complex motions that are routine in nature, but that would be otherwise difficult to obtain with a single actuator. To the best of the authors' knowledge, this MSMPMC actuator is the first solitary actuator capable of multiple-input control and the resulting deformability and maneuverability.

Toward a computational theory for motion understanding: The expert animators model

NASA Technical Reports Server (NTRS)

Mohamed, Ahmed S.; Armstrong, William W.

1988-01-01

Artificial intelligence researchers claim to understand some aspect of human intelligence when their model is able to emulate it. In the context of computer graphics, the ability to go from motion representation to convincing animation should accordingly be treated not simply as a trick for computer graphics programmers but as important epistemological and methodological goal. In this paper we investigate a unifying model for animating a group of articulated bodies such as humans and robots in a three-dimensional environment. The proposed model is considered in the framework of knowledge representation and processing, with special reference to motion knowledge. The model is meant to help setting the basis for a computational theory for motion understanding applied to articulated bodies.

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.

An Inverse Optimal Control Approach to Explain Human Arm Reaching Control Based on Multiple Internal Models.

PubMed

Oguz, Ozgur S; Zhou, Zhehua; Glasauer, Stefan; Wollherr, Dirk

2018-04-03

Human motor control is highly efficient in generating accurate and appropriate motor behavior for a multitude of tasks. This paper examines how kinematic and dynamic properties of the musculoskeletal system are controlled to achieve such efficiency. Even though recent studies have shown that the human motor control relies on multiple models, how the central nervous system (CNS) controls this combination is not fully addressed. In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this combination changes for different reaching tasks. We conducted an experiment where participants executed a comprehensive set of free-space reaching motions. The results show that there is a trade-off between kinematics and dynamics based controllers depending on the reaching task. In addition, this trade-off depends on the initial and final arm configurations, which in turn affect the musculoskeletal load to be controlled. Given this insight, we further provide a discomfort metric to demonstrate its influence on the contribution of different inverse internal models. This formulation together with our analysis not only support the multiple internal models (MIMs) hypothesis but also suggest a hierarchical framework for the control of human reaching motions by the CNS.

Elements of an improved model of debris-flow motion

USGS Publications Warehouse

Iverson, R.M.

2009-01-01

A new depth-averaged model of debris-flow motion describes simultaneous evolution of flow velocity and depth, solid and fluid volume fractions, and pore-fluid pressure. Non-hydrostatic pore-fluid pressure is produced by dilatancy, a state-dependent property that links the depth-averaged shear rate and volumetric strain rate of the granular phase. Pore-pressure changes caused by shearing allow the model to exhibit rate-dependent flow resistance, despite the fact that the basal shear traction involves only rate-independent Coulomb friction. An analytical solution of simplified model equations shows that the onset of downslope motion can be accelerated or retarded by pore-pressure change, contingent on whether dilatancy is positive or negative. A different analytical solution shows that such effects will likely be muted if downslope motion continues long enough, because dilatancy then evolves toward zero, and volume fractions and pore pressure concurrently evolve toward steady states. ?? 2009 American Institute of Physics.

Extension of Characterized Source Model for Broadband Strong Ground Motion Simulations (0.1-50s) of M9 Earthquake

NASA Astrophysics Data System (ADS)

Asano, K.; Iwata, T.

2014-12-01

Fourier amplitude spectra in the period range 0.1-50s. The location of this large slip area seems to overlap the source regions of historical events in 1793 and 1897 off Sanriku area. We think the source model for strong motion prediction of Mw9 event could be constructed by the combination of hierarchical multiple asperities or source patches related to histrorical events in this region.

Brownian motion model with stochastic parameters for asset prices

NASA Astrophysics Data System (ADS)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

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.

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

PubMed

Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz

2014-05-01

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

PubMed Central

Beck, Cornelia; Neumann, Heiko

2011-01-01

Background The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour. PMID:21814543

A model for the pilot's use of motion cues in roll-axis tracking tasks

NASA Technical Reports Server (NTRS)

Levison, W. H.; Junker, A. M.

1977-01-01

Simulated target-following and disturbance-regulation tasks were explored with subjects using visual-only and combined visual and motion cues. The effects of motion cues on task performance and pilot response behavior were appreciably different for the two task configurations and were consistent with data reported in earlier studies for similar task configurations. The optimal-control model for pilot/vehicle systems provided a task-independent framework for accounting for the pilot's use of motion cues. Specifically, the availability of motion cues was modeled by augmenting the set of perceptual variables to include position, rate, acceleration, and accleration-rate of the motion simulator, and results were consistent with the hypothesis of attention-sharing between visual and motion variables. This straightforward informational model allowed accurate model predictions of the effects of motion cues on a variety of response measures for both the target-following and disturbance-regulation tasks.

Multiple switching modes and multiple level states in memristive devices

NASA Astrophysics Data System (ADS)

Miao, Feng; Yang, J. Joshua; Borghetti, Julien; Strachan, John Paul; Zhang, M.-X.; Goldfarb, Ilan; Medeiros-Ribeiro, Gilberto; Williams, R. Stanley

2011-03-01

As one of the most promising technologies for next generation non-volatile memory, metal oxide based memristive devices have demonstrated great advantages on scalability, operating speed and power consumption. Here we report the observation of multiple switching modes and multiple level states in different memristive systems. The multiple switching modes can be obtained by limiting the current during electroforming, and related transport behaviors, including ionic and electronic motions, are characterized. Such observation can be rationalized by a model of two effective switching layers adjacent to the bottom and top electrodes. Multiple level states, corresponding to different composition of the conducting channel, will also be discussed in the context of multiple-level storage for high density, non-volatile memory applications.

Modeling and measuring the visual detection of ecologically relevant motion by an Anolis lizard.

PubMed

Pallus, Adam C; Fleishman, Leo J; Castonguay, Philip M

2010-01-01

Motion in the visual periphery of lizards, and other animals, often causes a shift of visual attention toward the moving object. This behavioral response must be more responsive to relevant motion (predators, prey, conspecifics) than to irrelevant motion (windblown vegetation). Early stages of visual motion detection rely on simple local circuits known as elementary motion detectors (EMDs). We presented a computer model consisting of a grid of correlation-type EMDs, with videos of natural motion patterns, including prey, predators and windblown vegetation. We systematically varied the model parameters and quantified the relative response to the different classes of motion. We carried out behavioral experiments with the lizard Anolis sagrei and determined that their visual response could be modeled with a grid of correlation-type EMDs with a spacing parameter of 0.3 degrees visual angle, and a time constant of 0.1 s. The model with these parameters gave substantially stronger responses to relevant motion patterns than to windblown vegetation under equivalent conditions. However, the model is sensitive to local contrast and viewer-object distance. Therefore, additional neural processing is probably required for the visual system to reliably distinguish relevant from irrelevant motion under a full range of natural conditions.

Generation of a mixture model ground-motion prediction equation for Northern Chile

NASA Astrophysics Data System (ADS)

Haendel, A.; Kuehn, N. M.; Scherbaum, F.

2012-12-01

In probabilistic seismic hazard analysis (PSHA) empirically derived ground motion prediction equations (GMPEs) are usually applied to estimate the ground motion at a site of interest as a function of source, path and site related predictor variables. Because GMPEs are derived from limited datasets they are not expected to give entirely accurate estimates or to reflect the whole range of possible future ground motion, thus giving rise to epistemic uncertainty in the hazard estimates. This is especially true for regions without an indigenous GMPE where foreign models have to be applied. The choice of appropriate GMPEs can then dominate the overall uncertainty in hazard assessments. In order to quantify this uncertainty, the set of ground motion models used in a modern PSHA has to capture (in SSHAC language) the center, body, and range of the possible ground motion at the site of interest. This was traditionally done within a logic tree framework in which existing (or only slightly modified) GMPEs occupy the branches of the tree and the branch weights describe the degree-of-belief of the analyst in their applicability. This approach invites the problem to combine GMPEs of very different quality and hence to potentially overestimate epistemic uncertainty. Some recent hazard analysis have therefore resorted to using a small number of high quality GMPEs as backbone models from which the full distribution of GMPEs for the logic tree (to capture the full range of possible ground motion uncertainty) where subsequently generated by scaling (in a general sense). In the present study, a new approach is proposed to determine an optimized backbone model as weighted components of a mixture model. In doing so, each GMPE is assumed to reflect the generation mechanism (e. g. in terms of stress drop, propagation properties, etc.) for at least a fraction of possible ground motions in the area of interest. The combination of different models into a mixture model (which is learned from

TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction

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

Li, G; Yuan, A; Wei, J

2014-06-15

Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation.more » The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships

SU-E-J-163: A Biomechanical Lung Model for Respiratory Motion Study

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

Liu, X; Belcher, AH; Grelewicz, Z

2015-06-15

Purpose: This work presents a biomechanical model to investigate the complex respiratory motion for the lung tumor tracking in radiosurgery by computer simulation. Methods: The models include networked massspring-dampers to describe the tumor motion, different types of surrogate signals, and the force generated by the diaphragm. Each mass-springdamper has the same mechanical structure and each model can have different numbers of mass-spring-dampers. Both linear and nonlinear stiffness parameters were considered, and the damping ratio was tuned in a range so that the tumor motion was over-damped (no natural tumor oscillation occurs without force from the diaphragm). The simulation was runmore » by using ODE45 (ordinary differential equations by Runge-Kutta method) in MATLAB, and all time courses of motions and inputs (force) were generated and compared. Results: The curvature of the motion time courses around their peaks was sensitive to the damping ratio. Therefore, the damping ratio can be determined based on the clinical data of a high sampling rate. The peak values of different signals and the time the peaks occurred were compared, and it was found that the diaphragm force had a time lead over the tumor motion, and the lead time (0.1–0.4 seconds) depended on the distance between the tumor and the diaphragm. Conclusion: We reported a model based analysis approach for the spatial and temporal relation between the motion of the lung tumor and the surrogate signals. Due to the phase lead of the diaphragm in comparing with the lung tumor motion, the measurement of diaphragm motion (or its electromyography signal) can be used as a beam gating signal in radiosurgery, and it can also be an additional surrogate signal for better tumor motion tracking. The research is funded by the American Cancer Society (ACS) grant. The grant name is: Frameless SRS Based on Robotic Head Motion Cancellation. The grant number is: RSG-13-313-01-CCE.« less

Polar Motion Constraints on Models of the Fortnightly Tide

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Egbert, G. D.; Smith, David E. (Technical Monitor)

2002-01-01

Estimates of the near-fortnightly Mf ocean tide from Topex/Poseidon satellite altimetry and from numerical solutions to the shallow water equations agree reasonably well, at least in their basin-scale features. For example, both show that the Pacific Ocean tide lags the Atlantic tide by roughly 30 degrees. There are hints of finer scale agreements in the elevation fields, but noise levels are high. In contrast, estimates of Mf currents are only weakly constrained by the TP data, because high-wavenumber Rossby waves (with intense currents) are associated with relatively small perturbations in surface elevation. As a result, a wide range of Mf current fields are consistent with both the TP data and the hydrodynamic equations within a priori plausible misfit bounds. We find that a useful constraint on the Mf currents is provided by independent estimates of the Earth's polar motion. At the Mf period polar motion shows a weak signal (both prograde and retrograde) which must be almost entirely caused by the ocean tide. We have estimated this signal from the SPACE2000 time series, after applying a broad-band correction for atmospheric angular momentum. Although the polar motion estimates have relatively large uncertainties, they are sufficiently precise to fix optimum data weights in a global ocean inverse model of Mf. These weights control the tradeoff between fitting a prior hydrodynamic model of Mf and fitting the relatively noisy T/P measurements of Mf. The predicted polar motion from the final inverse model agrees remarkably well with the Mf polar motion observations. The preferred model is also consistent with noise levels suggested by island gauges, and it is marginally consistent with differences observed by subsetting the altimetry (to the small extent that this is possible). In turn, this new model of the Mf ocean tide allows the ocean component to be removed from Mf estimates of length of day, thus yielding estimates of complex Love numbers less contaminated by

Processing of angular motion and gravity information through an internal model.

PubMed

Laurens, Jean; Straumann, Dominik; Hess, Bernhard J M

2010-09-01

The vestibular organs in the base of the skull provide important information about head orientation and motion in space. Previous studies have suggested that both angular velocity information from the semicircular canals and information about head orientation and translation from the otolith organs are centrally processed in an internal model of head motion, using the principles of optimal estimation. This concept has been successfully applied to model behavioral responses to classical vestibular motion paradigms. This study measured the dynamic of the vestibuloocular reflex during postrotatory tilt, tilt during the optokinetic afternystagmus, and off-vertical axis rotation. The influence of otolith signal on the VOR was systematically varied by using a series of tilt angles. We found that the time constants of responses varied almost identically as a function of gravity in these paradigms. We show that Bayesian modeling could predict the experimental results in an accurate and consistent manner. In contrast to other approaches, the Bayesian model also provides a plausible explanation of why these vestibulooculo motor responses occur as a consequence of an internal process of optimal motion estimation.

Surrogate-driven deformable motion model for organ motion tracking in particle radiation therapy

NASA Astrophysics Data System (ADS)

Fassi, Aurora; Seregni, Matteo; Riboldi, Marco; Cerveri, Pietro; Sarrut, David; Battista Ivaldi, Giovanni; Tabarelli de Fatis, Paola; Liotta, Marco; Baroni, Guido

2015-02-01

The aim of this study is the development and experimental testing of a tumor tracking method for particle radiation therapy, providing the daily respiratory dynamics of the patient’s thoraco-abdominal anatomy as a function of an external surface surrogate combined with an a priori motion model. The proposed tracking approach is based on a patient-specific breathing motion model, estimated from the four-dimensional (4D) planning computed tomography (CT) through deformable image registration. The model is adapted to the interfraction baseline variations in the patient’s anatomical configuration. The driving amplitude and phase parameters are obtained intrafractionally from a respiratory surrogate signal derived from the external surface displacement. The developed technique was assessed on a dataset of seven lung cancer patients, who underwent two repeated 4D CT scans. The first 4D CT was used to build the respiratory motion model, which was tested on the second scan. The geometric accuracy in localizing lung lesions, mediated over all breathing phases, ranged between 0.6 and 1.7 mm across all patients. Errors in tracking the surrounding organs at risk, such as lungs, trachea and esophagus, were lower than 1.3 mm on average. The median absolute variation in water equivalent path length (WEL) within the target volume did not exceed 1.9 mm-WEL for simulated particle beams. A significant improvement was achieved compared with error compensation based on standard rigid alignment. The present work can be regarded as a feasibility study for the potential extension of tumor tracking techniques in particle treatments. Differently from current tracking methods applied in conventional radiotherapy, the proposed approach allows for the dynamic localization of all anatomical structures scanned in the planning CT, thus providing complete information on density and WEL variations required for particle beam range adaptation.

Building Mathematical Models of Simple Harmonic and Damped Motion.

ERIC Educational Resources Information Center

Edwards, Thomas

1995-01-01

By developing a sequence of mathematical models of harmonic motion, shows that mathematical models are not right or wrong, but instead are better or poorer representations of the problem situation. (MKR)

A neural model of motion processing and visual navigation by cortical area MST.

PubMed

Grossberg, S; Mingolla, E; Pack, C

1999-12-01

Cells in the dorsal medial superior temporal cortex (MSTd) process optic flow generated by self-motion during visually guided navigation. A neural model shows how interactions between well-known neural mechanisms (log polar cortical magnification, Gaussian motion-sensitive receptive fields, spatial pooling of motion-sensitive signals and subtractive extraretinal eye movement signals) lead to emergent properties that quantitatively simulate neurophysiological data about MSTd cell properties and psychophysical data about human navigation. Model cells match MSTd neuron responses to optic flow stimuli placed in different parts of the visual field, including position invariance, tuning curves, preferred spiral directions, direction reversals, average response curves and preferred locations for stimulus motion centers. The model shows how the preferred motion direction of the most active MSTd cells can explain human judgments of self-motion direction (heading), without using complex heading templates. The model explains when extraretinal eye movement signals are needed for accurate heading perception, and when retinal input is sufficient, and how heading judgments depend on scene layouts and rotation rates.

Multiple vibration modes within the organ of Corti revealed by high-resolution, outer-hair-cell-driven micromechanical motions at acoustic frequencies

NASA Astrophysics Data System (ADS)

Karavitaki, K. Domenica; Guinan, John J.; Mountain, David C.

2018-05-01

Electrically-evoked outer-hair-cell-driven micromechanical motions within the organ of Corti were visualized and quantified using a video stroboscopy system. The resulting radial motions exhibited phase transitions along the radial direction, characteristic of a system that can exhibit multiple modes of vibration. We argue that the interaction of these modes would shape the input to the inner hair cell hair bundles and resulting auditory-nerve response patterns.

Lagrangian speckle model and tissue-motion estimation--theory.

PubMed

Maurice, R L; Bertrand, M

1999-07-01

It is known that when a tissue is subjected to movements such as rotation, shearing, scaling, etc., changes in speckle patterns that result act as a noise source, often responsible for most of the displacement-estimate variance. From a modeling point of view, these changes can be thought of as resulting from two mechanisms: one is the motion of the speckles and the other, the alterations of their morphology. In this paper, we propose a new tissue-motion estimator to counteract these speckle decorrelation effects. The estimator is based on a Lagrangian description of the speckle motion. This description allows us to follow local characteristics of the speckle field as if they were a material property. This method leads to an analytical description of the decorrelation in a way which enables the derivation of an appropriate inverse filter for speckle restoration. The filter is appropriate for linear geometrical transformation of the scattering function (LT), i.e., a constant-strain region of interest (ROI). As the LT itself is a parameter of the filter, a tissue-motion estimator can be formulated as a nonlinear minimization problem, seeking the best match between the pre-tissue-motion image and a restored-speckle post-motion image. The method is tested, using simulated radio-frequency (RF) images of tissue undergoing axial shear.

Ride quality evaluation. IV - Models of subjective reaction to aircraft motion

NASA Technical Reports Server (NTRS)

Jacobson, I. D.; Richards, L. G.

1978-01-01

The paper examines models of human reaction to the motions typically experienced on short-haul aircraft flights. Data are taken on the regularly scheduled flights of four commercial airlines - three airplanes and one helicopter. The data base consists of: (1) a series of motion recordings distributed over each flight, each including all six degrees of freedom of motion; temperature, pressure, and noise are also recorded; (2) ratings of perceived comfort and satisfaction from the passengers on each flight; (3) moment-by-moment comfort ratings from a test subject assigned to each airplane; and (4) overall comfort ratings for each flight from the test subjects. Regression models are obtained for prediction of rated comfort from rms values for six degrees of freedom of motion. It is shown that the model C = 2.1 + 17.1 T + 17.2 V (T = transverse acceleration, V = vertical acceleration) gives a good fit to the airplane data but is less acceptable for the helicopter data.

Changes in Upper Extremity Range of Motion and Efficiency in Multiple Sclerosis Patients Due to Water Activity.

ERIC Educational Resources Information Center

Duthie, Pamela Rae

To determine the effects of water exercise on the movements of multiple sclerosis patients, this study utilized tests to determine changes in the linear range of motion of the shoulder, elbow, and wrist after a 45-minute period of water activities and to determine if the movement became more effective. The test used was an overhead throw with a…

Direct Visuo-Haptic 4D Volume Rendering Using Respiratory Motion Models.

PubMed

Fortmeier, Dirk; Wilms, Matthias; Mastmeyer, Andre; Handels, Heinz

2015-01-01

This article presents methods for direct visuo-haptic 4D volume rendering of virtual patient models under respiratory motion. Breathing models are computed based on patient-specific 4D CT image data sequences. Virtual patient models are visualized in real-time by ray casting based rendering of a reference CT image warped by a time-variant displacement field, which is computed using the motion models at run-time. Furthermore, haptic interaction with the animated virtual patient models is provided by using the displacements computed at high rendering rates to translate the position of the haptic device into the space of the reference CT image. This concept is applied to virtual palpation and the haptic simulation of insertion of a virtual bendable needle. To this aim, different motion models that are applicable in real-time are presented and the methods are integrated into a needle puncture training simulation framework, which can be used for simulated biopsy or vessel puncture in the liver. To confirm real-time applicability, a performance analysis of the resulting framework is given. It is shown that the presented methods achieve mean update rates around 2,000 Hz for haptic simulation and interactive frame rates for volume rendering and thus are well suited for visuo-haptic rendering of virtual patients under respiratory motion.

Thoracic respiratory motion estimation from MRI using a statistical model and a 2-D image navigator.

PubMed

King, A P; Buerger, C; Tsoumpas, C; Marsden, P K; Schaeffter, T

2012-01-01

Respiratory motion models have potential application for estimating and correcting the effects of motion in a wide range of applications, for example in PET-MR imaging. Given that motion cycles caused by breathing are only approximately repeatable, an important quality of such models is their ability to capture and estimate the intra- and inter-cycle variability of the motion. In this paper we propose and describe a technique for free-form nonrigid respiratory motion correction in the thorax. Our model is based on a principal component analysis of the motion states encountered during different breathing patterns, and is formed from motion estimates made from dynamic 3-D MRI data. We apply our model using a data-driven technique based on a 2-D MRI image navigator. Unlike most previously reported work in the literature, our approach is able to capture both intra- and inter-cycle motion variability. In addition, the 2-D image navigator can be used to estimate how applicable the current motion model is, and hence report when more imaging data is required to update the model. We also use the motion model to decide on the best positioning for the image navigator. We validate our approach using MRI data acquired from 10 volunteers and demonstrate improvements of up to 40.5% over other reported motion modelling approaches, which corresponds to 61% of the overall respiratory motion present. Finally we demonstrate one potential application of our technique: MRI-based motion correction of real-time PET data for simultaneous PET-MRI acquisition. Copyright © 2011 Elsevier B.V. All rights reserved.

Motion analysis study on sensitivity of finite element model of the cervical spine to geometry.

PubMed

Zafarparandeh, Iman; Erbulut, Deniz U; Ozer, Ali F

2016-07-01

Numerous finite element models of the cervical spine have been proposed, with exact geometry or with symmetric approximation in the geometry. However, few researches have investigated the sensitivity of predicted motion responses to the geometry of the cervical spine. The goal of this study was to evaluate the effect of symmetric assumption on the predicted motion by finite element model of the cervical spine. We developed two finite element models of the cervical spine C2-C7. One model was based on the exact geometry of the cervical spine (asymmetric model), whereas the other was symmetric (symmetric model) about the mid-sagittal plane. The predicted range of motion of both models-main and coupled motions-was compared with published experimental data for all motion planes under a full range of loads. The maximum differences between the asymmetric model and symmetric model predictions for the principal motion were 31%, 78%, and 126% for flexion-extension, right-left lateral bending, and right-left axial rotation, respectively. For flexion-extension and lateral bending, the minimum difference was 0%, whereas it was 2% for axial rotation. The maximum coupled motions predicted by the symmetric model were 1.5° axial rotation and 3.6° lateral bending, under applied lateral bending and axial rotation, respectively. Those coupled motions predicted by the asymmetric model were 1.6° axial rotation and 4° lateral bending, under applied lateral bending and axial rotation, respectively. In general, the predicted motion response of the cervical spine by the symmetric model was in the acceptable range and nonlinearity of the moment-rotation curve for the cervical spine was properly predicted. © IMechE 2016.

Ubiquitous human upper-limb motion estimation using wearable sensors.

PubMed

Zhang, Zhi-Qiang; Wong, Wai-Choong; Wu, Jian-Kang

2011-07-01

Human motion capture technologies have been widely used in a wide spectrum of applications, including interactive game and learning, animation, film special effects, health care, navigation, and so on. The existing human motion capture techniques, which use structured multiple high-resolution cameras in a dedicated studio, are complicated and expensive. With the rapid development of microsensors-on-chip, human motion capture using wearable microsensors has become an active research topic. Because of the agility in movement, upper-limb motion estimation has been regarded as the most difficult problem in human motion capture. In this paper, we take the upper limb as our research subject and propose a novel ubiquitous upper-limb motion estimation algorithm, which concentrates on modeling the relationship between upper-arm movement and forearm movement. A link structure with 5 degrees of freedom (DOF) is proposed to model the human upper-limb skeleton structure. Parameters are defined according to Denavit-Hartenberg convention, forward kinematics equations are derived, and an unscented Kalman filter is deployed to estimate the defined parameters. The experimental results have shown that the proposed upper-limb motion capture and analysis algorithm outperforms other fusion methods and provides accurate results in comparison to the BTS optical motion tracker.

Numerical modeling of on-orbit propellant motion resulting from an impulsive acceleration

NASA Technical Reports Server (NTRS)

Aydelott, John C.; Mjolsness, Raymond C.; Torrey, Martin D.; Hochstein, John I.

1987-01-01

In-space docking and separation maneuvers of spacecraft that have large fluid mass fractions may cause undesirable spacecraft motion in response to the impulsive-acceleration-induced fluid motion. An example of this potential low gravity fluid management problem arose during the development of the shuttle/Centaur vehicle. Experimentally verified numerical modeling techniques were developed to establish the propellant dynamics, and subsequent vehicle motion, associated with the separation of the Centaur vehicle from the shuttle orbiter cargo bay. Although the shuttle/Centaur development activity was suspended, the numerical modeling techniques are available to predict on-orbit liquid motion resulting from impulsive accelerations for other missions and spacecraft.

A biomechanical modeling guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2017-03-01

Four-dimensional (4D) cone-beam computed tomography (CBCT) enables motion tracking of anatomical structures and removes artifacts introduced by motion. However, the imaging time/dose of 4D-CBCT is substantially longer/higher than traditional 3D-CBCT. We previously developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, to reconstruct high-quality 4D-CBCT from limited number of projections to reduce the imaging time/dose. However, the accuracy of SMEIR is limited in reconstructing low-contrast regions with fine structure details. In this study, we incorporate biomechanical modeling into the SMEIR algorithm (SMEIR-Bio), to improve the reconstruction accuracy at low-contrast regions with fine details. The efficacy of SMEIR-Bio is evaluated using 11 lung patient cases and compared to that of the original SMEIR algorithm. Qualitative and quantitative comparisons showed that SMEIR-Bio greatly enhances the accuracy of reconstructed 4D-CBCT volume in low-contrast regions, which can potentially benefit multiple clinical applications including the treatment outcome analysis.

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks

PubMed Central

Vakanski, A; Ferguson, JM; Lee, S

2016-01-01

Objective The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient’s exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient’s physician with recommendations for improvement. Methods The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. Results The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject’s performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. Conclusion The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks.

PubMed

Vakanski, A; Ferguson, J M; Lee, S

2016-12-01

The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement. The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject's performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of

Facial motion parameter estimation and error criteria in model-based image coding

NASA Astrophysics Data System (ADS)

Liu, Yunhai; Yu, Lu; Yao, Qingdong

2000-04-01

Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.

The application of the sinusoidal model to lung cancer patient respiratory motion

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

George, R.; Vedam, S.S.; Chung, T.D.

2005-09-15

Accurate modeling of the respiratory cycle is important to account for the effect of organ motion on dose calculation for lung cancer patients. The aim of this study is to evaluate the accuracy of a respiratory model for lung cancer patients. Lujan et al. [Med. Phys. 26(5), 715-720 (1999)] proposed a model, which became widely used, to describe organ motion due to respiration. This model assumes that the parameters do not vary between and within breathing cycles. In this study, first, the correlation of respiratory motion traces with the model f(t) as a function of the parameter n(n=1,2,3) was undertakenmore » for each breathing cycle from 331 four-minute respiratory traces acquired from 24 lung cancer patients using three breathing types: free breathing, audio instruction, and audio-visual biofeedback. Because cos{sup 2} and cos{sup 4} had similar correlation coefficients, and cos{sup 2} and cos{sup 1} have a trigonometric relationship, for simplicity, the cos{sup 1} value was consequently used for further analysis in which the variations in mean position (z{sub 0}), amplitude of motion (b) and period ({tau}) with and without biofeedback or instructions were investigated. For all breathing types, the parameter values, mean position (z{sub 0}), amplitude of motion (b), and period ({tau}) exhibited significant cycle-to-cycle variations. Audio-visual biofeedback showed the least variations for all three parameters (z{sub 0}, b, and {tau}). It was found that mean position (z{sub 0}) could be approximated with a normal distribution, and the amplitude of motion (b) and period ({tau}) could be approximated with log normal distributions. The overall probability density function (pdf) of f(t) for each of the three breathing types was fitted with three models: normal, bimodal, and the pdf of a simple harmonic oscillator. It was found that the normal and the bimodal models represented the overall respiratory motion pdfs with correlation values from 0.95 to 0.99, whereas

Subject-Specific Carpal Ligament Elongation in Extreme Positions, Grip, and the Dart Thrower's Motion

PubMed Central

Rainbow, Michael J.; Kamal, Robin N.; Moore, Douglas C.; Akelman, Edward; Wolfe, Scott W.; Crisco, Joseph J.

2015-01-01

This study examined whether the radiocarpal and dorsal capsular ligaments limit end-range wrist motion or remain strained during midrange wrist motion. Fibers of these ligaments were modeled in the wrists of 12 subjects over multiple wrist positions that reflect high demand tasks and the dart thrower's motion. We found that many of the volar and dorsal ligaments were within 5% of their maximum length throughout the range of wrist motion. Our finding of wrist ligament recruitment during midrange and end-range wrist motion helps to explain the complex but remarkably similar intersubject patterns of carpal motion. PMID:26367853

The use of the logistic model in space motion sickness prediction

NASA Technical Reports Server (NTRS)

Lin, Karl K.; Reschke, Millard F.

1987-01-01

The one-equation and the two-equation logistic models were used to predict subjects' susceptibility to motion sickness in KC-135 parabolic flights using data from other ground-based motion sickness tests. The results show that the logistic models correctly predicted substantially more cases (an average of 13 percent) in the data subset used for model building. Overall, the logistic models ranged from 53 to 65 percent predictions of the three endpoint parameters, whereas the Bayes linear discriminant procedure ranged from 48 to 65 percent correct for the cross validation sample.

Coexistence of bounded and unbounded motions in a bouncing ball model

NASA Astrophysics Data System (ADS)

Marò, Stefano

2013-05-01

We consider the model describing the vertical motion of a ball falling with constant acceleration on a wall and elastically reflected. The wall is supposed to move in the vertical direction according to a given periodic function f. We apply the Aubry-Mather theory to the generating function in order to prove the existence of bounded motions with prescribed mean time between the bounces. As the existence of unbounded motions is known, it is possible to find a class of functions f that allow both bounded and unbounded motions.

Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy

NASA Astrophysics Data System (ADS)

Qiu, Peng; D'Souza, Warren D.; McAvoy, Thomas J.; Liu, K. J. Ray

2007-09-01

Tumor motion induced by respiration presents a challenge to the reliable delivery of conformal radiation treatments. Real-time motion compensation represents the technologically most challenging clinical solution but has the potential to overcome the limitations of existing methods. The performance of a real-time couch-based motion compensation system is mainly dependent on two aspects: the ability to infer the internal anatomical position and the performance of the feedback control system. In this paper, we propose two novel methods for the two aspects respectively, and then combine the proposed methods into one system. To accurately estimate the internal tumor position, we present partial-least squares (PLS) regression to predict the position of the diaphragm using skin-based motion surrogates. Four radio-opaque markers were placed on the abdomen of patients who underwent fluoroscopic imaging of the diaphragm. The coordinates of the markers served as input variables and the position of the diaphragm served as the output variable. PLS resulted in lower prediction errors compared with standard multiple linear regression (MLR). The performance of the feedback control system depends on the system dynamics and dead time (delay between the initiation and execution of the control action). While the dynamics of the system can be inverted in a feedback control system, the dead time cannot be inverted. To overcome the dead time of the system, we propose a predictive feedback control system by incorporating forward prediction using least-mean-square (LMS) and recursive least square (RLS) filtering into the couch-based control system. Motion data were obtained using a skin-based marker. The proposed predictive feedback control system was benchmarked against pure feedback control (no forward prediction) and resulted in a significant performance gain. Finally, we combined the PLS inference model and the predictive feedback control to evaluate the overall performance of the

Active Brownian motion models and applications to ratchets

NASA Astrophysics Data System (ADS)

Fiasconaro, A.; Ebeling, W.; Gudowska-Nowak, E.

2008-10-01

We give an overview over recent studies on the model of Active Brownian Motion (ABM) coupled to reservoirs providing free energy which may be converted into kinetic energy of motion. First, we present an introduction to a general concept of active Brownian particles which are capable to take up energy from the source and transform part of it in order to perform various activities. In the second part of our presentation we consider applications of ABM to ratchet systems with different forms of differentiable potentials. Both analytical and numerical evaluations are discussed for three cases of sinusoidal, staircaselike and Mateos ratchet potentials, also with the additional loads modelled by tilted potential structure. In addition, stochastic character of the kinetics is investigated by considering perturbation by Gaussian white noise which is shown to be responsible for driving the directionality of the asymptotic flux in the ratchet. This stochastically driven directionality effect is visualized as a strong nonmonotonic dependence of the statistics of the right versus left trajectories of motion leading to a net current of particles. Possible applications of the ratchet systems to molecular motors are also briefly discussed.

Ground Motion Prediction Model Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Dhanya, J.; Raghukanth, S. T. G.

2018-03-01

This article focuses on developing a ground motion prediction equation based on artificial neural network (ANN) technique for shallow crustal earthquakes. A hybrid technique combining genetic algorithm and Levenberg-Marquardt technique is used for training the model. The present model is developed to predict peak ground velocity, and 5% damped spectral acceleration. The input parameters for the prediction are moment magnitude ( M w), closest distance to rupture plane ( R rup), shear wave velocity in the region ( V s30) and focal mechanism ( F). A total of 13,552 ground motion records from 288 earthquakes provided by the updated NGA-West2 database released by Pacific Engineering Research Center are utilized to develop the model. The ANN architecture considered for the model consists of 192 unknowns including weights and biases of all the interconnected nodes. The performance of the model is observed to be within the prescribed error limits. In addition, the results from the study are found to be comparable with the existing relations in the global database. The developed model is further demonstrated by estimating site-specific response spectra for Shimla city located in Himalayan region.

A New Conflict Resolution Method for Multiple Mobile Robots in Cluttered Environments With Motion-Liveness.

PubMed

Shahriari, Mohammadali; Biglarbegian, Mohammad

2018-01-01

This paper presents a new conflict resolution methodology for multiple mobile robots while ensuring their motion-liveness, especially for cluttered and dynamic environments. Our method constructs a mathematical formulation in a form of an optimization problem by minimizing the overall travel times of the robots subject to resolving all the conflicts in their motion. This optimization problem can be easily solved through coordinating only the robots' speeds. To overcome the computational cost in executing the algorithm for very cluttered environments, we develop an innovative method through clustering the environment into independent subproblems that can be solved using parallel programming techniques. We demonstrate the scalability of our approach through performing extensive simulations. Simulation results showed that our proposed method is capable of resolving the conflicts of 100 robots in less than 1.23 s in a cluttered environment that has 4357 intersections in the paths of the robots. We also developed an experimental testbed and demonstrated that our approach can be implemented in real time. We finally compared our approach with other existing methods in the literature both quantitatively and qualitatively. This comparison shows while our approach is mathematically sound, it is more computationally efficient, scalable for very large number of robots, and guarantees the live and smooth motion of robots.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.

PubMed

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-11-21

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.

Meshless Modeling of Deformable Shapes and their Motion

PubMed Central

Adams, Bart; Ovsjanikov, Maks; Wand, Michael; Seidel, Hans-Peter; Guibas, Leonidas J.

2010-01-01

We present a new framework for interactive shape deformation modeling and key frame interpolation based on a meshless finite element formulation. Starting from a coarse nodal sampling of an object’s volume, we formulate rigidity and volume preservation constraints that are enforced to yield realistic shape deformations at interactive frame rates. Additionally, by specifying key frame poses of the deforming shape and optimizing the nodal displacements while targeting smooth interpolated motion, our algorithm extends to a motion planning framework for deformable objects. This allows reconstructing smooth and plausible deformable shape trajectories in the presence of possibly moving obstacles. The presented results illustrate that our framework can handle complex shapes at interactive rates and hence is a valuable tool for animators to realistically and efficiently model and interpolate deforming 3D shapes. PMID:24839614

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.

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

NASA Technical Reports Server (NTRS)

Oman, C. M.

1982-01-01

The etiology of motion sickness is now usually explained in terms of a qualitatively formulated sensory conflict hypothesis. By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstances, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behavior.

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

NASA Technical Reports Server (NTRS)

Oman, C. M.

1980-01-01

The etiology of motion sickness is explained in terms of a qualitatively formulated sensory conflict hypothesis. By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory-motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstances, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model is proposed which describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behaviors.

A trade-off analysis design tool. Aircraft interior noise-motion/passenger satisfaction model

NASA Technical Reports Server (NTRS)

Jacobson, I. D.

1977-01-01

A design tool was developed to enhance aircraft passenger satisfaction. The effect of aircraft interior motion and noise on passenger comfort and satisfaction was modelled. Effects of individual aircraft noise sources were accounted for, and the impact of noise on passenger activities and noise levels to safeguard passenger hearing were investigated. The motion noise effect models provide a means for tradeoff analyses between noise and motion variables, and also provide a framework for optimizing noise reduction among noise sources. Data for the models were collected onboard commercial aircraft flights and specially scheduled tests.

Motion capture for human motion measuring by using single camera with triangle markers

NASA Astrophysics Data System (ADS)

Takahashi, Hidenori; Tanaka, Takayuki; Kaneko, Shun'ichi

2005-12-01

This study aims to realize a motion capture for measuring 3D human motions by using single camera. Although motion capture by using multiple cameras is widely used in sports field, medical field, engineering field and so on, optical motion capture method with one camera is not established. In this paper, the authors achieved a 3D motion capture by using one camera, named as Mono-MoCap (MMC), on the basis of two calibration methods and triangle markers which each length of side is given. The camera calibration methods made 3D coordinates transformation parameter and a lens distortion parameter with Modified DLT method. The triangle markers enabled to calculate a coordinate value of a depth direction on a camera coordinate. Experiments of 3D position measurement by using the MMC on a measurement space of cubic 2 m on each side show an average error of measurement of a center of gravity of a triangle marker was less than 2 mm. As compared with conventional motion capture method by using multiple cameras, the MMC has enough accuracy for 3D measurement. Also, by putting a triangle marker on each human joint, the MMC was able to capture a walking motion, a standing-up motion and a bending and stretching motion. In addition, a method using a triangle marker together with conventional spherical markers was proposed. Finally, a method to estimate a position of a marker by measuring the velocity of the marker was proposed in order to improve the accuracy of MMC.

Motion Recognition and Modifying Motion Generation for Imitation Robot Based on Motion Knowledge Formation

NASA Astrophysics Data System (ADS)

Okuzawa, Yuki; Kato, Shohei; Kanoh, Masayoshi; Itoh, Hidenori

A knowledge-based approach to imitation learning of motion generation for humanoid robots and an imitative motion generation system based on motion knowledge learning and modification are described. The system has three parts: recognizing, learning, and modifying parts. The first part recognizes an instructed motion distinguishing it from the motion knowledge database by the continuous hidden markov model. When the motion is recognized as being unfamiliar, the second part learns it using locally weighted regression and acquires a knowledge of the motion. When a robot recognizes the instructed motion as familiar or judges that its acquired knowledge is applicable to the motion generation, the third part imitates the instructed motion by modifying a learned motion. This paper reports some performance results: the motion imitation of several radio gymnastics motions.

Optimization of blade motion of vertical axis turbine

NASA Astrophysics Data System (ADS)

Ma, Yong; Zhang, Liang; Zhang, Zhi-yang; Han, Duan-feng

2016-04-01

In this paper, a method is proposed to improve the energy efficiency of the vertical axis turbine. First of all, a single disk multiple stream-tube model is used to calculate individual fitness. Genetic algorithm is adopted to optimize blade pitch motion of vertical axis turbine with the maximum energy efficiency being selected as the optimization objective. Then, a particular data processing method is proposed, fitting the result data into a cosine-like curve. After that, a general formula calculating the blade motion is developed. Finally, CFD simulation is used to validate the blade pitch motion formula. The results show that the turbine's energy efficiency becomes higher after the optimization of blade pitch motion; compared with the fixed pitch turbine, the efficiency of variable-pitch turbine is significantly improved by the active blade pitch control; the energy efficiency declines gradually with the growth of speed ratio; besides, compactness has lager effect on the blade motion while the number of blades has little effect on it.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait.

PubMed

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E; Del-Ama, Antonio J; Dimbwadyo, Iris; Moreno, Juan C; Florez, Julian; Pons, Jose L

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton.

A Subject-Specific Kinematic Model to Predict Human Motion in Exoskeleton-Assisted Gait

PubMed Central

Torricelli, Diego; Cortés, Camilo; Lete, Nerea; Bertelsen, Álvaro; Gonzalez-Vargas, Jose E.; del-Ama, Antonio J.; Dimbwadyo, Iris; Moreno, Juan C.; Florez, Julian; Pons, Jose L.

2018-01-01

The relative motion between human and exoskeleton is a crucial factor that has remarkable consequences on the efficiency, reliability and safety of human-robot interaction. Unfortunately, its quantitative assessment has been largely overlooked in the literature. Here, we present a methodology that allows predicting the motion of the human joints from the knowledge of the angular motion of the exoskeleton frame. Our method combines a subject-specific skeletal model with a kinematic model of a lower limb exoskeleton (H2, Technaid), imposing specific kinematic constraints between them. To calibrate the model and validate its ability to predict the relative motion in a subject-specific way, we performed experiments on seven healthy subjects during treadmill walking tasks. We demonstrate a prediction accuracy lower than 3.5° globally, and around 1.5° at the hip level, which represent an improvement up to 66% compared to the traditional approach assuming no relative motion between the user and the exoskeleton. PMID:29755336

MetaTracker: integration and abstraction of 3D motion tracking data from multiple hardware systems

NASA Astrophysics Data System (ADS)

Kopecky, Ken; Winer, Eliot

2014-06-01

Motion tracking has long been one of the primary challenges in mixed reality (MR), augmented reality (AR), and virtual reality (VR). Military and defense training can provide particularly difficult challenges for motion tracking, such as in the case of Military Operations in Urban Terrain (MOUT) and other dismounted, close quarters simulations. These simulations can take place across multiple rooms, with many fast-moving objects that need to be tracked with a high degree of accuracy and low latency. Many tracking technologies exist, such as optical, inertial, ultrasonic, and magnetic. Some tracking systems even combine these technologies to complement each other. However, there are no systems that provide a high-resolution, flexible, wide-area solution that is resistant to occlusion. While frameworks exist that simplify the use of tracking systems and other input devices, none allow data from multiple tracking systems to be combined, as if from a single system. In this paper, we introduce a method for compensating for the weaknesses of individual tracking systems by combining data from multiple sources and presenting it as a single tracking system. Individual tracked objects are identified by name, and their data is provided to simulation applications through a server program. This allows tracked objects to transition seamlessly from the area of one tracking system to another. Furthermore, it abstracts away the individual drivers, APIs, and data formats for each system, providing a simplified API that can be used to receive data from any of the available tracking systems. Finally, when single-piece tracking systems are used, those systems can themselves be tracked, allowing for real-time adjustment of the trackable area. This allows simulation operators to leverage limited resources in more effective ways, improving the quality of training.

Animation control of surface motion capture.

PubMed

Tejera, Margara; Casas, Dan; Hilton, Adrian

2013-12-01

Surface motion capture (SurfCap) of actor performance from multiple view video provides reconstruction of the natural nonrigid deformation of skin and clothing. This paper introduces techniques for interactive animation control of SurfCap sequences which allow the flexibility in editing and interactive manipulation associated with existing tools for animation from skeletal motion capture (MoCap). Laplacian mesh editing is extended using a basis model learned from SurfCap sequences to constrain the surface shape to reproduce natural deformation. Three novel approaches for animation control of SurfCap sequences, which exploit the constrained Laplacian mesh editing, are introduced: 1) space–time editing for interactive sequence manipulation; 2) skeleton-driven animation to achieve natural nonrigid surface deformation; and 3) hybrid combination of skeletal MoCap driven and SurfCap sequence to extend the range of movement. These approaches are combined with high-level parametric control of SurfCap sequences in a hybrid surface and skeleton-driven animation control framework to achieve natural surface deformation with an extended range of movement by exploiting existing MoCap archives. Evaluation of each approach and the integrated animation framework are presented on real SurfCap sequences for actors performing multiple motions with a variety of clothing styles. Results demonstrate that these techniques enable flexible control for interactive animation with the natural nonrigid surface dynamics of the captured performance and provide a powerful tool to extend current SurfCap databases by incorporating new motions from MoCap sequences.

Flocking and Turning: a New Model for Self-organized Collective Motion

NASA Astrophysics Data System (ADS)

Cavagna, Andrea; Del Castello, Lorenzo; Giardina, Irene; Grigera, Tomas; Jelic, Asja; Melillo, Stefania; Mora, Thierry; Parisi, Leonardo; Silvestri, Edmondo; Viale, Massimiliano; Walczak, Aleksandra M.

2015-02-01

Birds in a flock move in a correlated way, resulting in large polarization of velocities. A good understanding of this collective behavior exists for linear motion of the flock. Yet observing actual birds, the center of mass of the group often turns giving rise to more complicated dynamics, still keeping strong polarization of the flock. Here we propose novel dynamical equations for the collective motion of polarized animal groups that account for correlated turning including solely social forces. We exploit rotational symmetries and conservation laws of the problem to formulate a theory in terms of generalized coordinates of motion for the velocity directions akin to a Hamiltonian formulation for rotations. We explicitly derive the correspondence between this formulation and the dynamics of the individual velocities, thus obtaining a new model of collective motion. In the appropriate overdamped limit we recover the well-known Vicsek model, which dissipates rotational information and does not allow for polarized turns. Although the new model has its most vivid success in describing turning groups, its dynamics is intrinsically different from previous ones in a wide dynamical regime, while reducing to the hydrodynamic description of Toner and Tu at very large length-scales. The derived framework is therefore general and it may describe the collective motion of any strongly polarized active matter system.

Geomagnetic field models for satellite angular motion studies

NASA Astrophysics Data System (ADS)

Ovchinnikov, M. Yu.; Penkov, V. I.; Roldugin, D. S.; Pichuzhkina, A. V.

2018-03-01

Four geomagnetic field models are discussed: IGRF, inclined, direct and simplified dipoles. Geomagnetic induction vector expressions are provided in different reference frames. Induction vector behavior is compared for different models. Models applicability for the analysis of satellite motion is studied from theoretical and engineering perspectives. Relevant satellite dynamics analysis cases using analytical and numerical techniques are provided. These cases demonstrate the benefit of a certain model for a specific dynamics study. Recommendations for models usage are summarized in the end.

Orbital motions of astronomical bodies and their centre of mass from different reference frames: a conceptual step between the geocentric and heliocentric models

NASA Astrophysics Data System (ADS)

Guerra, André G. C.; Simeão Carvalho, Paulo

2016-09-01

The motion of astronomical bodies and the centre of mass of the system is not always well perceived by students. One of the struggles is the conceptual change of reference frame, which is the same that held back the acceptance of the Heliocentric model over the Geocentric one. To address the question, the notion of centre of mass, motion equations (and their numerical solution for a system of multiple bodies), and change of frame of reference is introduced. The discussion is done based on conceptual and real world examples, using the solar system. Consequently, through the use of simple ‘do it yourself’ methods and basic equations, students can debate complex motions, and have a wider and potentially effective understanding of physics.

The Long Decay Model of One-Dimensional Projectile Motion

ERIC Educational Resources Information Center

Lattery, Mark Joseph

2008-01-01

This article introduces a research study on student model formation and development in introductory mechanics. As a point of entry, I present a detailed analysis of the Long Decay Model of one-dimensional projectile motion. This model has been articulated by Galileo ("in De Motu") and by contemporary students. Implications for instruction are…

Source Model of Huge Subduction Earthquakes for Strong Ground Motion Prediction

NASA Astrophysics Data System (ADS)

Iwata, T.; Asano, K.

2012-12-01

It is a quite important issue for strong ground motion prediction to construct the source model of huge subduction earthquakes. Irikura and Miyake (2001, 2011) proposed the characterized source model for strong ground motion prediction, which consists of plural strong ground motion generation area (SMGA, Miyake et al., 2003) patches on the source fault. We obtained the SMGA source models for many events using the empirical Green's function method and found the SMGA size has an empirical scaling relationship with seismic moment. Therefore, the SMGA size can be assumed from that empirical relation under giving the seismic moment for anticipated earthquakes. Concerning to the setting of the SMGAs position, the information of the fault segment is useful for inland crustal earthquakes. For the 1995 Kobe earthquake, three SMGA patches are obtained and each Nojima, Suma, and Suwayama segment respectively has one SMGA from the SMGA modeling (e.g. Kamae and Irikura, 1998). For the 2011 Tohoku earthquake, Asano and Iwata (2012) estimated the SMGA source model and obtained four SMGA patches on the source fault. Total SMGA area follows the extension of the empirical scaling relationship between the seismic moment and the SMGA area for subduction plate-boundary earthquakes, and it shows the applicability of the empirical scaling relationship for the SMGA. The positions of two SMGAs are in Miyagi-Oki segment and those other two SMGAs are in Fukushima-Oki and Ibaraki-Oki segments, respectively. Asano and Iwata (2012) also pointed out that all SMGAs are corresponding to the historical source areas of 1930's. Those SMGAs do not overlap the huge slip area in the shallower part of the source fault which estimated by teleseismic data, long-period strong motion data, and/or geodetic data during the 2011 mainshock. This fact shows the huge slip area does not contribute to strong ground motion generation (10-0.1s). The information of the fault segment in the subduction zone, or

Sensitivity of Tumor Motion Simulation Accuracy to Lung Biomechanical Modeling Approaches and Parameters

PubMed Central

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the Neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation. PMID:26531324

3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models

PubMed Central

Dhou, Salam; Hurwitz, Martina; Mishra, Pankaj; Cai, Weixing; Rottmann, Joerg; Li, Ruijiang; Williams, Christopher; Wagar, Matthew; Berbeco, Ross; Ionascu, Dan; Lewis, John H.

2015-01-01

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we develop and perform initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and use these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparing to ground truth digital and physical phantom images. The performance of 4DCBCT- and 4DCT- based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms, and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. PMID:25905722

The effect of postoperative passive motion on rotator cuff healing in a rat model.

PubMed

Peltz, Cathryn D; Dourte, Leann M; Kuntz, Andrew F; Sarver, Joseph J; Kim, Soung-Yon; Williams, Gerald R; Soslowsky, Louis J

2009-10-01

Surgical repairs of torn rotator cuff tendons frequently fail. Immobilization has been shown to improve tissue mechanical properties in an animal model of rotator cuff repair, and passive motion has been shown to improve joint mechanics in animal models of flexor tendon repair. Our objective was to determine if daily passive motion would improve joint mechanics in comparison with continuous immobilization in a rat rotator cuff repair model. We hypothesized that daily passive motion would result in improved passive shoulder joint mechanics in comparison with continuous immobilization initially and that there would be no differences in passive joint mechanics or insertion site mechanical properties after four weeks of remobilization. A supraspinatus injury was created and was surgically repaired in sixty-five Sprague-Dawley rats. Rats were separated into three postoperative groups (continuous immobilization, passive motion protocol 1, and passive motion protocol 2) for two weeks before all underwent a remobilization protocol for four weeks. Serial measurements of passive shoulder mechanics (internal and external range of motion and joint stiffness) were made before surgery and at two and six weeks after surgery. After the animals were killed, collagen organization and mechanical properties of the tendon-to-bone insertion site were determined. Total range of motion for both passive motion groups (49% and 45% of the pre-injury values) was less than that for the continuous immobilization group (59% of the pre-injury value) at two weeks and remained significantly less following four weeks of remobilization exercise. Joint stiffness at two weeks was increased for both passive motion groups in comparison with the continuous immobilization group. At both two and six weeks after repair, internal range of motion was significantly decreased whereas external range of motion was not. There were no differences between the groups in terms of collagen organization or mechanical

On-chip visual perception of motion: a bio-inspired connectionist model on FPGA.

PubMed

Torres-Huitzil, César; Girau, Bernard; Castellanos-Sánchez, Claudio

2005-01-01

Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired neural model for motion estimation is presented. The motion estimation is based on a strongly localized bio-inspired connectionist model with a particular adaptation of spatio-temporal Gabor-like filtering. The architecture is constituted by three main modules that perform spatial, temporal, and excitatory-inhibitory connectionist processing. The biomimetic architecture is modeled, simulated and validated in VHDL. The synthesis results on a Field Programmable Gate Array (FPGA) device show the potential achievement of real-time performance at an affordable silicon area.

Multiple-hypothesis multiple-model line tracking

NASA Astrophysics Data System (ADS)

Pace, Donald W.; Owen, Mark W.; Cox, Henry

2000-07-01

Passive sonar signal processing generally includes tracking of narrowband and/or broadband signature components observed on a Lofargram or on a Bearing-Time-Record (BTR) display. Fielded line tracking approaches to date have been recursive and single-hypthesis-oriented Kalman- or alpha-beta filters, with no mechanism for considering tracking alternatives beyond the most recent scan of measurements. While adaptivity is often built into the filter to handle changing track dynamics, these approaches are still extensions of single target tracking solutions to multiple target tracking environment. This paper describes an application of multiple-hypothesis, multiple target tracking technology to the sonar line tracking problem. A Multiple Hypothesis Line Tracker (MHLT) is developed which retains the recursive minimum-mean-square-error tracking behavior of a Kalman Filter in a maximum-a-posteriori delayed-decision multiple hypothesis context. Multiple line track filter states are developed and maintained using the interacting multiple model (IMM) state representation. Further, the data association and assignment problem is enhanced by considering line attribute information (line bandwidth and SNR) in addition to beam/bearing and frequency fit. MHLT results on real sonar data are presented to demonstrate the benefits of the multiple hypothesis approach. The utility of the system in cluttered environments and particularly in crossing line situations is shown.

Application of data assimilation methods for analysis and integration of observed and modeled Arctic Sea ice motions

NASA Astrophysics Data System (ADS)

Meier, Walter Neil

This thesis demonstrates the applicability of data assimilation methods to improve observed and modeled ice motion fields and to demonstrate the effects of assimilated motion on Arctic processes important to the global climate and of practical concern to human activities. Ice motions derived from 85 GHz and 37 GHz SSM/I imagery and estimated from two-dimensional dynamic-thermodynamic sea ice models are compared to buoy observations. Mean error, error standard deviation, and correlation with buoys are computed for the model domain. SSM/I motions generally have a lower bias, but higher error standard deviations and lower correlation with buoys than model motions. There are notable variations in the statistics depending on the region of the Arctic, season, and ice characteristics. Assimilation methods are investigated and blending and optimal interpolation strategies are implemented. Blending assimilation improves error statistics slightly, but the effect of the assimilation is reduced due to noise in the SSM/I motions and is thus not an effective method to improve ice motion estimates. However, optimal interpolation assimilation reduces motion errors by 25--30% over modeled motions and 40--45% over SSM/I motions. Optimal interpolation assimilation is beneficial in all regions, seasons and ice conditions, and is particularly effective in regimes where modeled and SSM/I errors are high. Assimilation alters annual average motion fields. Modeled ice products of ice thickness, ice divergence, Fram Strait ice volume export, transport across the Arctic and interannual basin averages are also influenced by assimilated motions. Assimilation improves estimates of pollutant transport and corrects synoptic-scale errors in the motion fields caused by incorrect forcings or errors in model physics. The portability of the optimal interpolation assimilation method is demonstrated by implementing the strategy in an ice thickness distribution (ITD) model. This research presents an

Numerical comparisons of ground motion predictions with kinematic rupture modeling

NASA Astrophysics Data System (ADS)

Yuan, Y. O.; Zurek, B.; Liu, F.; deMartin, B.; Lacasse, M. D.

2017-12-01

Recent advances in large-scale wave simulators allow for the computation of seismograms at unprecedented levels of detail and for areas sufficiently large to be relevant to small regional studies. In some instances, detailed information of the mechanical properties of the subsurface has been obtained from seismic exploration surveys, well data, and core analysis. Using kinematic rupture modeling, this information can be used with a wave propagation simulator to predict the ground motion that would result from an assumed fault rupture. The purpose of this work is to explore the limits of wave propagation simulators for modeling ground motion in different settings, and in particular, to explore the numerical accuracy of different methods in the presence of features that are challenging to simulate such as topography, low-velocity surface layers, and shallow sources. In the main part of this work, we use a variety of synthetic three-dimensional models and compare the relative costs and benefits of different numerical discretization methods in computing the seismograms of realistic-size models. The finite-difference method, the discontinuous-Galerkin method, and the spectral-element method are compared for a range of synthetic models having different levels of complexity such as topography, large subsurface features, low-velocity surface layers, and the location and characteristics of fault ruptures represented as an array of seismic sources. While some previous studies have already demonstrated that unstructured-mesh methods can sometimes tackle complex problems (Moczo et al.), we investigate the trade-off between unstructured-mesh methods and regular-grid methods for a broad range of models and source configurations. Finally, for comparison, our direct simulation results are briefly contrasted with those predicted by a few phenomenological ground-motion prediction equations, and a workflow for accurately predicting ground motion is proposed.

The HAMP Signal Relay Domain Adopts Multiple Conformational States through Collective Piston and Tilt Motions

PubMed Central

Zhu, Lizhe; Bolhuis, Peter G.; Vreede, Jocelyne

2013-01-01

The HAMP domain is a linker region in prokaryotic sensor proteins and relays input signals to the transmitter domain and vice versa. Functional as a dimer, the structure of HAMP shows a parallel coiled-coil motif comprising four helices. To date, it is unclear how HAMP can relay signals from one domain to another, although several models exist. In this work, we use molecular simulation to test the hypothesis that HAMP adopts different conformations, one of which represents an active, signal-relaying configuration, and another an inactive, resting state. We first performed molecular dynamics simulation on the prototype HAMP domain Af1503 from Archaeoglobus fulgidus. We explored its conformational space by taking the structure of the A291F mutant disabling HAMP activity as a starting point. These simulations revealed additional conformational states that differ in the tilt angles between the helices as well as the relative piston shifts of the helices relative to each other. By enhancing the sampling in a metadynamics set up, we investigated three mechanistic models for HAMP signal transduction. Our results indicate that HAMP can access additional conformational states characterized by piston motion. Furthermore, the piston motion of the N-terminal helix of one monomer is directly correlated with the opposite piston motion of the C-terminal helix of the other monomer. The change in piston motion is accompanied by a change in tilt angle between the monomers, thus revealing that HAMP exhibits a collective motion, i.e. a combination of changes in tilt angles and a piston-like displacement. Our results provide insights into the conformational changes that underlie the signaling mechanism involving HAMP. PMID:23468603

Computational model for amoeboid motion: Coupling membrane and cytosol dynamics

NASA Astrophysics Data System (ADS)

Moure, Adrian; Gomez, Hector

2016-10-01

A distinguishing feature of amoeboid motion is that the migrating cell undergoes large deformations, caused by the emergence and retraction of actin-rich protrusions, called pseudopods. Here, we propose a cell motility model that represents pseudopod dynamics, as well as its interaction with membrane signaling molecules. The model accounts for internal and external forces, such as protrusion, contraction, adhesion, surface tension, or those arising from cell-obstacle contacts. By coupling the membrane and cytosol interactions we are able to reproduce a realistic picture of amoeboid motion. The model results are in quantitative agreement with experiments and show how cells may take advantage of the geometry of their microenvironment to migrate more efficiently.

Discriminating Rigid from Nonrigid Motion

DTIC Science & Technology

1989-07-31

motion can be given a three-dimensional interpretation using a constraint of rigidity. Kruppa’s result and others (Faugeras & Maybank , 1989; Huang...Experimental Psychology: Human Perception and Performance, 10, 1-11. Faugeras, 0., & Maybank , S. (1989). Motion from point matches: multiplicity of

Quantitative relation between server motion and receiver anticipation in tennis: implications of responses to computer-simulated motions.

PubMed

Ida, Hirofumi; Fukuhara, Kazunobu; Sawada, Misako; Ishii, Motonobu

2011-01-01

The purpose of this study was to determine the quantitative relationships between the server's motion and the receiver's anticipation using a computer graphic animation of tennis serves. The test motions were determined by capturing the motion of a model player and estimating the computational perturbations caused by modulating the rotation of the player's elbow and forearm joints. Eight experienced and eight novice players rated their anticipation of the speed, direction, and spin of the ball on a visual analogue scale. The experienced players significantly altered some of their anticipatory judgment depending on the percentage of both the forearm and elbow modulations, while the novice players indicated no significant changes. Multiple regression analyses, including that of the racket's kinematic parameters immediately before racket-ball impact as independent variables, showed that the experienced players demonstrated a higher coefficient of determination than the novice players in their anticipatory judgment of the ball direction. The results have implications on the understanding of the functional relation between a player's motion and the opponent's anticipatory judgment during real play.

Parent-Child Talk about Motion: Links to Children's Development of Motion Event Language

ERIC Educational Resources Information Center

Hohenstein, Jill

2013-01-01

This study investigated the motion event language children and their parents engaged in while playing a board game. Children are sensitive to differences in manner and path at infancy, yet adult-like motion event expression appears relatively late in development. While multiple studies have examined how exposure to parent speech generally relates…

Recurrent network dynamics reconciles visual motion segmentation and integration.

PubMed

Medathati, N V Kartheek; Rankin, James; Meso, Andrew I; Kornprobst, Pierre; Masson, Guillaume S

2017-09-12

In sensory systems, a range of computational rules are presumed to be implemented by neuronal subpopulations with different tuning functions. For instance, in primate cortical area MT, different classes of direction-selective cells have been identified and related either to motion integration, segmentation or transparency. Still, how such different tuning properties are constructed is unclear. The dominant theoretical viewpoint based on a linear-nonlinear feed-forward cascade does not account for their complex temporal dynamics and their versatility when facing different input statistics. Here, we demonstrate that a recurrent network model of visual motion processing can reconcile these different properties. Using a ring network, we show how excitatory and inhibitory interactions can implement different computational rules such as vector averaging, winner-take-all or superposition. The model also captures ordered temporal transitions between these behaviors. In particular, depending on the inhibition regime the network can switch from motion integration to segmentation, thus being able to compute either a single pattern motion or to superpose multiple inputs as in motion transparency. We thus demonstrate that recurrent architectures can adaptively give rise to different cortical computational regimes depending upon the input statistics, from sensory flow integration to segmentation.

Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging.

PubMed

Jerome, N P; Orton, M R; d'Arcy, J A; Feiweier, T; Tunariu, N; Koh, D-M; Leach, M O; Collins, D J

2015-01-21

Respiratory motion commonly confounds abdominal diffusion-weighted magnetic resonance imaging, where averaging of successive samples at different parts of the respiratory cycle, performed in the scanner, manifests the motion as blurring of tissue boundaries and structural features and can introduce bias into calculated diffusion metrics. Storing multiple averages separately allows processing using metrics other than the mean; in this prospective volunteer study, median and trimmed mean values of signal intensity for each voxel over repeated averages and diffusion-weighting directions are shown to give images with sharper tissue boundaries and structural features for moving tissues, while not compromising non-moving structures. Expert visual scoring of derived diffusion maps is significantly higher for the median than for the mean, with modest improvement from the trimmed mean. Diffusion metrics derived from mono- and bi-exponential diffusion models are comparable for non-moving structures, demonstrating a lack of introduced bias from using the median. The use of the median is a simple and computationally inexpensive alternative to complex and expensive registration algorithms, requiring only additional data storage (and no additional scanning time) while returning visually superior images that will facilitate the appropriate placement of regions-of-interest when analysing abdominal diffusion-weighted magnetic resonance images, for assessment of disease characteristics and treatment response.

Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging

NASA Astrophysics Data System (ADS)

Jerome, N. P.; Orton, M. R.; d'Arcy, J. A.; Feiweier, T.; Tunariu, N.; Koh, D.-M.; Leach, M. O.; Collins, D. J.

2015-01-01

Respiratory motion commonly confounds abdominal diffusion-weighted magnetic resonance imaging, where averaging of successive samples at different parts of the respiratory cycle, performed in the scanner, manifests the motion as blurring of tissue boundaries and structural features and can introduce bias into calculated diffusion metrics. Storing multiple averages separately allows processing using metrics other than the mean; in this prospective volunteer study, median and trimmed mean values of signal intensity for each voxel over repeated averages and diffusion-weighting directions are shown to give images with sharper tissue boundaries and structural features for moving tissues, while not compromising non-moving structures. Expert visual scoring of derived diffusion maps is significantly higher for the median than for the mean, with modest improvement from the trimmed mean. Diffusion metrics derived from mono- and bi-exponential diffusion models are comparable for non-moving structures, demonstrating a lack of introduced bias from using the median. The use of the median is a simple and computationally inexpensive alternative to complex and expensive registration algorithms, requiring only additional data storage (and no additional scanning time) while returning visually superior images that will facilitate the appropriate placement of regions-of-interest when analysing abdominal diffusion-weighted magnetic resonance images, for assessment of disease characteristics and treatment response.

Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids.

PubMed

Leylavi Shoushtari, Ali

2016-01-01

Motion planning for humanoid robots is one of the critical issues due to the high redundancy and theoretical and technical considerations e.g. stability, motion feasibility and collision avoidance. The strategies which central nervous system employs to plan, signal and control the human movements are a source of inspiration to deal with the mentioned problems. Self-modeling is a concept inspired by body self-awareness in human. In this research it is integrated in an optimal motion planning framework in order to detect and avoid collision of the manipulated object with the humanoid body during performing a dynamic task. Twelve parametric functions are designed as self-models to determine the boundary of humanoid's body. Later, the boundaries which mathematically defined by the self-models are employed to calculate the safe region for box to avoid the collision with the robot. Four different objective functions are employed in motion simulation to validate the robustness of algorithm under different dynamics. The results also confirm the collision avoidance, reality and stability of the predicted motion.

Domain Motion Enhanced (DoME) Model for Efficient Conformational Sampling of Multidomain Proteins.

PubMed

Kobayashi, Chigusa; Matsunaga, Yasuhiro; Koike, Ryotaro; Ota, Motonori; Sugita, Yuji

2015-11-19

Large conformational changes of multidomain proteins are difficult to simulate using all-atom molecular dynamics (MD) due to the slow time scale. We show that a simple modification of the structure-based coarse-grained (CG) model enables a stable and efficient MD simulation of those proteins. "Motion Tree", a tree diagram that describes conformational changes between two structures in a protein, provides information on rigid structural units (domains) and the magnitudes of domain motions. In our new CG model, which we call the DoME (domain motion enhanced) model, interdomain interactions are defined as being inversely proportional to the magnitude of the domain motions in the diagram, whereas intradomain interactions are kept constant. We applied the DoME model in combination with the Go model to simulations of adenylate kinase (AdK). The results of the DoME-Go simulation are consistent with an all-atom MD simulation for 10 μs as well as known experimental data. Unlike the conventional Go model, the DoME-Go model yields stable simulation trajectories against temperature changes and conformational transitions are easily sampled despite domain rigidity. Evidently, identification of domains and their interfaces is useful approach for CG modeling of multidomain proteins.

Ground-motion modeling of Hayward fault scenario earthquakes, part II: Simulation of long-period and broadband ground motions

USGS Publications Warehouse

Aagaard, Brad T.; Graves, Robert W.; Rodgers, Arthur; Brocher, Thomas M.; Simpson, Robert W.; Dreger, Douglas; Petersson, N. Anders; Larsen, Shawn C.; Ma, Shuo; Jachens, Robert C.

2010-01-01

We simulate long-period (T>1.0–2.0 s) and broadband (T>0.1 s) ground motions for 39 scenario earthquakes (Mw 6.7–7.2) involving the Hayward, Calaveras, and Rodgers Creek faults. For rupture on the Hayward fault, we consider the effects of creep on coseismic slip using two different approaches, both of which reduce the ground motions, compared with neglecting the influence of creep. Nevertheless, the scenario earthquakes generate strong shaking throughout the San Francisco Bay area, with about 50% of the urban area experiencing modified Mercalli intensity VII or greater for the magnitude 7.0 scenario events. Long-period simulations of the 2007 Mw 4.18 Oakland earthquake and the 2007 Mw 5.45 Alum Rock earthquake show that the U.S. Geological Survey’s Bay Area Velocity Model version 08.3.0 permits simulation of the amplitude and duration of shaking throughout the San Francisco Bay area for Hayward fault earthquakes, with the greatest accuracy in the Santa Clara Valley (San Jose area). The ground motions for the suite of scenarios exhibit a strong sensitivity to the rupture length (or magnitude), hypocenter (or rupture directivity), and slip distribution. The ground motions display a much weaker sensitivity to the rise time and rupture speed. Peak velocities, peak accelerations, and spectral accelerations from the synthetic broadband ground motions are, on average, slightly higher than the Next Generation Attenuation (NGA) ground-motion prediction equations. We attribute much of this difference to the seismic velocity structure in the San Francisco Bay area and how the NGA models account for basin amplification; the NGA relations may underpredict amplification in shallow sedimentary basins. The simulations also suggest that the Spudich and Chiou (2008) directivity corrections to the NGA relations could be improved by increasing the areal extent of rupture directivity with period.

Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis

PubMed Central

Balto, Julia M; Kinnett-Hopkins, Dominique L

2016-01-01

Background There is increased interest in the application of smartphone applications and wearable motion sensors among multiple sclerosis (MS) patients. Objective This study examined the accuracy and precision of common smartphone applications and motion sensors for measuring steps taken by MS patients while walking on a treadmill. Methods Forty-five MS patients (Expanded Disability Status Scale (EDSS) = 1.0–5.0) underwent two 500-step walking trials at comfortable walking speed on a treadmill. Participants wore five motion sensors: the Digi-Walker SW-200 pedometer (Yamax), the UP2 and UP Move (Jawbone), and the Flex and One (Fitbit). The smartphone applications were Health (Apple), Health Mate (Withings), and Moves (ProtoGeo Oy). Results The Fitbit One had the best absolute (mean = 490.6 steps, 95% confidence interval (CI) = 485.6–495.5 steps) and relative accuracy (1.9% error), and absolute (SD = 16.4) and relative precision (coefficient of variation (CV) = 0.0), for the first 500-step walking trial; this was repeated with the second trial. Relative accuracy was correlated with slower walking speed for the first (rs = −.53) and second (rs = −.53) trials. Conclusion The results suggest that the waist-worn Fitbit One is the most precise and accurate sensor for measuring steps when walking on a treadmill, but future research is needed (testing the device across a broader range of disability, at different speeds, and in real-life walking conditions) before inclusion in clinical research and practice with MS patients. PMID:28607720

Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis.

PubMed

Balto, Julia M; Kinnett-Hopkins, Dominique L; Motl, Robert W

2016-01-01

There is increased interest in the application of smartphone applications and wearable motion sensors among multiple sclerosis (MS) patients. This study examined the accuracy and precision of common smartphone applications and motion sensors for measuring steps taken by MS patients while walking on a treadmill. Forty-five MS patients (Expanded Disability Status Scale (EDSS) = 1.0-5.0) underwent two 500-step walking trials at comfortable walking speed on a treadmill. Participants wore five motion sensors: the Digi-Walker SW-200 pedometer (Yamax), the UP2 and UP Move (Jawbone), and the Flex and One (Fitbit). The smartphone applications were Health (Apple), Health Mate (Withings), and Moves (ProtoGeo Oy). The Fitbit One had the best absolute (mean = 490.6 steps, 95% confidence interval (CI) = 485.6-495.5 steps) and relative accuracy (1.9% error), and absolute (SD = 16.4) and relative precision (coefficient of variation (CV) = 0.0), for the first 500-step walking trial; this was repeated with the second trial. Relative accuracy was correlated with slower walking speed for the first ( r s  =  -.53) and second ( r s  =  -.53) trials. The results suggest that the waist-worn Fitbit One is the most precise and accurate sensor for measuring steps when walking on a treadmill, but future research is needed (testing the device across a broader range of disability, at different speeds, and in real-life walking conditions) before inclusion in clinical research and practice with MS patients.

Using an external surrogate for predictor model training in real-time motion management of lung tumors.

PubMed

Rottmann, Joerg; Berbeco, Ross

2014-12-01

Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal-external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of

Validation of attenuation models for ground motion applications in central and eastern North America

DOE PAGES

Pasyanos, Michael E.

2015-11-01

Recently developed attenuation models are incorporated into standard one-dimensional (1-D) ground motion prediction equations (GMPEs), effectively making them two-dimensional (2-D) and eliminating the need to create different GMPEs for an increasing number of sub-regions. The model is tested against a data set of over 10,000 recordings from 81 earthquakes in North America. The use of attenuation models in GMPEs improves our ability to fit observed ground motions and should be incorporated into future national hazard maps. The improvement is most significant at higher frequencies and longer distances which have a greater number of wave cycles. This has implications for themore » rare high-magnitude earthquakes, which produce potentially damaging ground motions over wide areas, and drive the seismic hazards. Furthermore, the attenuation models can be created using weak ground motions, they could be developed for regions of low seismicity where empirical recordings of ground motions are uncommon and do not span the full range of magnitudes and distances.« less

Hybrid broadband Ground Motion simulation based on a dynamic rupture model of the 2011 Mw 9.0 Tohoku earthquake.

NASA Astrophysics Data System (ADS)

Galvez, P.; Somerville, P.; Bayless, J.; Dalguer, L. A.

2015-12-01

The rupture process of the 2011 Tohoku earthquake exhibits depth-dependent variations in the frequency content of seismic radiation from the plate interface. This depth-varying rupture property has also been observed in other subduction zones (Lay et al, 2012). During the Tohoku earthquake, the shallow region radiated coherent low frequency seismic waves whereas the deeper region radiated high frequency waves. Several kinematic inversions (Suzuki et al, 2011; Lee et al, 2011; Bletery et al, 2014; Minson et al, 2014) detected seismic waves below 0.1 Hz coming from the shallow depths that produced slip larger than 40-50 meters close to the trench. Using empirical green functions, Asano & Iwata (2012), Kurahashi and Irikura (2011) and others detected regions of strong ground motion radiation at frequencies up to 10Hz located mainly at the bottom of the plate interface. A recent dynamic model that embodies this depth-dependent radiation using physical models has been developed by Galvez et al (2014, 2015). In this model the rupture process is modeled using a linear weakening friction law with slip reactivation on the shallow region of the plate interface (Galvez et al, 2015). This model reproduces the multiple seismic wave fronts recorded on the Kik-net seismic network along the Japanese coast up to 0.1 Hz as well as the GPS displacements. In the deep region, the rupture sequence is consistent with the sequence of the strong ground motion generation areas (SMGAs) that radiate high frequency ground motion at the bottom of the plate interface (Kurahashi and Irikura, 2013). It remains challenging to perform ground motions fully coupled with a dynamic rupture up to 10 Hz for a megathrust event. Therefore, to generate high frequency ground motions, we make use of the stochastic approach of Graves and Pitarka (2010) but add to the source spectrum the slip rate function of the dynamic model. In this hybrid-dynamic approach, the slip rate function is windowed with Gaussian

Construction of Source Model of Huge Subduction Earthquakes for Strong Ground Motion Prediction

NASA Astrophysics Data System (ADS)

Iwata, T.; Asano, K.; Kubo, H.

2013-12-01

It is a quite important issue for strong ground motion prediction to construct the source model of huge subduction earthquakes. Iwata and Asano (2012, AGU) summarized the scaling relationships of large slip area of heterogeneous slip model and total SMGA sizes on seismic moment for subduction earthquakes and found the systematic change between the ratio of SMGA to the large slip area and the seismic moment. They concluded this tendency would be caused by the difference of period range of source modeling analysis. In this paper, we try to construct the methodology of construction of the source model for strong ground motion prediction for huge subduction earthquakes. Following to the concept of the characterized source model for inland crustal earthquakes (Irikura and Miyake, 2001; 2011) and intra-slab earthquakes (Iwata and Asano, 2011), we introduce the proto-type of the source model for huge subduction earthquakes and validate the source model by strong ground motion modeling.

Elastic network model of learned maintained contacts to predict protein motion

PubMed Central

Putz, Ines

2017-01-01

We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein’s contact topology. Existing elastic network models assume that the contact topology remains unchanged throughout the motion and are thus most appropriate to simulate highly collective function-related movements. lmcENM uses machine learning to differentiate breaking from maintained contacts. We show that lmcENM accurately captures functional transitions unexplained by the classical ENM and three reference ENM variants, while preserving the simplicity of classical ENM. We demonstrate the effectiveness of our approach on a large set of proteins covering different motion types. Our results suggest that accurately predicting a “deformation-invariant” contact topology offers a promising route to increase the general applicability of ENMs. We also find that to correctly predict this contact topology a combination of several features seems to be relevant which may vary slightly depending on the protein. Additionally, we present case studies of two biologically interesting systems, Ferric Citrate membrane transporter FecA and Arachidonate 15-Lipoxygenase. PMID:28854238

The effects of rigid motions on elastic network model force constants.

PubMed

Lezon, Timothy R

2012-04-01

Elastic network models provide an efficient way to quickly calculate protein global dynamics from experimentally determined structures. The model's single parameter, its force constant, determines the physical extent of equilibrium fluctuations. The values of force constants can be calculated by fitting to experimental data, but the results depend on the type of experimental data used. Here, we investigate the differences between calculated values of force constants and data from NMR and X-ray structures. We find that X-ray B factors carry the signature of rigid-body motions, to the extent that B factors can be almost entirely accounted for by rigid motions alone. When fitting to more refined anisotropic temperature factors, the contributions of rigid motions are significantly reduced, indicating that the large contribution of rigid motions to B factors is a result of over-fitting. No correlation is found between force constants fit to NMR data and those fit to X-ray data, possibly due to the inability of NMR data to accurately capture protein dynamics. Copyright © 2011 Wiley Periodicals, Inc.

Sampled-data-based consensus and containment control of multiple harmonic oscillators: A motion-planning approach

NASA Astrophysics Data System (ADS)

Liu, Yongfang; Zhao, Yu; Chen, Guanrong

2016-11-01

This paper studies the distributed consensus and containment problems for a group of harmonic oscillators with a directed communication topology. First, for consensus without a leader, a class of distributed consensus protocols is designed by using motion planning and Pontryagin's principle. The proposed protocol only requires relative information measurements at the sampling instants, without requiring information exchange over the sampled interval. By using stability theory and the properties of stochastic matrices, it is proved that the distributed consensus problem can be solved in the motion planning framework. Second, for the case with multiple leaders, a class of distributed containment protocols is developed for followers such that their positions and velocities can ultimately converge to the convex hull formed by those of the leaders. Compared with the existing consensus algorithms, a remarkable advantage of the proposed sampled-data-based protocols is that the sampling periods, communication topologies and control gains are all decoupled and can be separately designed, which relaxes many restrictions in controllers design. Finally, some numerical examples are given to illustrate the effectiveness of the analytical results.

Mathematical model for the simulation of Dynamic Docking Test System (DDST) active table motion

NASA Technical Reports Server (NTRS)

Gates, R. M.; Graves, D. L.

1974-01-01

The mathematical model developed to describe the three-dimensional motion of the dynamic docking test system active table is described. The active table is modeled as a rigid body supported by six flexible hydraulic actuators which produce the commanded table motions.

Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model.

PubMed

Hertanto, Agung; Zhang, Qinghui; Hu, Yu-Chi; Dzyubak, Oleksandr; Rimner, Andreas; Mageras, Gig S

2012-06-01

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase

Multiple brain networks for visual self-recognition with different sensitivity for motion and body part.

PubMed

Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Miura, Naoki; Akitsuki, Yuko; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2006-10-01

Multiple brain networks may support visual self-recognition. It has been hypothesized that the left ventral occipito-temporal cortex processes one's own face as a symbol, and the right parieto-frontal network processes self-image in association with motion-action contingency. Using functional magnetic resonance imaging, we first tested these hypotheses based on the prediction that these networks preferentially respond to a static self-face and to moving one's whole body, respectively. Brain activation specifically related to self-image during familiarity judgment was compared across four stimulus conditions comprising a two factorial design: factor Motion contrasted picture (Picture) and movie (Movie), and factor Body part a face (Face) and whole body (Body). Second, we attempted to segregate self-specific networks using a principal component analysis (PCA), assuming an independent pattern of inter-subject variability in activation over the four stimulus conditions in each network. The bilateral ventral occipito-temporal and the right parietal and frontal cortices exhibited self-specific activation. The left ventral occipito-temporal cortex exhibited greater self-specific activation for Face than for Body, in Picture, consistent with the prediction for this region. The activation profiles of the right parietal and frontal cortices did not show preference for Movie Body predicted by the assumed roles of these regions. The PCA extracted two cortical networks, one with its peaks in the right posterior, and another in frontal cortices; their possible roles in visuo-spatial and conceptual self-representations, respectively, were suggested by previous findings. The results thus supported and provided evidence of multiple brain networks for visual self-recognition.

Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

PubMed

Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

2017-07-01

Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

A Pilot/Vehicle Model Analysis of the Effects of Motion Cues on Harrier Control Tasks.

DTIC Science & Technology

1983-09-01

7 D- R136 291 A PILOT/VEHILE MODEL ANALYSIS OF THE EFFECTS OF MOTION i/i LS 91 CUES ON HARRIER C..(U) BOLT BERANEK AND NEWMAN INC CAMBRIDGE MA S...provided by well-designed platform motion systems , the actual rovement of performance or training effectiveness that results from incorporating these...for the Harrier AV-8B. The effects of providing motion cues via an idealized platform motion system or a g-seat device are predicted with the model, and

Analytical approach to calculation of response spectra from seismological models of ground motion

USGS Publications Warehouse

Safak, Erdal

1988-01-01

An analytical approach to calculate response spectra from seismological models of ground motion is presented. Seismological models have three major advantages over empirical models: (1) they help in an understanding of the physics of earthquake mechanisms, (2) they can be used to predict ground motions for future earthquakes and (3) they can be extrapolated to cases where there are no data available. As shown with this study, these models also present a convenient form for the calculation of response spectra, by using the methods of random vibration theory, for a given magnitude and site conditions. The first part of the paper reviews the past models for ground motion description, and introduces the available seismological models. Then, the random vibration equations for the spectral response are presented. The nonstationarity, spectral bandwidth and the correlation of the peaks are considered in the calculation of the peak response.

One-degree-of-freedom spherical model for the passive motion of the human ankle joint.

PubMed

Sancisi, Nicola; Baldisserri, Benedetta; Parenti-Castelli, Vincenzo; Belvedere, Claudio; Leardini, Alberto

2014-04-01

Mathematical modelling of mobility at the human ankle joint is essential for prosthetics and orthotic design. The scope of this study is to show that the ankle joint passive motion can be represented by a one-degree-of-freedom spherical motion. Moreover, this motion is modelled by a one-degree-of-freedom spherical parallel mechanism model, and the optimal pivot-point position is determined. Passive motion and anatomical data were taken from in vitro experiments in nine lower limb specimens. For each of these, a spherical mechanism, including the tibiofibular and talocalcaneal segments connected by a spherical pair and by the calcaneofibular and tibiocalcaneal ligament links, was defined from the corresponding experimental kinematics and geometry. An iterative procedure was used to optimize the geometry of the model, able to predict original experimental motion. The results of the simulations showed a good replication of the original natural motion, despite the numerous model assumptions and simplifications, with mean differences between experiments and predictions smaller than 1.3 mm (average 0.33 mm) for the three joint position components and smaller than 0.7° (average 0.32°) for the two out-of-sagittal plane rotations, once plotted versus the full flexion arc. The relevant pivot-point position after model optimization was found within the tibial mortise, but not exactly in a central location. The present combined experimental and modelling analysis of passive motion at the human ankle joint shows that a one degree-of-freedom spherical mechanism predicts well what is observed in real joints, although its computational complexity is comparable to the standard hinge joint model.

The importance of being equivalent: Newton's two models of one-body motion

NASA Astrophysics Data System (ADS)

Pourciau, Bruce

2004-05-01

As an undergraduate at Cambridge, Newton entered into his "Waste Book" an assumption that we have named the Equivalence Assumption (The Younger): "If a body move progressively in some crooked line [about a center of motion] ..., [then this] crooked line may bee conceived to consist of an infinite number of streight lines. Or else in any point of the croked line the motion may bee conceived to be on in the tangent". In this assumption, Newton somewhat imprecisely describes two mathematical models, a "polygonal limit model" and a "tangent deflected model", for "one-body motion", that is, for the motion of a "body in orbit about a fixed center", and then claims that these two models are equivalent. In the first part of this paper, we study the Principia to determine how the elder Newton would more carefully describe the polygonal limit and tangent deflected models. From these more careful descriptions, we then create Equivalence Assumption (The Elder), a precise interpretation of Equivalence Assumption (The Younger) as it might have been restated by Newton, after say 1687. We then review certain portions of the Waste Book and the Principia to make the case that, although Newton never restates nor even alludes to the Equivalence Assumption after his youthful Waste Book entry, still the polygonal limit and tangent deflected models, as well as an unspoken belief in their equivalence, infuse Newton's work on orbital motion. In particular, we show that the persuasiveness of the argument for the Area Property in Proposition 1 of the Principia depends crucially on the validity of Equivalence Assumption (The Elder). After this case is made, we present the mathematical analysis required to establish the validity of the Equivalence Assumption (The Elder). Finally, to illustrate the fundamental nature of the resulting theorem, the Equivalence Theorem as we call it, we present three significant applications: we use the Equivalence Theorem first to clarify and resolve questions

Assessment of terrestrial water contributions to polar motion from GRACE and hydrological models

NASA Astrophysics Data System (ADS)

Jin, S. G.; Hassan, A. A.; Feng, G. P.

2012-12-01

The hydrological contribution to polar motion is a major challenge in explaining the observed geodetic residual of non-atmospheric and non-oceanic excitations since hydrological models have limited input of comprehensive global direct observations. Although global terrestrial water storage (TWS) estimated from the Gravity Recovery and Climate Experiment (GRACE) provides a new opportunity to study the hydrological excitation of polar motion, the GRACE gridded data are subject to the post-processing de-striping algorithm, spatial gridded mapping and filter smoothing effects as well as aliasing errors. In this paper, the hydrological contributions to polar motion are investigated and evaluated at seasonal and intra-seasonal time scales using the recovered degree-2 harmonic coefficients from all GRACE spherical harmonic coefficients and hydrological models data with the same filter smoothing and recovering methods, including the Global Land Data Assimilation Systems (GLDAS) model, Climate Prediction Center (CPC) model, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis products and European Center for Medium-Range Weather Forecasts (ECMWF) operational model (opECMWF). It is shown that GRACE is better in explaining the geodetic residual of non-atmospheric and non-oceanic polar motion excitations at the annual period, while the models give worse estimates with a larger phase shift or amplitude bias. At the semi-annual period, the GRACE estimates are also generally closer to the geodetic residual, but with some biases in phase or amplitude due mainly to some aliasing errors at near semi-annual period from geophysical models. For periods less than 1-year, the hydrological models and GRACE are generally worse in explaining the intraseasonal polar motion excitations.

Quantum Brownian motion model for the stock market

NASA Astrophysics Data System (ADS)

Meng, Xiangyi; Zhang, Jian-Wei; Guo, Hong

2016-06-01

It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysical framework for the stock market, based on which we analogously map massive numbers of single stocks into a reservoir consisting of many quantum harmonic oscillators and their stock index into a typical quantum open system-a quantum Brownian particle. In particular, the irrationality of stock transactions is quantitatively considered as the Planck constant within Heisenberg's uncertainty relationship of quantum mechanics in an analogous manner. We analyze real stock data of Shanghai Stock Exchange of China and investigate fat-tail phenomena and non-Markovian behaviors of the stock index with the assistance of the quantum Brownian motion model, thereby interpreting and studying the limitations of the classical Brownian motion model for the efficient market hypothesis from a new perspective of quantum open system dynamics.

ARMA models for earthquake ground motions. Seismic safety margins research program

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

Chang, M. K.; Kwiatkowski, J. W.; Nau, R. F.

1981-02-01

Four major California earthquake records were analyzed by use of a class of discrete linear time-domain processes commonly referred to as ARMA (Autoregressive/Moving-Average) models. It was possible to analyze these different earthquakes, identify the order of the appropriate ARMA model(s), estimate parameters, and test the residuals generated by these models. It was also possible to show the connections, similarities, and differences between the traditional continuous models (with parameter estimates based on spectral analyses) and the discrete models with parameters estimated by various maximum-likelihood techniques applied to digitized acceleration data in the time domain. The methodology proposed is suitable for simulatingmore » earthquake ground motions in the time domain, and appears to be easily adapted to serve as inputs for nonlinear discrete time models of structural motions. 60 references, 19 figures, 9 tables.« less

A heuristic mathematical model for the dynamics of sensory conflict and motion sickness

NASA Technical Reports Server (NTRS)

Oman, C. M.

1982-01-01

By consideration of the information processing task faced by the central nervous system in estimating body spatial orientation and in controlling active body movement using an internal model referenced control strategy, a mathematical model for sensory conflict generation is developed. The model postulates a major dynamic functional role for sensory conflict signals in movement control, as well as in sensory-motor adaptation. It accounts for the role of active movement in creating motion sickness symptoms in some experimental circumstance, and in alleviating them in others. The relationship between motion sickness produced by sensory rearrangement and that resulting from external motion disturbances is explicitly defined. A nonlinear conflict averaging model is proposed which describes dynamic aspects of experimentally observed subjective discomfort sensation, and suggests resulting behaviours. The model admits several possibilities for adaptive mechanisms which do not involve internal model updating. Further systematic efforts to experimentally refine and validate the model are indicated.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

PubMed

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

Multiple Indicators, Multiple Causes Measurement Error Models

PubMed Central

Tekwe, Carmen D.; Carter, Randy L.; Cullings, Harry M.; Carroll, Raymond J.

2014-01-01

Multiple Indicators, Multiple Causes Models (MIMIC) are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times however when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this paper are: (1) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model, (2) to develop likelihood based estimation methods for the MIMIC ME model, (3) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. As a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure. PMID:24962535

Modeling the influence of plate motions on subduction

NASA Astrophysics Data System (ADS)

Hillebrand, Bram; Thieulot, Cedric; van den Berg, Arie; Spakman, Wim

2014-05-01

Subduction zones are widely studied complex geodynamical systems. Their evolution is influenced by a broad range of parameters such as the age of the plates (both subducting and overriding) as well as their rheology, their nature (oceanic or continental), the presence of a crust and the involved plate motions to name a few. To investigate the importance of these different parameters on the evolution of subduction we have created a series of 2D numerical thermomechanical subduction models. These subduction models are multi-material flow models containing continental and oceanic crusts, a lithosphere and a mantle. We use the sticky air approach to allow for topography build up in the model. In order to model multi-material flow in our Eulerian finite element code of SEPRAN (Segal and Praagman, 2000) we use the well benchmarked level set method (Osher and Sethian, 1988) to track the different materials and their mode of deformation through the model domain. To our knowledge the presented results are the first subduction model results with the level set method. We will present preliminary results of our parametric study focusing mainly on the influence of plate motions on the evolution of subduction. S. Osher and J.A. Sethian. Fronts propagating with curvature-dependent speed: Algorithms based on hamilton-jacobi formulations. JCP 1988 A. Segal and N.P. Praagman. The SEPRAN package. Technical report, 2000 This research is funded by The Netherlands Research Centre for Integrated Solid Earth Science (ISES)

Lumbar joint torque estimation based on simplified motion measurement using multiple inertial sensors.

PubMed

Miyajima, Saori; Tanaka, Takayuki; Imamura, Yumeko; Kusaka, Takashi

2015-01-01

We estimate lumbar torque based on motion measurement using only three inertial sensors. First, human motion is measured by a 6-axis motion tracking device that combines a 3-axis accelerometer and a 3-axis gyroscope placed on the shank, thigh, and back. Next, the lumbar joint torque during the motion is estimated by kinematic musculoskeletal simulation. The conventional method for estimating joint torque uses full body motion data measured by an optical motion capture system. However, in this research, joint torque is estimated by using only three link angles of the body, thigh, and shank. The utility of our method was verified by experiments. We measured motion of bendung knee and waist simultaneously. As the result, we were able to estimate the lumbar joint torque from measured motion.

SU-G-BRA-17: Tracking Multiple Targets with Independent Motion in Real-Time Using a Multi-Leaf Collimator

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

Ge, Y; Keall, P; Poulsen, P

Purpose: Multiple targets with large intrafraction independent motion are often involved in advanced prostate, lung, abdominal, and head and neck cancer radiotherapy. Current standard of care treats these with the originally planned fields, jeopardizing the treatment outcomes. A real-time multi-leaf collimator (MLC) tracking method has been developed to address this problem for the first time. This study evaluates the geometric uncertainty of the multi-target tracking method. Methods: Four treatment scenarios are simulated based on a prostate IMAT plan to treat a moving prostate target and static pelvic node target: 1) real-time multi-target MLC tracking; 2) real-time prostate-only MLC tracking; 3)more » correcting for prostate interfraction motion at setup only; and 4) no motion correction. The geometric uncertainty of the treatment is assessed by the sum of the erroneously underexposed target area and overexposed healthy tissue areas for each individual target. Two patient-measured prostate trajectories of average 2 and 5 mm motion magnitude are used for simulations. Results: Real-time multi-target tracking accumulates the least uncertainty overall. As expected, it covers the static nodes similarly well as no motion correction treatment and covers the moving prostate similarly well as the real-time prostate-only tracking. Multi-target tracking reduces >90% of uncertainty for the static nodal target compared to the real-time prostate-only tracking or interfraction motion correction. For prostate target, depending on the motion trajectory which affects the uncertainty due to leaf-fitting, multi-target tracking may or may not perform better than correcting for interfraction prostate motion by shifting patient at setup, but it reduces ∼50% of uncertainty compared to no motion correction. Conclusion: The developed real-time multi-target MLC tracking can adapt for the independently moving targets better than other available treatment adaptations. This will enable

Object instance recognition using motion cues and instance specific appearance models

NASA Astrophysics Data System (ADS)

Schumann, Arne

2014-03-01

In this paper we present an object instance retrieval approach. The baseline approach consists of a pool of image features which are computed on the bounding boxes of a query object track and compared to a database of tracks in order to find additional appearances of the same object instance. We improve over this simple baseline approach in multiple ways: 1) we include motion cues to achieve improved robustness to viewpoint and rotation changes, 2) we include operator feedback to iteratively re-rank the resulting retrieval lists and 3) we use operator feedback and location constraints to train classifiers and learn an instance specific appearance model. We use these classifiers to further improve the retrieval results. The approach is evaluated on two popular public datasets for two different applications. We evaluate person re-identification on the CAVIAR shopping mall surveillance dataset and vehicle instance recognition on the VIVID aerial dataset and achieve significant improvements over our baseline results.

A novel Bayesian respiratory motion model to estimate and resolve uncertainty in image-guided cardiac interventions.

PubMed

Peressutti, Devis; Penney, Graeme P; Housden, R James; Kolbitsch, Christoph; Gomez, Alberto; Rijkhorst, Erik-Jan; Barratt, Dean C; Rhode, Kawal S; King, Andrew P

2013-05-01

In image-guided cardiac interventions, respiratory motion causes misalignments between the pre-procedure roadmap of the heart used for guidance and the intra-procedure position of the heart, reducing the accuracy of the guidance information and leading to potentially dangerous consequences. We propose a novel technique for motion-correcting the pre-procedural information that combines a probabilistic MRI-derived affine motion model with intra-procedure real-time 3D echocardiography (echo) images in a Bayesian framework. The probabilistic model incorporates a measure of confidence in its motion estimates which enables resolution of the potentially conflicting information supplied by the model and the echo data. Unlike models proposed so far, our method allows the final motion estimate to deviate from the model-produced estimate according to the information provided by the echo images, so adapting to the complex variability of respiratory motion. The proposed method is evaluated using gold-standard MRI-derived motion fields and simulated 3D echo data for nine volunteers and real 3D live echo images for four volunteers. The Bayesian method is compared to 5 other motion estimation techniques and results show mean/max improvements in estimation accuracy of 10.6%/18.9% for simulated echo images and 20.8%/41.5% for real 3D live echo data, over the best comparative estimation method. Copyright © 2013 Elsevier B.V. All rights reserved.

Dependence of subject-specific parameters for a fast helical CT respiratory motion model on breathing rate: an animal study

NASA Astrophysics Data System (ADS)

O'Connell, Dylan; Thomas, David H.; Lamb, James M.; Lewis, John H.; Dou, Tai; Sieren, Jered P.; Saylor, Melissa; Hofmann, Christian; Hoffman, Eric A.; Lee, Percy P.; Low, Daniel A.

2018-02-01

To determine if the parameters relating lung tissue displacement to a breathing surrogate signal in a previously published respiratory motion model vary with the rate of breathing during image acquisition. An anesthetized pig was imaged using multiple fast helical scans to sample the breathing cycle with simultaneous surrogate monitoring. Three datasets were collected while the animal was mechanically ventilated with different respiratory rates: 12 bpm (breaths per minute), 17 bpm, and 24 bpm. Three sets of motion model parameters describing the correspondences between surrogate signals and tissue displacements were determined. The model error was calculated individually for each dataset, as well asfor pairs of parameters and surrogate signals from different experiments. The values of one model parameter, a vector field denoted α which related tissue displacement to surrogate amplitude, determined for each experiment were compared. The mean model error of the three datasets was 1.00  ±  0.36 mm with a 95th percentile value of 1.69 mm. The mean error computed from all combinations of parameters and surrogate signals from different datasets was 1.14  ±  0.42 mm with a 95th percentile of 1.95 mm. The mean difference in α over all pairs of experiments was 4.7%  ±  5.4%, and the 95th percentile was 16.8%. The mean angle between pairs of α was 5.0  ±  4.0 degrees, with a 95th percentile of 13.2 mm. The motion model parameters were largely unaffected by changes in the breathing rate during image acquisition. The mean error associated with mismatched sets of parameters and surrogate signals was 0.14 mm greater than the error achieved when using parameters and surrogate signals acquired with the same breathing rate, while maximum respiratory motion was 23.23 mm on average.

General relativistic satellite astrometry. II. Modeling parallax and proper motion

NASA Astrophysics Data System (ADS)

de Felice, F.; Bucciarelli, B.; Lattanzi, M. G.; Vecchiato, A.

2001-07-01

The non-perturbative general relativistic approach to global astrometry introduced by de Felice et al. (\\cite{defetal}) is here extended to account for the star motions on the Schwarzschild celestial sphere. A new expression of the observables, i.e. angular distances among stars, is provided, which takes into account the effects of parallax and proper motions. This dynamical model is then tested on an end-to-end simulation of the global astrometry mission GAIA. The results confirm the findings of our earlier work, which applied to the case of a static (angular coordinates only) sphere. In particular, measurements of large arcs among stars (each measurement good to ~ 100 mu arcsec, as expected for V ~ 17 mag stars) repeated over an observing period comparable to the mission lifetime foreseen for GAIA, can be modeled to yield estimates of positions, parallaxes, and annual proper motions good to ~ 15 mu arcsec. This second round of experiments confirms, within the limitations of the simulation and the assumptions of the current relativistic model, that the space-born global astrometry initiated with Hipparcos can be pushed down to the 10-5 arcsec accuracy level proposed with the GAIA mission. Finally, the simplified case we have solved can be used as reference for testing the limiting behavior of more realistic models as they become available.

Nuclear quadrupole resonance lineshape analysis for different motional models: Stochastic Liouville approach

NASA Astrophysics Data System (ADS)

Kruk, D.; Earle, K. A.; Mielczarek, A.; Kubica, A.; Milewska, A.; Moscicki, J.

2011-12-01

A general theory of lineshapes in nuclear quadrupole resonance (NQR), based on the stochastic Liouville equation, is presented. The description is valid for arbitrary motional conditions (particularly beyond the valid range of perturbation approaches) and interaction strengths. It can be applied to the computation of NQR spectra for any spin quantum number and for any applied magnetic field. The treatment presented here is an adaptation of the "Swedish slow motion theory," [T. Nilsson and J. Kowalewski, J. Magn. Reson. 146, 345 (2000), 10.1006/jmre.2000.2125] originally formulated for paramagnetic systems, to NQR spectral analysis. The description is formulated for simple (Brownian) diffusion, free diffusion, and jump diffusion models. The two latter models account for molecular cooperativity effects in dense systems (such as liquids of high viscosity or molecular glasses). The sensitivity of NQR slow motion spectra to the mechanism of the motional processes modulating the nuclear quadrupole interaction is discussed.

A multiple fault rupture model of the November 13 2016, M 7.8 Kaikoura earthquake, New Zealand

NASA Astrophysics Data System (ADS)

Benites, R. A.; Francois-Holden, C.; Langridge, R. M.; Kaneko, Y.; Fry, B.; Kaiser, A. E.; Caldwell, T. G.

2017-12-01

The rupture-history of the November 13 2016 MW7.8 Kaikoura earthquake recorded by near- and intermediate-field strong-motion seismometers and 2 high-rate GPS stations reveals a complex cascade of multiple crustal fault rupture. In spite of such complexity, we show that the rupture history of each fault is well approximated by simple kinematic model with uniform slip and rupture velocity. Using 9 faults embedded in a crustal layer 19 km thick, each with a prescribed slip vector and rupture velocity, this model accurately reproduces the displacement waveforms recorded at the near-field strong-motion and GPS stations. This model includes the `Papatea Fault' with a mixed thrust and strike-slip mechanism based on in-situ geological observations with up to 8 m of uplift observed. Although the kinematic model fits the ground-motion at the nearest strong station, it doesn not reproduce the one sided nature of the static deformation field observed geodetically. This suggests a dislocation based approach does not completely capture the mechanical response of the Papatea Fault. The fault system as a whole extends for approximately 150 km along the eastern side of the Marlborough fault system in the South Island of New Zealand. The total duration of the rupture was 74 seconds. The timing and location of each fault's rupture suggests fault interaction and triggering resulting in a northward cascade crustal ruptures. Our model does not require rupture of the underlying subduction interface to explain the data.

Seeing blur: 'motion sharpening' without motion.

PubMed Central

Georgeson, Mark A; Hammett, Stephen T

2002-01-01

It is widely supposed that things tend to look blurred when they are moving fast. Previous work has shown that this is true for sharp edges but, paradoxically, blurred edges look sharper when they are moving than when stationary. This is 'motion sharpening'. We show that blurred edges also look up to 50% sharper when they are presented briefly (8-24 ms) than at longer durations (100-500 ms) without motion. This argues strongly against high-level models of sharpening based specifically on compensation for motion blur. It also argues against a recent, low-level, linear filter model that requires motion to produce sharpening. No linear filter model can explain our finding that sharpening was similar for sinusoidal and non-sinusoidal gratings, since linear filters can never distort sine waves. We also conclude that the idea of a 'default' assumption of sharpness is not supported by experimental evidence. A possible source of sharpening is a nonlinearity in the contrast response of early visual mechanisms to fast or transient temporal changes, perhaps based on the magnocellular (M-cell) pathway. Our finding that sharpening is not diminished at low contrast sets strong constraints on the nature of the nonlinearity. PMID:12137571

Analyzing Multiple-Choice Questions by Model Analysis and Item Response Curves

NASA Astrophysics Data System (ADS)

Wattanakasiwich, P.; Ananta, S.

2010-07-01

In physics education research, the main goal is to improve physics teaching so that most students understand physics conceptually and be able to apply concepts in solving problems. Therefore many multiple-choice instruments were developed to probe students' conceptual understanding in various topics. Two techniques including model analysis and item response curves were used to analyze students' responses from Force and Motion Conceptual Evaluation (FMCE). For this study FMCE data from more than 1000 students at Chiang Mai University were collected over the past three years. With model analysis, we can obtain students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts. The model analysis consists of two algorithms—concentration factor and model estimation. This paper only presents results from using the model estimation algorithm to obtain a model plot. The plot helps to identify a class model state whether it is in the misconception region or not. Item response curve (IRC) derived from item response theory is a plot between percentages of students selecting a particular choice versus their total score. Pros and cons of both techniques are compared and discussed.

Blind motion image deblurring using nonconvex higher-order total variation model

NASA Astrophysics Data System (ADS)

Li, Weihong; Chen, Rui; Xu, Shangwen; Gong, Weiguo

2016-09-01

We propose a nonconvex higher-order total variation (TV) method for blind motion image deblurring. First, we introduce a nonconvex higher-order TV differential operator to define a new model of the blind motion image deblurring, which can effectively eliminate the staircase effect of the deblurred image; meanwhile, we employ an image sparse prior to improve the edge recovery quality. Second, to improve the accuracy of the estimated motion blur kernel, we use L1 norm and H1 norm as the blur kernel regularization term, considering the sparsity and smoothing of the motion blur kernel. Third, because it is difficult to solve the numerically computational complexity problem of the proposed model owing to the intrinsic nonconvexity, we propose a binary iterative strategy, which incorporates a reweighted minimization approximating scheme in the outer iteration, and a split Bregman algorithm in the inner iteration. And we also discuss the convergence of the proposed binary iterative strategy. Last, we conduct extensive experiments on both synthetic and real-world degraded images. The results demonstrate that the proposed method outperforms the previous representative methods in both quality of visual perception and quantitative measurement.

Multiple indicators, multiple causes measurement error models

DOE PAGES

Tekwe, Carmen D.; Carter, Randy L.; Cullings, Harry M.; ...

2014-06-25

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methodsmore » for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.« less

Multiple indicators, multiple causes measurement error models

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

Tekwe, Carmen D.; Carter, Randy L.; Cullings, Harry M.

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methodsmore » for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.« less

From deep TLS validation to ensembles of atomic models built from elemental motions

DOE PAGES

Urzhumtsev, Alexandre; Afonine, Pavel V.; Van Benschoten, Andrew H.; ...

2015-07-28

The translation–libration–screw model first introduced by Cruickshank, Schomaker and Trueblood describes the concerted motions of atomic groups. Using TLS models can improve the agreement between calculated and experimental diffraction data. Because the T, L and S matrices describe a combination of atomic vibrations and librations, TLS models can also potentially shed light on molecular mechanisms involving correlated motions. However, this use of TLS models in mechanistic studies is hampered by the difficulties in translating the results of refinement into molecular movement or a structural ensemble. To convert the matrices into a constituent molecular movement, the matrix elements must satisfy severalmore » conditions. Refining the T, L and S matrix elements as independent parameters without taking these conditions into account may result in matrices that do not represent concerted molecular movements. Here, a mathematical framework and the computational tools to analyze TLS matrices, resulting in either explicit decomposition into descriptions of the underlying motions or a report of broken conditions, are described. The description of valid underlying motions can then be output as a structural ensemble. All methods are implemented as part of the PHENIX project.« less

Asynchronous partial contact motion due to internal resonance in multiple degree-of-freedom rotordynamics

NASA Astrophysics Data System (ADS)

Shaw, A. D.; Champneys, A. R.; Friswell, M. I.

2016-08-01

Sudden onset of violent chattering or whirling rotor-stator contact motion in rotational machines can cause significant damage in many industrial applications. It is shown that internal resonance can lead to the onset of bouncing-type partial contact motion away from primary resonances. These partial contact limit cycles can involve any two modes of an arbitrarily high degree-of-freedom system, and can be seen as an extension of a synchronization condition previously reported for a single disc system. The synchronization formula predicts multiple drivespeeds, corresponding to different forms of mode-locked bouncing orbits. These results are backed up by a brute-force bifurcation analysis which reveals numerical existence of the corresponding family of bouncing orbits at supercritical drivespeeds, provided the damping is sufficiently low. The numerics reveal many overlapping families of solutions, which leads to significant multi-stability of the response at given drive speeds. Further, secondary bifurcations can also occur within each family, altering the nature of the response and ultimately leading to chaos. It is illustrated how stiffness and damping of the stator have a large effect on the number and nature of the partial contact solutions, illustrating the extreme sensitivity that would be observed in practice.

Bayesian approach to MSD-based analysis of particle motion in live cells.

PubMed

Monnier, Nilah; Guo, Syuan-Ming; Mori, Masashi; He, Jun; Lénárt, Péter; Bathe, Mark

2012-08-08

Quantitative tracking of particle motion using live-cell imaging is a powerful approach to understanding the mechanism of transport of biological molecules, organelles, and cells. However, inferring complex stochastic motion models from single-particle trajectories in an objective manner is nontrivial due to noise from sampling limitations and biological heterogeneity. Here, we present a systematic Bayesian approach to multiple-hypothesis testing of a general set of competing motion models based on particle mean-square displacements that automatically classifies particle motion, properly accounting for sampling limitations and correlated noise while appropriately penalizing model complexity according to Occam's Razor to avoid over-fitting. We test the procedure rigorously using simulated trajectories for which the underlying physical process is known, demonstrating that it chooses the simplest physical model that explains the observed data. Further, we show that computed model probabilities provide a reliability test for the downstream biological interpretation of associated parameter values. We subsequently illustrate the broad utility of the approach by applying it to disparate biological systems including experimental particle trajectories from chromosomes, kinetochores, and membrane receptors undergoing a variety of complex motions. This automated and objective Bayesian framework easily scales to large numbers of particle trajectories, making it ideal for classifying the complex motion of large numbers of single molecules and cells from high-throughput screens, as well as single-cell-, tissue-, and organism-level studies. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Measurement of Motion Transfer Functions for Mirror Suspensions

NASA Astrophysics Data System (ADS)

Stuver, Amber; Beilby, Mark; Glancy, Aran; Gonzalez, Gabriela

2001-04-01

Interferometric gravitational wave detectors, such as LIGO, use mirrors suspended in pendulums. The current LIGO dectors use simple pendulums, but advanced LIGO detectors will use multiple pendulums with some stages on soft vertical springs. A drawback of the a multiple pendulum design is that it is difficult to model and predict cross couplings from one vibrational mode to another due to slight unavoidable asymmetries in the real system. Of most concern are the couplings to motion along the optical axis and into angular motions, which have the most potential to contaminate data. Our research focuses on the experimental testing of the pendulum designs for cross couplings with a special dedicated shaking stage. The cross couplings in each degree of freedom, their isolation and damping are investigated in this research though the measurement of transfer functions as filtered though the suspension system. This research is supported by The Pennsylvania State University, the NSF Grant no. PHY-9870032, and the REU program at The Pennsylvania State University.

A variational reconstruction method for undersampled dynamic x-ray tomography based on physical motion models

NASA Astrophysics Data System (ADS)

Burger, Martin; Dirks, Hendrik; Frerking, Lena; Hauptmann, Andreas; Helin, Tapio; Siltanen, Samuli

2017-12-01

In this paper we study the reconstruction of moving object densities from undersampled dynamic x-ray tomography in two dimensions. A particular motivation of this study is to use realistic measurement protocols for practical applications, i.e. we do not assume to have a full Radon transform in each time step, but only projections in few angular directions. This restriction enforces a space-time reconstruction, which we perform by incorporating physical motion models and regularization of motion vectors in a variational framework. The methodology of optical flow, which is one of the most common methods to estimate motion between two images, is utilized to formulate a joint variational model for reconstruction and motion estimation. We provide a basic mathematical analysis of the forward model and the variational model for the image reconstruction. Moreover, we discuss the efficient numerical minimization based on alternating minimizations between images and motion vectors. A variety of results are presented for simulated and real measurement data with different sampling strategy. A key observation is that random sampling combined with our model allows reconstructions of similar amount of measurements and quality as a single static reconstruction.

Dynamic visual attention: motion direction versus motion magnitude

NASA Astrophysics Data System (ADS)

Bur, A.; Wurtz, P.; Müri, R. M.; Hügli, H.

2008-02-01

Defined as an attentive process in the context of visual sequences, dynamic visual attention refers to the selection of the most informative parts of video sequence. This paper investigates the contribution of motion in dynamic visual attention, and specifically compares computer models designed with the motion component expressed either as the speed magnitude or as the speed vector. Several computer models, including static features (color, intensity and orientation) and motion features (magnitude and vector) are considered. Qualitative and quantitative evaluations are performed by comparing the computer model output with human saliency maps obtained experimentally from eye movement recordings. The model suitability is evaluated in various situations (synthetic and real sequences, acquired with fixed and moving camera perspective), showing advantages and inconveniences of each method as well as preferred domain of application.

Colliding Stellar Wind Models with Orbital Motion

NASA Astrophysics Data System (ADS)

Wilkin, Francis P.; O'Connor, Brendan

2018-01-01

We present thin-shell models for the collision between two ballistic stellar winds, including orbital motion.The stellar orbits are assumed circular, so that steady-state solutions exist in the rotating frame, where we include centrifugal and Coriolis forces. Exact solutions for the pre-shock winds are incorporated. Here we discuss 2-D model results for equal wind momentum-loss rates, although we allow for the winds to have distinct speeds and mass loss rates. For these unequal wind conditions, we obtain a clear violation of skew-symmetry, despite equal momentum loss rates, due to the Coriolis force.

Motion direction discrimination training reduces perceived motion repulsion.

PubMed

Jia, Ke; Li, Sheng

2017-04-01

Participants often exaggerate the perceived angular separation between two simultaneously presented motion stimuli, which is referred to as motion repulsion. The overestimation helps participants differentiate between the two superimposed motion directions, yet it causes the impairment of direction perception. Since direction perception can be refined through perceptual training, we here attempted to investigate whether the training of a direction discrimination task changes the amount of motion repulsion. Our results showed a direction-specific learning effect, which was accompanied by a reduced amount of motion repulsion both for the trained and the untrained directions. The reduction of the motion repulsion disappeared when the participants were trained on a luminance discrimination task (control experiment 1) or a speed discrimination task (control experiment 2), ruling out any possible interpretation in terms of adaptation or training-induced attentional bias. Furthermore, training with a direction discrimination task along a direction 150° away from both directions in the transparent stimulus (control experiment 3) also had little effect on the amount of motion repulsion, ruling out the contribution of task learning. The changed motion repulsion observed in the main experiment was consistent with the prediction of the recurrent model of perceptual learning. Therefore, our findings demonstrate that training in direction discrimination can benefit the precise direction perception of the transparent stimulus and provide new evidence for the recurrent model of perceptual learning.

PEER NGA-East Overview: Development of a Ground Motion Characterization Model (Ground Motion Prediction Equations) for Central and Eastern North America

NASA Astrophysics Data System (ADS)

Goulet, C. A.; Abrahamson, N. A.; Al Atik, L.; Atkinson, G. M.; Bozorgnia, Y.; Graves, R. W.; Kuehn, N. M.; Youngs, R. R.

2017-12-01

The Next Generation Attenuation project for Central and Eastern North America (CENA), NGA-East, is a major multi-disciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER). The project was co-sponsored by the U.S. Nuclear Regulatory Commission (NRC), the U.S. Department of Energy (DOE), the Electric Power Research Institute (EPRI) and the U.S. Geological Survey (USGS). NGA-East involved a large number of participating researchers from various organizations in academia, industry and government and was carried-out as a combination of 1) a scientific research project and 2) a model-building component following the NRC Seismic Senior Hazard Analysis Committee (SSHAC) Level 3 process. The science part of the project led to several data products and technical reports while the SSHAC component aggregated the various results into a ground motion characterization (GMC) model. The GMC model consists in a set of ground motion models (GMMs) for median and standard deviation of ground motions and their associated weights, combined into logic-trees for use in probabilistic seismic hazard analyses (PSHA). NGA-East addressed many technical challenges, most of them related to the relatively small number of earthquake recordings available for CENA. To resolve this shortcoming, the project relied on ground motion simulations to supplement the available data. Other important scientific issues were addressed through research projects on topics such as the regionalization of seismic source, path and attenuation of motions, the treatment of variability and uncertainties and on the evaluation of site effects. Seven working groups were formed to cover the complexity and breadth of topics in the NGA-East project, each focused on a specific technical area. This presentation provides an overview of the NGA-East research project and its key products.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

PubMed

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

Covariant Structure of Models of Geophysical Fluid Motion

NASA Astrophysics Data System (ADS)

Dubos, Thomas

2018-01-01

Geophysical models approximate classical fluid motion in rotating frames. Even accurate approximations can have profound consequences, such as the loss of inertial frames. If geophysical fluid dynamics are not strictly equivalent to Newtonian hydrodynamics observed in a rotating frame, what kind of dynamics are they? We aim to clarify fundamental similarities and differences between relativistic, Newtonian, and geophysical hydrodynamics, using variational and covariant formulations as tools to shed the necessary light. A space-time variational principle for the motion of a perfect fluid is introduced. The geophysical action is interpreted as a synchronous limit of the relativistic action. The relativistic Levi-Civita connection also has a finite synchronous limit, which provides a connection with which to endow geophysical space-time, generalizing Cartan (1923). A covariant mass-momentum budget is obtained using covariance of the action and metric-preserving properties of the connection. Ultimately, geophysical models are found to differ from the standard compressible Euler model only by a specific choice of a metric-Coriolis-geopotential tensor akin to the relativistic space-time metric. Once this choice is made, the same covariant mass-momentum budget applies to Newtonian and all geophysical hydrodynamics, including those models lacking an inertial frame. Hence, it is argued that this mass-momentum budget provides an appropriate, common fundamental principle of dynamics. The postulate that Euclidean, inertial frames exist can then be regarded as part of the Newtonian theory of gravitation, which some models of geophysical hydrodynamics slightly violate.

Hybrid Co-Evolutionary Motion Planning via Visibility-Based Repair

NASA Technical Reports Server (NTRS)

Dozier, Gerry; McCullough, Shaun; Brown, Edward, Jr.; Homaifar, Abdollah; Bikdash, Mar-wan

1997-01-01

This paper introduces a hybrid co-evolutionary system for global motion planning within unstructured environments. This system combines the concept of co-evolutionary search along with a concept that we refer to as the visibility-based repair to form a hybrid which quickly transforms infeasible motions into feasible ones. Also, this system makes use of a novel representation scheme for the obstacles within an environment. Our hybrid evolutionary system differs from other evolutionary motion planners in that (1) more emphasis is placed on repairing infeasible motions to develop feasible motions rather than using simulated evolution exclusively as a means of discovering feasible motions, (2) a continuous map of the environment is used rather than a discretized map, and (3) it develops global motion plans for multiple mobile destinations by co-evolving populations of sub-global motion plans. In this paper, we demonstrate the effectiveness of this system by using it to solve two challenging motion planning problems where multiple targets try to move away from a point robot.

Self-noise models of five commercial strong-motion accelerometers

USGS Publications Warehouse

Ringler, Adam; Evans, John R.; Hutt, Charles R.

2015-01-01

To better characterize the noise of a number of commonly deployed accelerometers in a standardized way, we conducted noise measurements on five different models of strong‐motion accelerometers. Our study was limited to traditional accelerometers (Fig. 1) and is in no way exhaustive.

Modeling of the motion of automobile elastic wheel in real-time for creation of wheeled vehicles motion control electronic systems

NASA Astrophysics Data System (ADS)

Balakina, E. V.; Zotov, N. M.; Fedin, A. P.

2018-02-01

Modeling of the motion of the elastic wheel of the vehicle in real-time is used in the tasks of constructing different models in the creation of wheeled vehicles motion control electronic systems, in the creation of automobile stand-simulators etc. The accuracy and the reliability of simulation of the parameters of the wheel motion in real-time when rolling with a slip within the given road conditions are determined not only by the choice of the model, but also by the inaccuracy and instability of the numerical calculation. It is established that the inaccuracy and instability of the calculation depend on the size of the step of integration and the numerical method being used. The analysis of these inaccuracy and instability when wheel rolling with a slip was made and recommendations for reducing them were developed. It is established that the total allowable range of steps of integration is 0.001.0.005 s; the strongest instability is manifested in the calculation of the angular and linear accelerations of the wheel; the weakest instability is manifested in the calculation of the translational velocity of the wheel and moving of the center of the wheel; the instability is less at large values of slip angle and on more slippery surfaces. A new method of the average acceleration is suggested, which allows to significantly reduce (up to 100%) the manifesting of instability of the solution in the calculation of all parameters of motion of the elastic wheel for different braking conditions and for the entire range of steps of integration. The results of research can be applied to the selection of control algorithms in vehicles motion control electronic systems and in the testing stand-simulators

Kinematic model for the space-variant image motion of star sensors under dynamical conditions

NASA Astrophysics Data System (ADS)

Liu, Chao-Shan; Hu, Lai-Hong; Liu, Guang-Bin; Yang, Bo; Li, Ai-Jun

2015-06-01

A kinematic description of a star spot in the focal plane is presented for star sensors under dynamical conditions, which involves all necessary parameters such as the image motion, velocity, and attitude parameters of the vehicle. Stars at different locations of the focal plane correspond to the slightly different orientation and extent of motion blur, which characterize the space-variant point spread function. Finally, the image motion, the energy distribution, and centroid extraction are numerically investigated using the kinematic model under dynamic conditions. A centroid error of eight successive iterations <0.002 pixel is used as the termination criterion for the Richardson-Lucy deconvolution algorithm. The kinematic model of a star sensor is useful for evaluating the compensation algorithms of motion-blurred images.

Comparison of different models of motion in a crowded environment: a Monte Carlo study.

PubMed

Polanowski, P; Sikorski, A

2017-02-22

In this paper we investigate the motion of molecules in crowded environments for two dramatically different types of molecular transport. The first type is realized by the dynamic lattice liquid model, which is based on a cooperative movement concept and thus, the motion of molecules is highly correlated. The second one corresponds to a so-called motion of a single agent where the motion of molecules is considered as a random walk without any correlation with other moving elements. The crowded environments are modeled as a two-dimensional triangular lattice with fixed impenetrable obstacles. Our simulation results indicate that the type of transport has an impact on the dynamics of the system, the percolation threshold, critical exponents, and on molecules' trajectories.

Integration of MATLAB Simulink(Registered Trademark) Models with the Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Lewis, Emily K.; Vuong, Nghia D.

2012-01-01

This paper describes the integration of MATLAB Simulink(Registered TradeMark) models into the Vertical Motion Simulator (VMS) at NASA Ames Research Center. The VMS is a high-fidelity, large motion flight simulator that is capable of simulating a variety of aerospace vehicles. Integrating MATLAB Simulink models into the VMS needed to retain the development flexibility of the MATLAB environment and allow rapid deployment of model changes. The process developed at the VMS was used successfully in a number of recent simulation experiments. This accomplishment demonstrated that the model integrity was preserved, while working within the hard real-time run environment of the VMS architecture, and maintaining the unique flexibility of the VMS to meet diverse research requirements.

SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

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

Ali, I; Ahmad, S; Alsbou, N

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulatemore » respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing

Multi-model approach to characterize human handwriting motion.

PubMed

Chihi, I; Abdelkrim, A; Benrejeb, M

2016-02-01

This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

Diffusion in different models of active Brownian motion

NASA Astrophysics Data System (ADS)

Lindner, B.; Nicola, E. M.

2008-04-01

Active Brownian particles (ABP) have served as phenomenological models of self-propelled motion in biology. We study the effective diffusion coefficient of two one-dimensional ABP models (simplified depot model and Rayleigh-Helmholtz model) differing in their nonlinear friction functions. Depending on the choice of the friction function the diffusion coefficient does or does not attain a minimum as a function of noise intensity. We furthermore discuss the case of an additional bias breaking the left-right symmetry of the system. We show that this bias induces a drift and that it generally reduces the diffusion coefficient. For a finite range of values of the bias, both models can exhibit a maximum in the diffusion coefficient vs. noise intensity.

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

PubMed

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

2016-12-01

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

Reducing the net torque and flow ripple effects of multiple hydraulic piston motor drives

NASA Technical Reports Server (NTRS)

Bartos, R. D.

1992-01-01

The torque and flow ripple effects which result when multiple hydraulic motors are used to drive a single motion of a mechanical device can significantly affect the way in which the device performs. This article presents a mathematical model describing the torque and flow ripple effects of a bent-axis hydraulic piston motor. The model is used to show how the ripple magnitude can be reduced when multiple motors are used to drive a motion. A discussion of the hydraulic servo system of the 70-m antennas located with the Deep Space Network is included to demonstrate the application of the concepts presented.

Tsunami simulation using submarine displacement calculated from simulation of ground motion due to seismic source model

NASA Astrophysics Data System (ADS)

Akiyama, S.; Kawaji, K.; Fujihara, S.

2013-12-01

Since fault fracturing due to an earthquake can simultaneously cause ground motion and tsunami, it is appropriate to evaluate the ground motion and the tsunami by single fault model. However, several source models are used independently in the ground motion simulation or the tsunami simulation, because of difficulty in evaluating both phenomena simultaneously. Many source models for the 2011 off the Pacific coast of Tohoku Earthquake are proposed from the inversion analyses of seismic observations or from those of tsunami observations. Most of these models show the similar features, which large amount of slip is located at the shallower part of fault area near the Japan Trench. This indicates that the ground motion and the tsunami can be evaluated by the single source model. Therefore, we examine the possibility of the tsunami prediction, using the fault model estimated from seismic observation records. In this study, we try to carry out the tsunami simulation using the displacement field of oceanic crustal movements, which is calculated from the ground motion simulation of the 2011 off the Pacific coast of Tohoku Earthquake. We use two fault models by Yoshida et al. (2011), which are based on both the teleseismic body wave and on the strong ground motion records. Although there is the common feature in those fault models, the amount of slip near the Japan trench is lager in the fault model from the strong ground motion records than in that from the teleseismic body wave. First, the large-scale ground motion simulations applying those fault models used by the voxel type finite element method are performed for the whole eastern Japan. The synthetic waveforms computed from the simulations are generally consistent with the observation records of K-NET (Kinoshita (1998)) and KiK-net stations (Aoi et al. (2000)), deployed by the National Research Institute for Earth Science and Disaster Prevention (NIED). Next, the tsunami simulations are performed by the finite

Multiple Indicator Stationary Time Series Models.

ERIC Educational Resources Information Center

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

A margin model to account for respiration-induced tumour motion and its variability

NASA Astrophysics Data System (ADS)

Coolens, Catherine; Webb, Steve; Shirato, H.; Nishioka, K.; Evans, Phil M.

2008-08-01

In order to reduce the sensitivity of radiotherapy treatments to organ motion, compensation methods are being investigated such as gating of treatment delivery, tracking of tumour position, 4D scanning and planning of the treatment, etc. An outstanding problem that would occur with all these methods is the assumption that breathing motion is reproducible throughout the planning and delivery process of treatment. This is obviously not a realistic assumption and is one that will introduce errors. A dynamic internal margin model (DIM) is presented that is designed to follow the tumour trajectory and account for the variability in respiratory motion. The model statistically describes the variation of the breathing cycle over time, i.e. the uncertainty in motion amplitude and phase reproducibility, in a polar coordinate system from which margins can be derived. This allows accounting for an additional gating window parameter for gated treatment delivery as well as minimizing the area of normal tissue irradiated. The model was illustrated with abdominal motion for a patient with liver cancer and tested with internal 3D lung tumour trajectories. The results confirm that the respiratory phases around exhale are most reproducible and have the smallest variation in motion amplitude and phase (approximately 2 mm). More importantly, the margin area covering normal tissue is significantly reduced by using trajectory-specific margins (as opposed to conventional margins) as the angular component is by far the largest contributor to the margin area. The statistical approach to margin calculation, in addition, offers the possibility for advanced online verification and updating of breathing variation as more data become available.

A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion.

PubMed

Min, Yugang; Santhanam, Anand; Neelakkantan, Harini; Ruddy, Bari H; Meeks, Sanford L; Kupelian, Patrick A

2010-09-07

In this paper, we present a graphics processing unit (GPU)-based simulation framework to calculate the delivered dose to a 3D moving lung tumor and its surrounding normal tissues, which are undergoing subject-specific lung deformations. The GPU-based simulation framework models the motion of the 3D volumetric lung tumor and its surrounding tissues, simulates the dose delivery using the dose extracted from a treatment plan using Pinnacle Treatment Planning System, Phillips, for one of the 3DCTs of the 4DCT and predicts the amount and location of radiation doses deposited inside the lung. The 4DCT lung datasets were registered with each other using a modified optical flow algorithm. The motion of the tumor and the motion of the surrounding tissues were simulated by measuring the changes in lung volume during the radiotherapy treatment using spirometry. The real-time dose delivered to the tumor for each beam is generated by summing the dose delivered to the target volume at each increase in lung volume during the beam delivery time period. The simulation results showed the real-time capability of the framework at 20 discrete tumor motion steps per breath, which is higher than the number of 4DCT steps (approximately 12) reconstructed during multiple breathing cycles.

Modeling Nonlinear Site Response Uncertainty in Broadband Ground Motion Simulations for the Los Angeles Basin

NASA Astrophysics Data System (ADS)

Assimaki, D.; Li, W.; Steidl, J. M.; Schmedes, J.

2007-12-01

The assessment of strong motion site response is of great significance, both for mitigating seismic hazard and for performing detailed analyses of earthquake source characteristics. There currently exists, however, large degree of uncertainty concerning the mathematical model to be employed for the computationally efficient evaluation of local site effects, and the site investigation program necessary to evaluate the nonlinear input model parameters and ensure cost-effective predictions; and while site response observations may provide critical constraints on interpretation methods, the lack of a statistically significant number of in-situ strong motion records prohibits statistical analyses to be conducted and uncertainties to be quantified based entirely on field data. In this paper, we combine downhole observations and broadband ground motion synthetics for characteristic site conditions the Los Angeles Basin, and investigate the variability in ground motion estimation introduced by the site response assessment methodology. In particular, site-specific regional velocity and attenuation structures are initially compiled using near-surface geotechnical data collected at downhole geotechnical arrays, inverse low-strain velocity and attenuation profiles at these sites obtained by inversion of weak motion records and the crustal velocity structure at the corresponding locations obtained from the Southern California Earthquake Centre Community Velocity Model. Successively, broadband ground motions are simulated by means of a hybrid low/high-frequency finite source model with correlated random parameters for rupture scenaria of weak, medium and large magnitude events (M =3.5-7.5). Observed estimates of site response at the stations of interest are first compared to the ensemble of approximate and incremental nonlinear site response models. Parametric studies are next conducted for each fixed magnitude (fault geometry) scenario by varying the source-to-site distance and

4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Zhang, Dong Ping; Edwards, Eddie; Mei, Lin; Rueckert, Daniel

2009-02-01

In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures.

Smoothing Motion Estimates for Radar Motion Compensation.

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

Doerry, Armin W.

2017-07-01

Simple motion models for complex motion environments are often not adequate for keeping radar data coherent. Eve n perfect motion samples appli ed to imperfect models may lead to interim calculations e xhibiting errors that lead to degraded processing results. Herein we discuss a specific i ssue involving calculating motion for groups of pulses, with measurements only available at pulse-group boundaries. - 4 - Acknowledgements This report was funded by General A tomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Re search and Development Agre ement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc.more » (GA-ASI), an affilia te of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and rel ated mission systems, includin g the Predator(r)/Gray Eagle(r)-series and Lynx(r) Multi-mode Radar.« less

Comparison of different detection methods for persistent multiple hypothesis tracking in wide area motion imagery

NASA Astrophysics Data System (ADS)

Hartung, Christine; Spraul, Raphael; Schuchert, Tobias

2017-10-01

Wide area motion imagery (WAMI) acquired by an airborne multicamera sensor enables continuous monitoring of large urban areas. Each image can cover regions of several square kilometers and contain thousands of vehicles. Reliable vehicle tracking in this imagery is an important prerequisite for surveillance tasks, but remains challenging due to low frame rate and small object size. Most WAMI tracking approaches rely on moving object detections generated by frame differencing or background subtraction. These detection methods fail when objects slow down or stop. Recent approaches for persistent tracking compensate for missing motion detections by combining a detection-based tracker with a second tracker based on appearance or local context. In order to avoid the additional complexity introduced by combining two trackers, we employ an alternative single tracker framework that is based on multiple hypothesis tracking and recovers missing motion detections with a classifierbased detector. We integrate an appearance-based similarity measure, merge handling, vehicle-collision tests, and clutter handling to adapt the approach to the specific context of WAMI tracking. We apply the tracking framework on a region of interest of the publicly available WPAFB 2009 dataset for quantitative evaluation; a comparison to other persistent WAMI trackers demonstrates state of the art performance of the proposed approach. Furthermore, we analyze in detail the impact of different object detection methods and detector settings on the quality of the output tracking results. For this purpose, we choose four different motion-based detection methods that vary in detection performance and computation time to generate the input detections. As detector parameters can be adjusted to achieve different precision and recall performance, we combine each detection method with different detector settings that yield (1) high precision and low recall, (2) high recall and low precision, and (3) best f

Assessment of Different Turbulence Models for the Motion of Non-metallic Inclusion in Induction Crucible Furnace

NASA Astrophysics Data System (ADS)

Barati, H.; Wu, M.; Kharicha, A.; Ludwig, A.

2016-07-01

Turbulent fluid flow due to the electromagnetic forces in induction crucible furnace (ICF) is modeled using k-ɛ, k-ω SST and Large Eddy Simulation (LES) turbulence models. Fluid flow patterns calculated by different turbulence models and their effects on the motion of non-metallic inclusions (NMI) in the bulk melt have been investigated. Results show that the conventional k-ɛ model cannot solve the transient flow in ICF properly. With k-ω model transient flow and oscillation behavior of the flow pattern can be solved, and the motion of NMI can be tracked fairly well. LES model delivers the best modeling result on both details of the transient flow pattern and motion trajectories of NMI without the limitation of NMI size. The drawback of LES model is the long calculation time. Therefore, for general purpose to estimate the dynamic behavior of NMI in ICF both k-ω SST and LES are recommended. For the precise calculation of the motion of NMI smaller than 10 μm only LES model is appropriate.

Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation.

PubMed

Feghali, Rosario; Mitiche, Amar

2004-11-01

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image quence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine imultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion undary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.

Development of a human body finite element model with multiple muscles and their controller for estimating occupant motions and impact responses in frontal crash situations.

PubMed

Iwamoto, Masami; Nakahira, Yuko; Kimpara, Hideyuki; Sugiyama, Takahiko; Min, Kyuengbo

2012-10-01

A few reports suggest differences in injury outcomes between cadaver tests and real-world accidents under almost similar conditions. This study hypothesized that muscle activity could primarily cause the differences, and then developed a human body finite element (FE) model with individual muscles. Each muscle was modeled as a hybrid model of bar elements with active properties and solid elements with passive properties. The model without muscle activation was firstly validated against five series of cadaver test data on impact responses in the anterior-posterior direction. The model with muscle activation levels estimated based on electromyography (EMG) data was secondly validated against four series of volunteer test data on bracing effects for stiffness and thickness of an upper arm muscle, and braced driver's responses under a static environment and a brake deceleration. A muscle controller using reinforcement learning (RL), which is a mathematical model of learning process in the basal ganglia associated with human postural controls, were newly proposed to estimate muscle activity in various occupant conditions including inattentive and attentive conditions. Control of individual muscles predicted by RL reproduced more human like head-neck motions than conventional control of two groups of agonist and antagonist muscles. The model and the controller demonstrated that head-neck motions of an occupant under an impact deceleration of frontal crash were different in between a bracing condition with maximal braking force and an occupant condition predicted by RL. The model and the controller have the potential to investigate muscular effects in various occupant conditions during frontal crashes.

Modeling stock prices in a portfolio using multidimensional geometric brownian motion

NASA Astrophysics Data System (ADS)

Maruddani, Di Asih I.; Trimono

2018-05-01

Modeling and forecasting stock prices of public corporates are important studies in financial analysis, due to their stock price characteristics. Stocks investments give a wide variety of risks. Taking a portfolio of several stocks is one way to minimize risk. Stochastic process of single stock price movements model can be formulated in Geometric Brownian Motion (GBM) model. But for a portfolio that consist more than one corporate stock, we need an expansion of GBM Model. In this paper, we use multidimensional Geometric Brownian Motion model. This paper aims to model and forecast two stock prices in a portfolio. These are PT. Matahari Department Store Tbk and PT. Telekomunikasi Indonesia Tbk on period January 4, 2016 until April 21, 2017. The goodness of stock price forecast value is based on Mean Absolute Percentage Error (MAPE). As the results, we conclude that forecast two stock prices in a portfolio using multidimensional GBM give less MAPE than using GBM for single stock price respectively. We conclude that multidimensional GBM is more appropriate for modeling stock prices, because the price of each stock affects each other.

REPRESENTATION OF ATMOSPHERIC MOTION IN MODELS OF REGIONAL-SCALE AIR POLLUTION

EPA Science Inventory

A method is developed for generating ensembles of wind fields for use in regional scale (1000 km) models of transport and diffusion. The underlying objective is a methodology for representing atmospheric motion in applied air pollution models that permits explicit treatment of th...

WE-AB-303-11: Verification of a Deformable 4DCT Motion Model for Lung Tumor Tracking Using Different Driving Surrogates

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

Woelfelschneider, J; Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, DE; Seregni, M

2015-06-15

Purpose: Tumor tracking is an advanced technique to treat intra-fractionally moving tumors. The aim of this study is to validate a surrogate-driven model based on four-dimensional computed tomography (4DCT) that is able to predict CT volumes corresponding to arbitrary respiratory states. Further, the comparison of three different driving surrogates is evaluated. Methods: This study is based on multiple 4DCTs of two patients treated for bronchial carcinoma and metastasis. Analyses for 18 additional patients are currently ongoing. The motion model was estimated from the planning 4DCT through deformable image registration. To predict a certain phase of a follow-up 4DCT, the modelmore » considers for inter-fractional variations (baseline correction) and intra-fractional respiratory parameters (amplitude and phase) derived from surrogates. In this evaluation, three different approaches were used to extract the motion surrogate: for each 4DCT phase, the 3D thoraco-abdominal surface motion, the body volume and the anterior-posterior motion of a virtual single external marker defined on the sternum were investigated. The estimated volumes resulting from the model were compared to the ground-truth clinical 4DCTs using absolute HU differences in the lung volume and landmarks localized using the Scale Invariant Feature Transform (SIFT). Results: The results show absolute HU differences between estimated and ground-truth images with median values limited to 55 HU and inter-quartile ranges (IQR) lower than 100 HU. Median 3D distances between about 1500 matching landmarks are below 2 mm for 3D surface motion and body volume methods. The single marker surrogates Result in increased median distances up to 0.6 mm. Analyses for the extended database incl. 20 patients are currently in progress. Conclusion: The results depend mainly on the image quality of the initial 4DCTs and the deformable image registration. All investigated surrogates can be used to estimate follow-up 4DCT

An Inexpensive Mechanical Model for Projectile Motion

ERIC Educational Resources Information Center

Kagan, David

2011-01-01

As experienced physicists, we see the beauty and simplicity of projectile motion. It is merely the superposition of uniform linear motion along the direction of the initial velocity vector and the downward motion due to the constant acceleration of gravity. We see the kinematic equations as just the mathematical machinery to perform the…

Detecting multiple moving objects in crowded environments with coherent motion regions

DOEpatents

Cheriyadat, Anil M.; Radke, Richard J.

2013-06-11

Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

Musculoskeletal Simulation Model Generation from MRI Data Sets and Motion Capture Data

NASA Astrophysics Data System (ADS)

Schmid, Jérôme; Sandholm, Anders; Chung, François; Thalmann, Daniel; Delingette, Hervé; Magnenat-Thalmann, Nadia

Today computer models and computer simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a generic musculoskeletal model based on data derived from anatomical and biomechanical studies of cadaverous specimens. To adapt this generic model to a specific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from magnetic resonance imaging (MRI) data sets and motion capture data. Based on subject-specific medical data and a model-based automatic segmentation approach, an accurate modeling of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information, and muscle-tendon actuators is finally used to create a subject-specific musculoskeletal model.

Dynamic modeling and motion simulation for a winged hybrid-driven underwater glider

NASA Astrophysics Data System (ADS)

Wang, Shu-Xin; Sun, Xiu-Jun; Wang, Yan-Hui; Wu, Jian-Guo; Wang, Xiao-Ming

2011-03-01

PETREL, a winged hybrid-driven underwater glider is a novel and practical marine survey platform which combines the features of legacy underwater glider and conventional AUV (autonomous underwater vehicle). It can be treated as a multi-rigid-body system with a floating base and a particular hydrodynamic profile. In this paper, theorems on linear and angular momentum are used to establish the dynamic equations of motion of each rigid body and the effect of translational and rotational motion of internal masses on the attitude control are taken into consideration. In addition, due to the unique external shape with fixed wings and deflectable rudders and the dual-drive operation in thrust and glide modes, the approaches of building dynamic model of conventional AUV and hydrodynamic model of submarine are introduced, and the tailored dynamic equations of the hybrid glider are formulated. Moreover, the behaviors of motion in glide and thrust operation are analyzed based on the simulation and the feasibility of the dynamic model is validated by data from lake field trials.

A Pursuit Theory Account for the Perception of Common Motion in Motion Parallax.

PubMed

Ratzlaff, Michael; Nawrot, Mark

2016-09-01

The visual system uses an extraretinal pursuit eye movement signal to disambiguate the perception of depth from motion parallax. Visual motion in the same direction as the pursuit is perceived nearer in depth while visual motion in the opposite direction as pursuit is perceived farther in depth. This explanation of depth sign applies to either an allocentric frame of reference centered on the fixation point or an egocentric frame of reference centered on the observer. A related problem is that of depth order when two stimuli have a common direction of motion. The first psychophysical study determined whether perception of egocentric depth order is adequately explained by a model employing an allocentric framework, especially when the motion parallax stimuli have common rather than divergent motion. A second study determined whether a reversal in perceived depth order, produced by a reduction in pursuit velocity, is also explained by this model employing this allocentric framework. The results show than an allocentric model can explain both the egocentric perception of depth order with common motion and the perceptual depth order reversal created by a reduction in pursuit velocity. We conclude that an egocentric model is not the only explanation for perceived depth order in these common motion conditions. © The Author(s) 2016.

A 4D global respiratory motion model of the thorax based on CT images: A proof of concept.

PubMed

Fayad, Hadi; Gilles, Marlene; Pan, Tinsu; Visvikis, Dimitris

2018-05-17

Respiratory motion reduces the sensitivity and specificity of medical images especially in the thoracic and abdominal areas. It may affect applications such as cancer diagnostic imaging and/or radiation therapy (RT). Solutions to this issue include modeling of the respiratory motion in order to optimize both diagnostic and therapeutic protocols. Personalized motion modeling required patient-specific four-dimensional (4D) imaging which in the case of 4D computed tomography (4D CT) acquisition is associated with an increased dose. The goal of this work was to develop a global respiratory motion model capable of relating external patient surface motion to internal structure motion without the need for a patient-specific 4D CT acquisition. The proposed global model is based on principal component analysis and can be adjusted to a given patient anatomy using only one or two static CT images in conjunction with a respiratory synchronized patient external surface motion. It is based on the relation between the internal motion described using deformation fields obtained by registering 4D CT images and patient surface maps obtained either from optical imaging devices or extracted from CT image-based patient skin segmentation. 4D CT images of six patients were used to generate the global motion model which was validated by adapting it on four different patients having skin segmented surfaces and two other patients having time of flight camera acquired surfaces. The reproducibility of the proposed model was also assessed on two patients with two 4D CT series acquired within 2 weeks of each other. Profile comparison shows the efficacy of the global respiratory motion model and an improvement while using two CT images in order to adapt the model. This was confirmed by the correlation coefficient with a mean correlation of 0.9 and 0.95 while using one or two CT images respectively and when comparing acquired to model generated 4D CT images. For the four patients with segmented

Early Improper Motion Detection in Golf Swings Using Wearable Motion Sensors: The First Approach

PubMed Central

Stančin, Sara; Tomažič, Sašo

2013-01-01

This paper presents an analysis of a golf swing to detect improper motion in the early phase of the swing. Led by the desire to achieve a consistent shot outcome, a particular golfer would (in multiple trials) prefer to perform completely identical golf swings. In reality, some deviations from the desired motion are always present due to the comprehensive nature of the swing motion. Swing motion deviations that are not detrimental to performance are acceptable. This analysis is conducted using a golfer's leading arm kinematic data, which are obtained from a golfer wearing a motion sensor that is comprised of gyroscopes and accelerometers. Applying the principal component analysis (PCA) to the reference observations of properly performed swings, the PCA components of acceptable swing motion deviations are established. Using these components, the motion deviations in the observations of other swings are examined. Any unacceptable deviations that are detected indicate an improper swing motion. Arbitrarily long observations of an individual player's swing sequences can be included in the analysis. The results obtained for the considered example show an improper swing motion in early phase of the swing, i.e., the first part of the backswing. An early detection method for improper swing motions that is conducted on an individual basis provides assistance for performance improvement. PMID:23752563

Early improper motion detection in golf swings using wearable motion sensors: the first approach.

PubMed

Stančin, Sara; Tomažič, Sašo

2013-06-10

This paper presents an analysis of a golf swing to detect improper motion in the early phase of the swing. Led by the desire to achieve a consistent shot outcome, a particular golfer would (in multiple trials) prefer to perform completely identical golf swings. In reality, some deviations from the desired motion are always present due to the comprehensive nature of the swing motion. Swing motion deviations that are not detrimental to performance are acceptable. This analysis is conducted using a golfer's leading arm kinematic data, which are obtained from a golfer wearing a motion sensor that is comprised of gyroscopes and accelerometers. Applying the principal component analysis (PCA) to the reference observations of properly performed swings, the PCA components of acceptable swing motion deviations are established. Using these components, the motion deviations in the observations of other swings are examined. Any unacceptable deviations that are detected indicate an improper swing motion. Arbitrarily long observations of an individual player's swing sequences can be included in the analysis. The results obtained for the considered example show an improper swing motion in early phase of the swing, i.e., the first part of the backswing. An early detection method for improper swing motions that is conducted on an individual basis provides assistance for performance improvement.

Uniform circular motion concept attainment through circle share learning model using real media

NASA Astrophysics Data System (ADS)

Ponimin; Suparmi; Sarwanto; Sunarno, W.

2017-01-01

Uniform circular motion is an important concept and has many applications in life. Student’s concept understanding of uniform circular motion is not optimal because the teaching learning is not carried out properly in accordance with the characteristics of the concept. To improve student learning outcomes required better teaching learning which is match with the characteristics of uniform circular motion. The purpose of the study is to determine the effect of real media and circle share model to the understanding of the uniform circular motion concept. The real media was used to visualize of uniform circular motion concept. The real media consists of toy car, round table and spring balance. Circle share model is a learning model through discussion sequentially and programmed. Each group must evaluate the worksheets of another group in a circular position. The first group evaluates worksheets the second group, the second group evaluates worksheets third group, and the end group evaluates the worksheets of the first group. Assessment of learning outcomes includes experiment worksheets and post-test of students. Based on data analysis we obtained some findings. First, students can explain the understanding of uniform circular motion whose angular velocity and speed is constant correctly. Second, students can distinguish the angular velocity and linear velocity correctly. Third, students can explain the direction of the linear velocity vector and the direction of the centripetal force vector. Fourth, the student can explain the influence of the mass, radius, and velocity toward the centripetal force. Fifth, students can explain the principle of combined of wheels. Sixth, teaching learning used circle share, can increase student activity, experimental results and efficiency of discussion time.

Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF

ERIC Educational Resources Information Center

Lee, Soo; Bulut, Okan; Suh, Youngsuk

2017-01-01

A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory…

Validating Pseudo-dynamic Source Models against Observed Ground Motion Data at the SCEC Broadband Platform, Ver 16.5

NASA Astrophysics Data System (ADS)

Song, S. G.

2016-12-01

Simulation-based ground motion prediction approaches have several benefits over empirical ground motion prediction equations (GMPEs). For instance, full 3-component waveforms can be produced and site-specific hazard analysis is also possible. However, it is important to validate them against observed ground motion data to confirm their efficiency and validity before practical uses. There have been community efforts for these purposes, which are supported by the Broadband Platform (BBP) project at the Southern California Earthquake Center (SCEC). In the simulation-based ground motion prediction approaches, it is a critical element to prepare a possible range of scenario rupture models. I developed a pseudo-dynamic source model for Mw 6.5-7.0 by analyzing a number of dynamic rupture models, based on 1-point and 2-point statistics of earthquake source parameters (Song et al. 2014; Song 2016). In this study, the developed pseudo-dynamic source models were tested against observed ground motion data at the SCEC BBP, Ver 16.5. The validation was performed at two stages. At the first stage, simulated ground motions were validated against observed ground motion data for past events such as the 1992 Landers and 1994 Northridge, California, earthquakes. At the second stage, they were validated against the latest version of empirical GMPEs, i.e., NGA-West2. The validation results show that the simulated ground motions produce ground motion intensities compatible with observed ground motion data at both stages. The compatibility of the pseudo-dynamic source models with the omega-square spectral decay and the standard deviation of the simulated ground motion intensities are also discussed in the study

Model of vertical plasma motion during the current quench

NASA Astrophysics Data System (ADS)

Breizman, Boris; Kiramov, Dmitrii

2017-10-01

Tokamak disruptions impair plasma position control, which allows the plasma column to move and hit the wall. These detrimental events enhance thermal and mechanical loads due to halo currents and runaway electron losses. Their fundamental understanding and prevention is one of the high-priority items for ITER. As commonly observed in experiments, the disruptive plasma tends to move vertically, and the timescale of this motion is rather resistive than Alfvenic. These observations suggest that the plasma column is nearly force-free during its vertical motion. In fact, the force-free constraint is already used in disruption simulators. In this work, we consider a geometrically simple system that mimics the tokamak plasma surrounded by the conducting structures. Using this model, we highlight the underlying mechanism of the vertical displacement events during the current quench phase of plasma disruption. We also address a question of ideal MHD stability of the plasma during its resistive motion. Work supported by the U.S. Department of Energy Contracts DEFG02-04ER54742 and DE-SC0016283.

Two-character motion analysis and synthesis.

PubMed

Kwon, Taesoo; Cho, Young-Sang; Park, Sang Il; Shin, Sung Yong

2008-01-01

In this paper, we deal with the problem of synthesizing novel motions of standing-up martial arts such as Kickboxing, Karate, and Taekwondo performed by a pair of human-like characters while reflecting their interactions. Adopting an example-based paradigm, we address three non-trivial issues embedded in this problem: motion modeling, interaction modeling, and motion synthesis. For the first issue, we present a semi-automatic motion labeling scheme based on force-based motion segmentation and learning-based action classification. We also construct a pair of motion transition graphs each of which represents an individual motion stream. For the second issue, we propose a scheme for capturing the interactions between two players. A dynamic Bayesian network is adopted to build a motion transition model on top of the coupled motion transition graph that is constructed from an example motion stream. For the last issue, we provide a scheme for synthesizing a novel sequence of coupled motions, guided by the motion transition model. Although the focus of the present work is on martial arts, we believe that the framework of the proposed approach can be conveyed to other two-player motions as well.

Constraints on mantle viscosity from convection models with plate motion history

NASA Astrophysics Data System (ADS)

Mao, W.; Zhong, S.

2017-12-01

The Earth's long-wavelength geoid and dynamic topography are mainly controlled by the mantle buoyancy and viscosity structure. Previous dynamical models for the geoid provide constraints on the 1-D mantle viscosity, using mantle buoyancy derived from seismic topography models. However, it is a challenge in these studies on how to convert seismic velocity to density anomalies and mantle buoyancy. Furthermore, these studies provide constraints only on relative viscosity variations but not on absolute magnitude of viscosity. In this study, we formulate time-dependent 3-D spherical mantle convection models with imposed plate motion history and seek constraints on mantle viscosity structure for both its radial relative variations and its absolute magnitude (i.e., Rayleigh number), using the geoid from the convection models. We found that the geoid at intermediate wavelengths of degrees 4-9 is mainly controlled by the subducted slabs in the upper mantle and the upper part of lower mantle that result from subduction from the last 50 Myr or the Cenozoic. To fit the degrees 4-9 geoid, we need viscosity contrast β defined as the ratio of the lower mantle viscosity and the asthenospheric viscosity to be larger than 2000 and Ra to be 1e8 (defined by the Earth's radius). The best fit model leads to 57% variance reduction and 76% correlation between the model and the observations. However, the long-wavelength geoid at degrees 2-3 is controlled by the lower mantle structure which requires much longer time scale to develop, as seen from our modeling. The preferred viscosity structure and Rayleigh number as constrained by the Cenozoic plate motion and the degrees 4-9 geoid no longer provide adequate fit to the geoid in models with the plate motion history for the last 450 Myr. The degrees 4-9 geoid amplitude is smaller for the models with longer plate motion history and a smaller Ra is required to fit the observation. In order to satisfy the relative amplitude between degrees 2

Shear Wave Generation and Modeling Ground Motion From a Source Physics Experiment (SPE) Underground Explosion

NASA Astrophysics Data System (ADS)

Pitarka, Arben; Mellors, Robert; Rodgers, Arthur; Vorobiev, Oleg; Ezzedine, Souheil; Matzel, Eric; Ford, Sean; Walter, Bill; Antoun, Tarabay; Wagoner, Jeffery; Pasyanos, Mike; Petersson, Anders; Sjogreen, Bjorn

2014-05-01

We investigate the excitation and propagation of far-field (epicentral distance larger than 20 m) seismic waves by analyzing and modeling ground motion from an underground chemical explosion recorded during the Source Physics Experiment (SPE), Nevada. The far-field recorded ground motion is characterized by complex features, such as large azimuthal variations in P- and S-wave amplitudes, as well as substantial energy on the tangential component of motion. Shear wave energy is also observed on the tangential component of the near-field motion (epicentral distance smaller than 20 m) suggesting that shear waves were generated at or very near the source. These features become more pronounced as the waves propagate away from the source. We address the shear wave generation during the explosion by modeling ground motion waveforms recorded in the frequency range 0.01-20 Hz, at distances of up to 1 km. We used a physics based approach that combines hydrodynamic modeling of the source with anelastic modeling of wave propagation in order to separate the contributions from the source and near-source wave scattering on shear motion generation. We found that wave propagation scattering caused by the near-source geological environment, including surface topography, contributes to enhancement of shear waves generated from the explosion source. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-06NA25946/ NST11-NCNS-TM-EXP-PD15.

Local respiratory motion correction for PET/CT imaging: Application to lung cancer

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

Lamare, F., E-mail: frederic.lamare@chu-bordeaux.fr; Fernandez, P.; Fayad, H.

Purpose: Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications. Methods: Both simulated (NURBS based 4D cardiac-torso phantom)more » and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions. Results: Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

PubMed Central

Angelaki, Dora E

2017-01-01

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements. PMID:29043978

Coupled large eddy simulation and discrete element model of bedload motion

NASA Astrophysics Data System (ADS)

Furbish, D.; Schmeeckle, M. W.

2011-12-01

We combine a three-dimensional large eddy simulation of turbulence to a three-dimensional discrete element model of turbulence. The large eddy simulation of the turbulent fluid is extended into the bed composed of non-moving particles by adding resistance terms to the Navier-Stokes equations in accordance with the Darcy-Forchheimer law. This allows the turbulent velocity and pressure fluctuations to penetrate the bed of discrete particles, and this addition of a porous zone results in turbulence structures above the bed that are similar to previous experimental and numerical results for hydraulically-rough beds. For example, we reproduce low-speed streaks that are less coherent than those over smooth-beds due to the episodic outflow of fluid from the bed. Local resistance terms are also added to the Navier-Stokes equations to account for the drag of individual moving particles. The interaction of the spherical particles utilizes a standard DEM soft-sphere Hertz model. We use only a simple drag model to calculate the fluid forces on the particles. The model reproduces an exponential distribution of bedload particle velocities that we have found experimentally using high-speed video of a flat bed of moving sand in a recirculating water flume. The exponential distribution of velocity results from the motion of many particles that are nearly constantly in contact with other bed particles and come to rest after short distances, in combination with a relatively few particles that are entrained further above the bed and have velocities approaching that of the fluid. Entrainment and motion "hot spots" are evident that are not perfectly correlated with the local, instantaneous fluid velocity. Zones of the bed that have recently experienced motion are more susceptible to motion because of the local configuration of particle contacts. The paradigm of a characteristic saltation hop length in riverine bedload transport has infused many aspects of geomorphic thought, including

4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

NASA Astrophysics Data System (ADS)

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-02-01

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp-Davis-Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations.

4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling.

PubMed

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-02-07

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp-Davis-Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations.

4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

PubMed Central

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-01-01

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp–Davis–Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations. PMID:26758496

Developing Stochastic Models as Inputs for High-Frequency Ground Motion Simulations

NASA Astrophysics Data System (ADS)

Savran, William Harvey

High-frequency ( 10 Hz) deterministic ground motion simulations are challenged by our understanding of the small-scale structure of the earth's crust and the rupture process during an earthquake. We will likely never obtain deterministic models that can accurately describe these processes down to the meter scale length required for broadband wave propagation. Instead, we can attempt to explain the behavior, in a statistical sense, by including stochastic models defined by correlations observed in the natural earth and through physics based simulations of the earthquake rupture process. Toward this goal, we develop stochastic models to address both of the primary considerations for deterministic ground motion simulations: namely, the description of the material properties in the crust, and broadband earthquake source descriptions. Using borehole sonic log data recorded in Los Angeles basin, we estimate the spatial correlation structure of the small-scale fluctuations in P-wave velocities by determining the best-fitting parameters of a von Karman correlation function. We find that Hurst exponents, nu, between 0.0-0.2, vertical correlation lengths, az, of 15-150m, an standard deviation, sigma of about 5% characterize the variability in the borehole data. Usin these parameters, we generated a stochastic model of velocity and density perturbations and combined with leading seismic velocity models to perform a validation exercise for the 2008, Chino Hills, CA using heterogeneous media. We find that models of velocity and density perturbations can have significant effects on the wavefield at frequencies as low as 0.3 Hz, with ensemble median values of various ground motion metrics varying up to +/-50%, at certain stations, compared to those computed solely from the CVM. Finally, we develop a kinematic rupture generator based on dynamic rupture simulations on geometrically complex faults. We analyze 100 dynamic rupture simulations on strike-slip faults ranging from Mw 6

Evaluation of deformable image registration and a motion model in CT images with limited features.

PubMed

Liu, F; Hu, Y; Zhang, Q; Kincaid, R; Goodman, K A; Mageras, G S

2012-05-07

Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.

Software package for modeling spin-orbit motion in storage rings

NASA Astrophysics Data System (ADS)

Zyuzin, D. V.

2015-12-01

A software package providing a graphical user interface for computer experiments on the motion of charged particle beams in accelerators, as well as analysis of obtained data, is presented. The software package was tested in the framework of the international project on electric dipole moment measurement JEDI (Jülich Electric Dipole moment Investigations). The specific features of particle spin motion imply the requirement to use a cyclic accelerator (storage ring) consisting of electrostatic elements, which makes it possible to preserve horizontal polarization for a long time. Computer experiments study the dynamics of 106-109 particles in a beam during 109 turns in an accelerator (about 1012-1015 integration steps for the equations of motion). For designing an optimal accelerator structure, a large number of computer experiments on polarized beam dynamics are required. The numerical core of the package is COSY Infinity, a program for modeling spin-orbit dynamics.

Sub-block motion derivation for merge mode in HEVC

NASA Astrophysics Data System (ADS)

Chien, Wei-Jung; Chen, Ying; Chen, Jianle; Zhang, Li; Karczewicz, Marta; Li, Xiang

2016-09-01

The new state-of-the-art video coding standard, H.265/HEVC, has been finalized in 2013 and it achieves roughly 50% bit rate saving compared to its predecessor, H.264/MPEG-4 AVC. In this paper, two additional merge candidates, advanced temporal motion vector predictor and spatial-temporal motion vector predictor, are developed to improve motion information prediction scheme under the HEVC structure. The proposed method allows each Prediction Unit (PU) to fetch multiple sets of motion information from multiple blocks smaller than the current PU. By splitting a large PU into sub-PUs and filling motion information for all the sub-PUs of the large PU, signaling cost of motion information could be reduced. This paper describes above-mentioned techniques in detail and evaluates their coding performance benefits based on the common test condition during HEVC development. Simulation results show that 2.4% performance improvement over HEVC can be achieved.

Dynamical modelling of coordinated multiple robot systems

NASA Technical Reports Server (NTRS)

Hayati, Samad

1987-01-01

The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.

On modeling animal movements using Brownian motion with measurement error.

PubMed

Pozdnyakov, Vladimir; Meyer, Thomas; Wang, Yu-Bo; Yan, Jun

2014-02-01

Modeling animal movements with Brownian motion (or more generally by a Gaussian process) has a long tradition in ecological studies. The recent Brownian bridge movement model (BBMM), which incorporates measurement errors, has been quickly adopted by ecologists because of its simplicity and tractability. We discuss some nontrivial properties of the discrete-time stochastic process that results from observing a Brownian motion with added normal noise at discrete times. In particular, we demonstrate that the observed sequence of random variables is not Markov. Consequently the expected occupation time between two successively observed locations does not depend on just those two observations; the whole path must be taken into account. Nonetheless, the exact likelihood function of the observed time series remains tractable; it requires only sparse matrix computations. The likelihood-based estimation procedure is described in detail and compared to the BBMM estimation.

Simultaneous two-view epipolar geometry estimation and motion segmentation by 4D tensor voting.

PubMed

Tong, Wai-Shun; Tang, Chi-Keung; Medioni, Gérard

2004-09-01

We address the problem of simultaneous two-view epipolar geometry estimation and motion segmentation from nonstatic scenes. Given a set of noisy image pairs containing matches of n objects, we propose an unconventional, efficient, and robust method, 4D tensor voting, for estimating the unknown n epipolar geometries, and segmenting the static and motion matching pairs into n independent motions. By considering the 4D isotropic and orthogonal joint image space, only two tensor voting passes are needed, and a very high noise to signal ratio (up to five) can be tolerated. Epipolar geometries corresponding to multiple, rigid motions are extracted in succession. Only two uncalibrated frames are needed, and no simplifying assumption (such as affine camera model or homographic model between images) other than the pin-hole camera model is made. Our novel approach consists of propagating a local geometric smoothness constraint in the 4D joint image space, followed by global consistency enforcement for extracting the fundamental matrices corresponding to independent motions. We have performed extensive experiments to compare our method with some representative algorithms to show that better performance on nonstatic scenes are achieved. Results on challenging data sets are presented.

Ground motion modeling of the 1906 San Francisco earthquake II: Ground motion estimates for the 1906 earthquake and scenario events

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

Aagaard, B; Brocher, T; Dreger, D

2007-02-09

We estimate the ground motions produced by the 1906 San Francisco earthquake making use of the recently developed Song et al. (2008) source model that combines the available geodetic and seismic observations and recently constructed 3D geologic and seismic velocity models. Our estimates of the ground motions for the 1906 earthquake are consistent across five ground-motion modeling groups employing different wave propagation codes and simulation domains. The simulations successfully reproduce the main features of the Boatwright and Bundock (2005) ShakeMap, but tend to over predict the intensity of shaking by 0.1-0.5 modified Mercalli intensity (MMI) units. Velocity waveforms at sitesmore » throughout the San Francisco Bay Area exhibit characteristics consistent with rupture directivity, local geologic conditions (e.g., sedimentary basins), and the large size of the event (e.g., durations of strong shaking lasting tens of seconds). We also compute ground motions for seven hypothetical scenarios rupturing the same extent of the northern San Andreas fault, considering three additional hypocenters and an additional, random distribution of slip. Rupture directivity exerts the strongest influence on the variations in shaking, although sedimentary basins do consistently contribute to the response in some locations, such as Santa Rosa, Livermore, and San Jose. These scenarios suggest that future large earthquakes on the northern San Andreas fault may subject the current San Francisco Bay urban area to stronger shaking than a repeat of the 1906 earthquake. Ruptures propagating southward towards San Francisco appear to expose more of the urban area to a given intensity level than do ruptures propagating northward.« less

A biomechanical modeling-guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2018-02-01

Reconstructing four-dimensional cone-beam computed tomography (4D-CBCT) images directly from respiratory phase-sorted traditional 3D-CBCT projections can capture target motion trajectory, reduce motion artifacts, and reduce imaging dose and time. However, the limited numbers of projections in each phase after phase-sorting decreases CBCT image quality under traditional reconstruction techniques. To address this problem, we developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, an iterative method that can reconstruct higher quality 4D-CBCT images from limited projections using an inter-phase intensity-driven motion model. However, the accuracy of the intensity-driven motion model is limited in regions with fine details whose quality is degraded due to insufficient projection number, which consequently degrades the reconstructed image quality in corresponding regions. In this study, we developed a new 4D-CBCT reconstruction algorithm by introducing biomechanical modeling into SMEIR (SMEIR-Bio) to boost the accuracy of the motion model in regions with small fine structures. The biomechanical modeling uses tetrahedral meshes to model organs of interest and solves internal organ motion using tissue elasticity parameters and mesh boundary conditions. This physics-driven approach enhances the accuracy of solved motion in the organ’s fine structures regions. This study used 11 lung patient cases to evaluate the performance of SMEIR-Bio, making both qualitative and quantitative comparisons between SMEIR-Bio, SMEIR, and the algebraic reconstruction technique with total variation regularization (ART-TV). The reconstruction results suggest that SMEIR-Bio improves the motion model’s accuracy in regions containing small fine details, which consequently enhances the accuracy and quality of the reconstructed 4D-CBCT images.

Modeling Visual, Vestibular and Oculomotor Interactions in Self-Motion Estimation

NASA Technical Reports Server (NTRS)

Perrone, John

1997-01-01

A computational model of human self-motion perception has been developed in collaboration with Dr. Leland S. Stone at NASA Ames Research Center. The research included in the grant proposal sought to extend the utility of this model so that it could be used for explaining and predicting human performance in a greater variety of aerospace applications. This extension has been achieved along with physiological validation of the basic operation of the model.

Dual Sticky Hierarchical Dirichlet Process Hidden Markov Model and Its Application to Natural Language Description of Motions.

PubMed

Hu, Weiming; Tian, Guodong; Kang, Yongxin; Yuan, Chunfeng; Maybank, Stephen

2017-09-25

In this paper, a new nonparametric Bayesian model called the dual sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) is proposed for mining activities from a collection of time series data such as trajectories. All the time series data are clustered. Each cluster of time series data, corresponding to a motion pattern, is modeled by an HMM. Our model postulates a set of HMMs that share a common set of states (topics in an analogy with topic models for document processing), but have unique transition distributions. For the application to motion trajectory modeling, topics correspond to motion activities. The learnt topics are clustered into atomic activities which are assigned predicates. We propose a Bayesian inference method to decompose a given trajectory into a sequence of atomic activities. On combining the learnt sources and sinks, semantic motion regions, and the learnt sequence of atomic activities, the action represented by the trajectory can be described in natural language in as automatic a way as possible. The effectiveness of our dual sticky HDP-HMM is validated on several trajectory datasets. The effectiveness of the natural language descriptions for motions is demonstrated on the vehicle trajectories extracted from a traffic scene.

Error-compensation model for simultaneous measurement of five degrees of freedom motion errors of a rotary axis

NASA Astrophysics Data System (ADS)

Bao, Chuanchen; Li, Jiakun; Feng, Qibo; Zhang, Bin

2018-07-01

This paper introduces an error-compensation model for our measurement method to measure five motion errors of a rotary axis based on fibre laser collimation. The error-compensation model is established in a matrix form using the homogeneous coordinate transformation theory. The influences of the installation errors, error crosstalk, and manufacturing errors are analysed. The model is verified by both ZEMAX simulation and measurement experiments. The repeatability values of the radial and axial motion errors are significantly suppressed by more than 50% after compensation. The repeatability experiments of five degrees of freedom motion errors and the comparison experiments of two degrees of freedom motion errors of an indexing table were performed by our measuring device and a standard instrument. The results show that the repeatability values of the angular positioning error ε z and tilt motion error around the Y axis ε y are 1.2″ and 4.4″, and the comparison deviations of the two motion errors are 4.0″ and 4.4″, respectively. The repeatability values of the radial and axial motion errors, δ y and δ z , are 1.3 and 0.6 µm, respectively. The repeatability value of the tilt motion error around the X axis ε x is 3.8″.

Rotational Motions from Teleseismic Events - Modelling and Observations

NASA Astrophysics Data System (ADS)

Schuberth, B.; Igel, H.; Wassermann, J.; Cochard, A.; Schreiber, U.

2004-12-01

Currently only ring lasers technology is capable of recording rotational motions resulting from earthquakes with a sensitivity and frequency band that are interesting for broadband seismology. One of those instruments is located at the Geodetic observatory in Wettzell/Germany. Here we present theoretical studies of rotational motions simulated with different Earth models and comparisons with several observations at the Wettzell ring laser. The 3-D global simulations were performed with the Spectral Element Method (Komatitsch and Tromp 2002a,b), that was modified to also allow the output of rotational seismograms. The Earth models used in these simulations range from simple radially symmetric ones, such as PREM, to more complex models including 3D velocity structures, attenuation and geometric effects like topography and bathymetry. Thus, by comparison of the theoretical rotation rates with the ring laser data we show how the results converge to the observed rotation rates when using more realistic Earth models. In a second step we compare rotation rates to the transverse component of translational acceleration both obtained from simulations with 3D velocity structures in crust and mantle. As expected from theory - under the assumption of plane wave propagation - those two signals should be in phase and scale linearly with the phase velocity. Using this relation, it is possible to determine the local phase velocity of transverse signals from collocated measurments of rotations and transverse accelerations. We compare the estimated phase velocities with those observed in a temporary seismic array installed around the ring laser.

A geometric model for evaluating the effects of inter-fraction rectal motion during prostate radiotherapy

NASA Astrophysics Data System (ADS)

Pavel-Mititean, Luciana M.; Rowbottom, Carl G.; Hector, Charlotte L.; Partridge, Mike; Bortfeld, Thomas; Schlegel, Wolfgang

2004-06-01

A geometric model is presented which allows calculation of the dosimetric consequences of rectal motion in prostate radiotherapy. Variations in the position of the rectum are measured by repeat CT scanning during the courses of treatment of five patients. Dose distributions are calculated by applying the same conformal treatment plan to each imaged fraction and rectal dose-surface histograms produced. The 2D model allows isotropic expansion and contraction in the plane of each CT slice. By summing the dose to specific volume elements tracked by the model, composite dose distributions are produced that explicitly include measured inter-fraction motion for each patient. These are then used to estimate effective dose-surface histograms (DSHs) for the entire treatment. Results are presented showing the magnitudes of the measured target and rectal motion and showing the effects of this motion on the integral dose to the rectum. The possibility of using such information to calculate normal tissue complication probabilities (NTCP) is demonstrated and discussed.

Equations of motion for a spectrum-generating algebra: Lipkin Meshkov Glick model

NASA Astrophysics Data System (ADS)

Rosensteel, G.; Rowe, D. J.; Ho, S. Y.

2008-01-01

For a spectrum-generating Lie algebra, a generalized equations-of-motion scheme determines numerical values of excitation energies and algebra matrix elements. In the approach to the infinite particle number limit or, more generally, whenever the dimension of the quantum state space is very large, the equations-of-motion method may achieve results that are impractical to obtain by diagonalization of the Hamiltonian matrix. To test the method's effectiveness, we apply it to the well-known Lipkin-Meshkov-Glick (LMG) model to find its low-energy spectrum and associated generator matrix elements in the eigenenergy basis. When the dimension of the LMG representation space is 106, computation time on a notebook computer is a few minutes. For a large particle number in the LMG model, the low-energy spectrum makes a quantum phase transition from a nondegenerate harmonic vibrator to a twofold degenerate harmonic oscillator. The equations-of-motion method computes critical exponents at the transition point.

Inter-segment foot motion in girls using a three-dimensional multi-segment foot model.

PubMed

Jang, Woo Young; Lee, Dong Yeon; Jung, Hae Woon; Lee, Doo Jae; Yoo, Won Joon; Choi, In Ho

2018-05-06

Several multi-segment foot models (MFMs) have been introduced for in vivo analyses of dynamic foot kinematics. However, the normal gait patterns of healthy children and adolescents remain uncharacterized. We sought to determine normal foot kinematics according to age in clinically normal female children and adolescents using a Foot 3D model. Fifty-eight girls (age 7-17 years) with normal function and without radiographic abnormalities were tested. Three representative strides from five separate trials were analyzed. Kinematic data of foot segment motion were tracked and evaluated using an MFM with a 15-marker set (Foot 3D model). As controls, 50 symptom-free female adults (20-35 years old) were analyzed. In the hindfoot kinematic analysis, plantar flexion motion in the pre-swing phase was significantly greater in girls aged 11 years or older than in girls aged <11 years, thereby resulting in a larger sagittal range of motion. Coronal plane hindfoot motion exhibited pronation, whereas transverse plane hindfoot motion exhibited increased internal rotation in girls aged <11 years. Hallux valgus angles increased significantly in girls aged 11 years or older. The foot progression angle showed mildly increased internal rotation in the loading response phase and the swing phase in girls aged <11 years old. The patterns of inter-segment foot motion in girls aged 11 years or older showed low-arch kinematic characteristics, whereas those in girls aged 11 years or older were more similar to the patterns in young adult women. Copyright © 2018 Elsevier B.V. All rights reserved.

Nonlinear model of a rotating hub-beams structure: Equations of motion

NASA Astrophysics Data System (ADS)

Warminski, Jerzy

2018-01-01

Dynamics of a rotating structure composed of a rigid hub and flexible beams is presented in the paper. A nonlinear model of a beam takes into account bending, extension and nonlinear curvature. The influence of geometric nonlinearity and nonconstant angular velocity on dynamics of the rotating structure is presented. The exact equations of motion and associated boundary conditions are derived on the basis of the Hamilton's principle. The simplification of the exact nonlinear mathematical model is proposed taking into account the second order approximation. The reduced partial differential equations of motion together with associated boundary conditions can be used to study natural or forced vibrations of a rotating structure considering constant or nonconstant angular speed of a rigid hub and an arbitrary number of flexible blades.

Evaluation of a computational model to predict elbow range of motion

PubMed Central

Nishiwaki, Masao; Johnson, James A.; King, Graham J. W.; Athwal, George S.

2014-01-01

Computer models capable of predicting elbow flexion and extension range of motion (ROM) limits would be useful for assisting surgeons in improving the outcomes of surgical treatment of patients with elbow contractures. A simple and robust computer-based model was developed that predicts elbow joint ROM using bone geometries calculated from computed tomography image data. The model assumes a hinge-like flexion-extension axis, and that elbow passive ROM limits can be based on terminal bony impingement. The model was validated against experimental results with a cadaveric specimen, and was able to predict the flexion and extension limits of the intact joint to 0° and 3°, respectively. The model was also able to predict the flexion and extension limits to 1° and 2°, respectively, when simulated osteophytes were inserted into the joint. Future studies based on this approach will be used for the prediction of elbow flexion-extension ROM in patients with primary osteoarthritis to help identify motion-limiting hypertrophic osteophytes, and will eventually permit real-time computer-assisted navigated excisions. PMID:24841799

Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy

NASA Astrophysics Data System (ADS)

Stemkens, Bjorn; Tijssen, Rob H. N.; de Senneville, Baudouin Denis; Lagendijk, Jan J. W.; van den Berg, Cornelis A. T.

2016-07-01

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.

Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy.

PubMed

Stemkens, Bjorn; Tijssen, Rob H N; de Senneville, Baudouin Denis; Lagendijk, Jan J W; van den Berg, Cornelis A T

2016-07-21

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.

Relation of landslides triggered by the Kiholo Bay earthquake to modeled ground motion

USGS Publications Warehouse

Harp, Edwin L.; Hartzell, Stephen H.; Jibson, Randall W.; Ramirez-Guzman, L.; Schmitt, Robert G.

2014-01-01

The 2006 Kiholo Bay, Hawaii, earthquake triggered high concentrations of rock falls and slides in the steep canyons of the Kohala Mountains along the north coast of Hawaii. Within these mountains and canyons a complex distribution of landslides was triggered by the earthquake shaking. In parts of the area, landslides were preferentially located on east‐facing slopes, whereas in other parts of the canyons no systematic pattern prevailed with respect to slope aspect or vertical position on the slopes. The geology within the canyons is homogeneous, so we hypothesize that the variable landslide distribution is the result of localized variation in ground shaking; therefore, we used a state‐of‐the‐art, high‐resolution ground‐motion simulation model to see if it could reproduce the landslide‐distribution patterns. We used a 3D finite‐element analysis to model earthquake shaking using a 10 m digital elevation model and slip on a finite‐fault model constructed from teleseismic records of the mainshock. Ground velocity time histories were calculated up to a frequency of 5 Hz. Dynamic shear strain also was calculated and compared with the landslide distribution. Results were mixed for the velocity simulations, with some areas showing correlation of landslide locations with peak modeled ground motions but many other areas showing no such correlation. Results were much improved for the comparison with dynamic shear strain. This suggests that (1) rock falls and slides are possibly triggered by higher frequency ground motions (velocities) than those in our simulations, (2) the ground‐motion velocity model needs more refinement, or (3) dynamic shear strain may be a more fundamental measurement of the decoupling process of slope materials during seismic shaking.

Ground-motion modeling of the 1906 San Francisco Earthquake, part II: Ground-motion estimates for the 1906 earthquake and scenario events

USGS Publications Warehouse

Aagaard, Brad T.; Brocher, T.M.; Dolenc, D.; Dreger, D.; Graves, R.W.; Harmsen, S.; Hartzell, S.; Larsen, S.; McCandless, K.; Nilsson, S.; Petersson, N.A.; Rodgers, A.; Sjogreen, B.; Zoback, M.L.

2008-01-01

We estimate the ground motions produce by the 1906 San Francisco earthquake making use of the recently developed Song et al. (2008) source model that combines the available geodetic and seismic observations and recently constructed 3D geologic and seismic velocity models. Our estimates of the ground motions for the 1906 earthquake are consistent across five ground-motion modeling groups employing different wave propagation codes and simulation domains. The simulations successfully reproduce the main features of the Boatwright and Bundock (2005) ShakeMap, but tend to over predict the intensity of shaking by 0.1-0.5 modified Mercalli intensity (MMI) units. Velocity waveforms at sites throughout the San Francisco Bay Area exhibit characteristics consistent with rupture directivity, local geologic conditions (e.g., sedimentary basins), and the large size of the event (e.g., durations of strong shaking lasting tens of seconds). We also compute ground motions for seven hypothetical scenarios rupturing the same extent of the northern San Andreas fault, considering three additional hypocenters and an additional, random distribution of slip. Rupture directivity exerts the strongest influence on the variations in shaking, although sedimentary basins do consistently contribute to the response in some locations, such as Santa Rosa, Livermore, and San Jose. These scenarios suggest that future large earthquakes on the northern San Andreas fault may subject the current San Francisco Bay urban area to stronger shaking than a repeat of the 1906 earthquake. Ruptures propagating southward towards San Francisco appear to expose more of the urban area to a given intensity level than do ruptures propagating northward.

Development of Physics and Control of Multiple Forcing Mechanisms for the Alaska Tsunami Forecast Model

NASA Astrophysics Data System (ADS)

Bahng, B.; Whitmore, P.; Macpherson, K. A.; Knight, W. R.

2016-12-01

The Alaska Tsunami Forecast Model (ATFM) is a numerical model used to forecast propagation and inundation of tsunamis generated by earthquakes or other mechanisms in either the Pacific Ocean, Atlantic Ocean or Gulf of Mexico. At the U.S. National Tsunami Warning Center (NTWC), the use of the model has been mainly for tsunami pre-computation due to earthquakes. That is, results for hundreds of hypothetical events are computed before alerts, and are accessed and calibrated with observations during tsunamis to immediately produce forecasts. The model has also been used for tsunami hindcasting due to submarine landslides and due to atmospheric pressure jumps, but in a very case-specific and somewhat limited manner. ATFM uses the non-linear, depth-averaged, shallow-water equations of motion with multiply nested grids in two-way communications between domains of each parent-child pair as waves approach coastal waters. The shallow-water wave physics is readily applicable to all of the above tsunamis as well as to tides. Recently, the model has been expanded to include multiple forcing mechanisms in a systematic fashion, and to enhance the model physics for non-earthquake events.ATFM is now able to handle multiple source mechanisms, either individually or jointly, which include earthquake, submarine landslide, meteo-tsunami and tidal forcing. As for earthquakes, the source can be a single unit source or multiple, interacting source blocks. Horizontal slip contribution can be added to the sea-floor displacement. The model now includes submarine landslide physics, modeling the source either as a rigid slump, or as a viscous fluid. Additional shallow-water physics have been implemented for the viscous submarine landslides. With rigid slumping, any trajectory can be followed. As for meteo-tsunami, the forcing mechanism is capable of following any trajectory shape. Wind stress physics has also been implemented for the meteo-tsunami case, if required. As an example of multiple

Software package for modeling spin–orbit motion in storage rings

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

Zyuzin, D. V., E-mail: d.zyuzin@fz-juelich.de

2015-12-15

A software package providing a graphical user interface for computer experiments on the motion of charged particle beams in accelerators, as well as analysis of obtained data, is presented. The software package was tested in the framework of the international project on electric dipole moment measurement JEDI (Jülich Electric Dipole moment Investigations). The specific features of particle spin motion imply the requirement to use a cyclic accelerator (storage ring) consisting of electrostatic elements, which makes it possible to preserve horizontal polarization for a long time. Computer experiments study the dynamics of 10{sup 6}–10{sup 9} particles in a beam during 10{supmore » 9} turns in an accelerator (about 10{sup 12}–10{sup 15} integration steps for the equations of motion). For designing an optimal accelerator structure, a large number of computer experiments on polarized beam dynamics are required. The numerical core of the package is COSY Infinity, a program for modeling spin–orbit dynamics.« less

Modeling correlated motion in thermoelectric skutterudite materials

NASA Astrophysics Data System (ADS)

Keiber, Trevor; Bridges, Frank; Bridges Lab Team

2014-03-01

Filled skutterudite compounds, LnT4X12 (Ln=rare earth; T=Fe,Ru,Os; X=P,As,Sb), have previously been modeled using a rigid cage approximation for the ``rattling'' rare earth atom. The large thermal broadening with temperature of the rattler can be fit using an Einstein model. Recent measurements of the second neighbor Ln-T peaks show an unusually large thermal broadening suggesting motion of the cage of atoms. To incorporate these results we developed three and four mass spring models to give the acoustic and optical phonon mode spectra. For the simplest three mass model we identify the low energy optical mode as the rattling mode. This rattling mode is likely coupled to the acoustic mode, and responsible for the low thermal conductivity of the skutterudite compound. We extend this model to four atoms to describe the CuO4 rings in oxy-skutterudites and the X4 rings in LnT4X12. This talk provides a model for the experimental results of the previous presentation. Support: NSF DMR1005568.

SU-E-J-234: Application of a Breathing Motion Model to ViewRay Cine MR Images

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

O’Connell, D. P.; Thomas, D. H.; Dou, T. H.

2015-06-15

Purpose: A respiratory motion model previously used to generate breathing-gated CT images was used with cine MR images. Accuracy and predictive ability of the in-plane models were evaluated. Methods: Sagittalplane cine MR images of a patient undergoing treatment on a ViewRay MRI/radiotherapy system were acquired before and during treatment. Images were acquired at 4 frames/second with 3.5 × 3.5 mm resolution and a slice thickness of 5 mm. The first cine frame was deformably registered to following frames. Superior/inferior component of the tumor centroid position was used as a breathing surrogate. Deformation vectors and surrogate measurements were used to determinemore » motion model parameters. Model error was evaluated and subsequent treatment cines were predicted from breathing surrogate data. A simulated CT cine was created by generating breathing-gated volumetric images at 0.25 second intervals along the measured breathing trace, selecting a sagittal slice and downsampling to the resolution of the MR cines. A motion model was built using the first half of the simulated cine data. Model accuracy and error in predicting the remaining frames of the cine were evaluated. Results: Mean difference between model predicted and deformably registered lung tissue positions for the 28 second preview MR cine acquired before treatment was 0.81 +/− 0.30 mm. The model was used to predict two minutes of the subsequent treatment cine with a mean accuracy of 1.59 +/− 0.63 mm. Conclusion: Inplane motion models were built using MR cine images and evaluated for accuracy and ability to predict future respiratory motion from breathing surrogate measurements. Examination of long term predictive ability is ongoing. The technique was applied to simulated CT cines for further validation, and the authors are currently investigating use of in-plane models to update pre-existing volumetric motion models used for generation of breathing-gated CT planning images.« less

The effects of rigid motions on elastic network model force constants

PubMed Central

Lezon, Timothy R.

2012-01-01

Elastic network models provide an efficient way to quickly calculate protein global dynamics from experimentally determined structures. The model’s single parameter, its force constant, determines the physical extent of equilibrium fluctuations. The values of force constants can be calculated by fitting to experimental data, but the results depend on the type of experimental data used. Here we investigate the differences between calculated values of force constants _t to data from NMR and X-ray structures. We find that X-ray B factors carry the signature of rigid-body motions, to the extent that B factors can be almost entirely accounted for by rigid motions alone. When fitting to more refined anisotropic temperature factors, the contributions of rigid motions are significantly reduced, indicating that the large contribution of rigid motions to B factors is a result of over-fitting. No correlation is found between force constants fit to NMR data and those fit to X-ray data, possibly due to the inability of NMR data to accurately capture protein dynamics. PMID:22228562

Estimation of contour motion and deformation for nonrigid object tracking

NASA Astrophysics Data System (ADS)

Shao, Jie; Porikli, Fatih; Chellappa, Rama

2007-08-01

We present an algorithm for nonrigid contour tracking in heavily cluttered background scenes. Based on the properties of nonrigid contour movements, a sequential framework for estimating contour motion and deformation is proposed. We solve the nonrigid contour tracking problem by decomposing it into three subproblems: motion estimation, deformation estimation, and shape regulation. First, we employ a particle filter to estimate the global motion parameters of the affine transform between successive frames. Then we generate a probabilistic deformation map to deform the contour. To improve robustness, multiple cues are used for deformation probability estimation. Finally, we use a shape prior model to constrain the deformed contour. This enables us to retrieve the occluded parts of the contours and accurately track them while allowing shape changes specific to the given object types. Our experiments show that the proposed algorithm significantly improves the tracker performance.

Main Cause of the Poloidal Plasma Motion Inside a Magnetic Cloud Inferred from Multiple-Spacecraft Observations

NASA Astrophysics Data System (ADS)

Zhao, Ake; Wang, Yuming; Chi, Yutian; Liu, Jiajia; Shen, Chenglong; Liu, Rui

2017-04-01

Although the dynamical evolution of magnetic clouds (MCs) has been one of the foci of interplanetary physics for decades, only few studies focus on the internal properties of large-scale MCs. Recent work by Wang et al. ( J. Geophys. Res. 120, 1543, 2015) suggested the existence of the poloidal plasma motion in MCs. However, the main cause of this motion is not clear. In order to find it, we identify and reconstruct the MC observed by the Solar Terrestrial Relations Observatory (STEREO)-A, Wind, and STEREO-B spacecraft during 19 - 20 November 2007 with the aid of the velocity-modified cylindrical force-free flux-rope model. We analyze the plasma velocity in the plane perpendicular to the MC axis. It is found that there was evident poloidal motion at Wind and STEREO-B, but this was not clear at STEREO-A, which suggests a local cause rather than a global cause for the poloidal plasma motion inside the MC. The rotational directions of the solar wind and MC plasma at the two sides of the MC boundary are found to be consistent, and the values of the rotational speeds of the solar wind and MC plasma at the three spacecraft show a rough correlation. All of these results illustrate that the interaction with ambient solar wind through viscosity might be one of the local causes of the poloidal motion. Additionally, we propose another possible local cause: the existence of a pressure gradient in the MC. The significant difference in the total pressure at the three spacecraft suggests that this speculation is perhaps correct.

Attitude determination using an adaptive multiple model filtering Scheme

NASA Technical Reports Server (NTRS)

Lam, Quang; Ray, Surendra N.

1995-01-01

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown

Attitude determination using an adaptive multiple model filtering Scheme

NASA Astrophysics Data System (ADS)

Lam, Quang; Ray, Surendra N.

1995-05-01

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown

Angular motion estimation using dynamic models in a gyro-free inertial measurement unit.

PubMed

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters.

Hand interception of occluded motion in humans: a test of model-based vs. on-line control

PubMed Central

Zago, Myrka; Lacquaniti, Francesco

2015-01-01

Two control schemes have been hypothesized for the manual interception of fast visual targets. In the model-free on-line control, extrapolation of target motion is based on continuous visual information, without resorting to physical models. In the model-based control, instead, a prior model of target motion predicts the future spatiotemporal trajectory. To distinguish between the two hypotheses in the case of projectile motion, we asked participants to hit a ball that rolled down an incline at 0.2 g and then fell in air at 1 g along a parabola. By varying starting position, ball velocity and trajectory differed between trials. Motion on the incline was always visible, whereas parabolic motion was either visible or occluded. We found that participants were equally successful at hitting the falling ball in both visible and occluded conditions. Moreover, in different trials the intersection points were distributed along the parabolic trajectories of the ball, indicating that subjects were able to extrapolate an extended segment of the target trajectory. Remarkably, this trend was observed even at the very first repetition of movements. These results are consistent with the hypothesis of model-based control, but not with on-line control. Indeed, ball path and speed during the occlusion could not be extrapolated solely from the kinematic information obtained during the preceding visible phase. The only way to extrapolate ball motion correctly during the occlusion was to assume that the ball would fall under gravity and air drag when hidden from view. Such an assumption had to be derived from prior experience. PMID:26133803

Application of multiple modelling to hyperthermia estimation: reducing the effects of model mismatch.

PubMed

Potocki, J K; Tharp, H S

1993-01-01

Multiple model estimation is a viable technique for dealing with the spatial perfusion model mismatch associated with hyperthermia dosimetry. Using multiple models, spatial discrimination can be obtained without increasing the number of unknown perfusion zones. Two multiple model estimators based on the extended Kalman filter (EKF) are designed and compared with two EKFs based on single models having greater perfusion zone segmentation. Results given here indicate that multiple modelling is advantageous when the number of thermal sensors is insufficient for convergence of single model estimators having greater perfusion zone segmentation. In situations where sufficient measured outputs exist for greater unknown perfusion parameter estimation, the multiple model estimators and the single model estimators yield equivalent results.

Test suite for image-based motion estimation of the brain and tongue

NASA Astrophysics Data System (ADS)

Ramsey, Jordan; Prince, Jerry L.; Gomez, Arnold D.

2017-03-01

Noninvasive analysis of motion has important uses as qualitative markers for organ function and to validate biomechanical computer simulations relative to experimental observations. Tagged MRI is considered the gold standard for noninvasive tissue motion estimation in the heart, and this has inspired multiple studies focusing on other organs, including the brain under mild acceleration and the tongue during speech. As with other motion estimation approaches, using tagged MRI to measure 3D motion includes several preprocessing steps that affect the quality and accuracy of estimation. Benchmarks, or test suites, are datasets of known geometries and displacements that act as tools to tune tracking parameters or to compare different motion estimation approaches. Because motion estimation was originally developed to study the heart, existing test suites focus on cardiac motion. However, many fundamental differences exist between the heart and other organs, such that parameter tuning (or other optimization) with respect to a cardiac database may not be appropriate. Therefore, the objective of this research was to design and construct motion benchmarks by adopting an "image synthesis" test suite to study brain deformation due to mild rotational accelerations, and a benchmark to model motion of the tongue during speech. To obtain a realistic representation of mechanical behavior, kinematics were obtained from finite-element (FE) models. These results were combined with an approximation of the acquisition process of tagged MRI (including tag generation, slice thickness, and inconsistent motion repetition). To demonstrate an application of the presented methodology, the effect of motion inconsistency on synthetic measurements of head- brain rotation and deformation was evaluated. The results indicated that acquisition inconsistency is roughly proportional to head rotation estimation error. Furthermore, when evaluating non-rigid deformation, the results suggest that

Test Suite for Image-Based Motion Estimation of the Brain and Tongue

PubMed Central

Ramsey, Jordan; Prince, Jerry L.; Gomez, Arnold D.

2017-01-01

Noninvasive analysis of motion has important uses as qualitative markers for organ function and to validate biomechanical computer simulations relative to experimental observations. Tagged MRI is considered the gold standard for noninvasive tissue motion estimation in the heart, and this has inspired multiple studies focusing on other organs, including the brain under mild acceleration and the tongue during speech. As with other motion estimation approaches, using tagged MRI to measure 3D motion includes several preprocessing steps that affect the quality and accuracy of estimation. Benchmarks, or test suites, are datasets of known geometries and displacements that act as tools to tune tracking parameters or to compare different motion estimation approaches. Because motion estimation was originally developed to study the heart, existing test suites focus on cardiac motion. However, many fundamental differences exist between the heart and other organs, such that parameter tuning (or other optimization) with respect to a cardiac database may not be appropriate. Therefore, the objective of this research was to design and construct motion benchmarks by adopting an “image synthesis” test suite to study brain deformation due to mild rotational accelerations, and a benchmark to model motion of the tongue during speech. To obtain a realistic representation of mechanical behavior, kinematics were obtained from finite-element (FE) models. These results were combined with an approximation of the acquisition process of tagged MRI (including tag generation, slice thickness, and inconsistent motion repetition). To demonstrate an application of the presented methodology, the effect of motion inconsistency on synthetic measurements of head-brain rotation and deformation was evaluated. The results indicated that acquisition inconsistency is roughly proportional to head rotation estimation error. Furthermore, when evaluating non-rigid deformation, the results suggest that

Pitching motion control of a butterfly-like 3D flapping wing-body model

NASA Astrophysics Data System (ADS)

Suzuki, Kosuke; Minami, Keisuke; Inamuro, Takaji

2014-11-01

Free flights and a pitching motion control of a butterfly-like flapping wing-body model are numerically investigated by using an immersed boundary-lattice Boltzmann method. The model flaps downward for generating the lift force and backward for generating the thrust force. Although the model can go upward against the gravity by the generated lift force, the model generates the nose-up torque, consequently gets off-balance. In this study, we discuss a way to control the pitching motion by flexing the body of the wing-body model like an actual butterfly. The body of the model is composed of two straight rigid rod connected by a rotary actuator. It is found that the pitching angle is suppressed in the range of +/-5° by using the proportional-plus-integral-plus-derivative (PID) control for the input torque of the rotary actuator.