Motion Variations Research Articles

Dim-Small Target Detection Based on Adaptive Pipeline Filtering

In order to improve the robustness of the pipeline target detection algorithm against strong noises and occlusion, this paper presents an adaptive pipeline filtering algorithm (APFA). In APFA, the velocity and the center of the target are firstly predicted based on the smooth motion trajectory after background suppression. Then, time-domain energy enhancement of targets is adopted to improve the obscure target detection, and adaptively updating the center and radius of the pipeline filter are carried out for targets’ motion variation. Experiments on five different typical scenes show that APFA can improve the robustness of the pipeline filter against strong noises and even when targets are temporarily obscured partially or completely. Simultaneously, APFA can significantly improve the energy and signal-to-noise ratio of targets, and as a result, the target detection rate is significantly promoted on all experiments.

Pilot beam-assisted adaptive compensation for atmospheric turbulence in free-space optical transmission of beams carrying orbital angular momentum

One of the major challenges for free-space optical (FSO) communication through atmosphere is the turbulence caused by the random variations in temperature and convective motion of air. It induces fluctuation in intensity and phase of the propagating optical signal and impairs the transmission quality. The FSO communication using beams carrying orbital angular momentum would be vulnerable to such fluctuation since they have a unique spatial phase profile of the helical phase front. In order to overcome the issue, we propose a pilot beam-assisted adaptive compensation method for the turbulence-induced phase fluctuation by using spatial light modulators and a wavefront sensor. The proposed method is a potential candidate for real-time compensation due to its fast operation without algorithmic converging process. The propagation of Laguerre–Gaussian beam through atmospheric turbulence is numerically analyzed based on the modified von Karman model and split-step beam propagation method. The simulation results reveal that the compensation performances are considerably improved by using the pilot beam which has the same azimuthal index as that of the data beam.

Effect of spatial variability of earthquake ground motions on the reliability of road system

This paper presents an approach for assessing the failure probability of a road system due to its interaction with landslides induced by the earthquake. The landslide occurrence and failure probability of the road system is estimated by considering the spatial variation of earthquake ground motion. Since significant incoherence in earthquake ground motions is usually observed within the spatial dimensions of large horizontally expanded structures like roads, bridges and dams, it is important to consider the uncertainty due to spatially varying ground motion. The stochastic nature of seismic loading is incorporated in the study by generating a series of earthquake ground motions while the spatial variation of ground motion is accounted for by using cross power spectral density function. Two phase material point method (MPM) is used to simulate the dynamic behaviour of saturated slopes. MPM is able to capture the failure mechanism of slopes under seismic loading and evaluates the travel distance of sliding mass.

Smoothness-oriented path optimization for robotic milling processes

Industrial robots are increasingly used for five-axis machining operations, where the rotation of the end effector along the tool-axis direction is functionally redundant. This functional redundancy should be carefully resolved when planning the robot path according to the tool path generated by a computer-aided manufacturing (CAM) system. Improper planning of the redundancy may cause drastic variations of the joint motions, which could significantly decrease the machining efficiency as well as the machining accuracy. To tackle this problem, this paper presents a new optimization-based methodology to globally resolve the functional redundancy for the robotic milling process. Firstly, a global performance index concerning the smoothness of the robot path at the joint acceleration level is proposed. By minimizing the smoothness performance index while considering the avoidance of joint limits and the singularity and the constraint of the stiffness performance, the resolution of the redundancy is formulated as a constrained optimization problem. To efficiently solve the problem, the sequential linearization programming method is employed to improve the initial solution provided by the conventional graph-based method. Then, simulations for a given tool path are presented. Compared with the graph-based method, the proposed method can generate a smoother robot path in which a significant reduction of the magnitude of the maximum joint acceleration is obtained, resulting in a smoother tool-tip feedrate profile. Finally, the experiment on the robotic milling system is also presented. The results show that the optimized robot path of the proposed method obtains better surface quality and higher machining efficiency, which verifies the effectiveness of the proposed method.

Phase-based Eulerian motion magnification reveals eardrum mobility from pneumatic otoscopy without sealing the ear canal

Pneumatic otoscopy is the recommended diagnostic method for middle ear infections. Physicians use a pneumatic otoscope to assess the position of the eardrum (bulging or retraction) as well as the eardrum mobility while an insufflation bulb is squeezed to generate air pressure changes in a sealed ear canal. While pneumatic otoscopy provides increased sensitivity and specificity by detecting decreased eardrum mobility, there exist many challenges to correctly perform and interpret results. For example, the ear canal must be sealed using a specialized ear speculum to deliver sufficiently large pressure changes that can induce visible movements of an eardrum. To overcome this challenge, video motion magnification is proposed to amplify pneumatic-induced motions of the eardrum without sealing of the ear canal. Pneumatic otoscopy is performed on adult subjects using a smartphone camera with an otoscope attachment at 60 frames per second, with pressure inputs at 5 Hz. Phase-based Eulerian motion magnification is applied to magnify spatiotemporal dependent motions in the video. As a result, the motion magnification of unsealed pneumatic otoscopy reveals comparable eardrum motions as in standard pneumatic otoscopy with a sealed ear canal. Furthermore, the estimated motions (in pixels) are quantified to examine the spatial and the temporal variations of the eardrum motions. The motion magnification may avoid the need for sealing the ear canal as well as decrease patient discomfort in pneumatic otoscopy, improving the capability and the usability as a point-of-care diagnostic tool in primary care and otology.

Eulerian video magnification: a review

<p>Many important subtle changes in the environment are invisible to the naked human eyes. These subtle changes occur because of colour variations, such as blood flow in a human face that leads to face colour change, or motion variations, such as vena movement under human skin and vibration of buildings. The human eye requires optical microscopes to detect these variations. Alternatively, new technologies, such as high-speed imagery and computer processing, can be used to detect these variations. These computerised microscopes depend on computation rather than optical amplification to amplify subtle colour and motion changes in videos. The most popular technique to achieve computation-based microscope is the Eulerian video magnification (EVM). However, several challenges in EVM still need to be solved to meet the requirements of real time and video quality. This paper presents a comprehensive study of EVM methods and reviews the related literature. The strengths and drawbacks of existing works are discussed, and the important research fields and challenges in the area of EVM are concluded.</p>

An unaccounted component on the Prometheus and Pandora offset angular positions

Near the turning of this millennium (1996–2004) it was detected that Prometheus and Pandora were not in their angular positions as predicted from their discoveries by the Voyager spacecrafts (1980). This is known as the problem of the lags of Prometheus and Pandora. The explanation for the origin of these lags is the chaotic motion associated with 121:118 mean motion resonance between the satellites. In the present work we revisit this problem and adopting the most extensive set of lags data, given by [R.G. French et al., Icarus 162, 143 (2003)], to show the need of unaccounted effects to produce the measured lags. By the analysis of conservation of angular momentum it can be verified that the mutual interaction between Prometheus and Pandora should be inversely proportional to the ratio of their masses. In this way, only the gravitational interaction between the two satellites does not explain such values. Consequently, the ratio between the lags of Prometheus and Pandora, Q, should be constant, and approximately the value of the inverse ratio between their masses (0.56, from [R.G. French et al., Icarus 162, 143 (2003)]). However, the values of Q from the measured lags are much higher, ranging from 48% up to 68% larger. Beyond that, the values increase over time in a rate given by the equation Q(t = 0.067 + 0.013t). Therefore, this analysis clearly shows the need of other mechanisms beyond the mutual interaction between Prometheus and Pandora in order to produce such values of lags. We estimate that at least one effect that produces an additional variation of mean motion of about 0.45°/year in one of the satellites for about 20 years would be necessary.

Automatic Video Segmentation Based on Information Centroid and Optimized SaliencyCut

We propose an automatic video segmentation method based on an optimized SaliencyCut equipped with information centroid (IC) detection according to level balance principle in physical theory. Unlike the existing methods, the image information of another dimension is provided by the IC to enhance the video segmentation accuracy. Specifically, our IC is implemented based on the information-level balance principle in the image, and denoted as the information pivot by aggregating all the image information to a point. To effectively enhance the saliency value of the target object and suppress the background area, we also combine the color and the coordinate information of the image in calculating the local IC and the global IC in the image. Then saliency maps for all frames in the video are calculated based on the detected IC. By applying IC smoothing to enhance the optimized saliency detection, we can further correct the unsatisfied saliency maps, where sharp variations of colors or motions may exist in complex videos. Finally, we obtain the segmentation results based on IC-based saliency maps and optimized SaliencyCut. Our method is evaluated on the DAVIS dataset, consisting of different kinds of challenging videos. Comparisons with the state-of-the-art methods are also conducted to evaluate our method. Convincing visual results and statistical comparisons demonstrate its advantages and robustness for automatic video segmentation.

On the rotational motion of NEAs during close encounters with the Earth

During their lifetime, the Near-Earth Asteroids (NEAs) suffer numerous close encounters (CE) with Earth, Mars and Venus. It has been demonstrated that gravitational interactions during close planetary encounters can alter an asteroid’s spin state, and hence, along with collisions, play a role in the rotational evolution of NEAs. The variation of the rotational angular momentum during the encounters can increase or decrease the rotation rate depending on the initial condition. In addition to the rotation rate, close encounters cause variation in the movement of precession and nutation of the asteroid. Using a numerical model that takes into account the spin-orbit coupling of a body with ellipsoidal shape, the subject of this study is to analyze the rotational motion (rotation, precession and nutation) of asteroids during CE with the Earth for different initial conditions. We computed the variation of the obliquity and the variation of spin period after the CE. We found significant change in obliquity and spin period only in cases with strong encounter, that is in cases that the impact parameter of the encounter (1.2 ≤ d ≤ 7 (Earth radii) and the relative velocity (v) are small. Our results also show that the variation of rotational motion due to the close encounter is capable of tumbling the axis of rotation and gravitational rupture may occur in a few cases.

Style‐Controllable Speech‐Driven Gesture Synthesis Using Normalising Flows

AbstractAutomatic synthesis of realistic gestures promises to transform the fields of animation, avatars and communicative agents. In off‐line applications, novel tools can alter the role of an animator to that of a director, who provides only high‐level input for the desired animation; a learned network then translates these instructions into an appropriate sequence of body poses. In interactive scenarios, systems for generating natural animations on the fly are key to achieving believable and relatable characters. In this paper we address some of the core issues towards these ends. By adapting a deep learning‐based motion synthesis method called MoGlow, we propose a new generative model for generating state‐of‐the‐art realistic speech‐driven gesticulation. Owing to the probabilistic nature of the approach, our model can produce a battery of different, yet plausible, gestures given the same input speech signal. Just like humans, this gives a rich natural variation of motion. We additionally demonstrate the ability to exert directorial control over the output style, such as gesture level, speed, symmetry and spacial extent. Such control can be leveraged to convey a desired character personality or mood. We achieve all this without any manual annotation of the data. User studies evaluating upper‐body gesticulation confirm that the generated motions are natural and well match the input speech. Our method scores above all prior systems and baselines on these measures, and comes close to the ratings of the original recorded motions. We furthermore find that we can accurately control gesticulation styles without unnecessarily compromising perceived naturalness. Finally, we also demonstrate an application of the same method to full‐body gesticulation, including the synthesis of stepping motion and stance.

Numerical simulations of shear-induced consecutive coronal mass ejections

Context. It is widely accepted that photospheric shearing motions play an important role in triggering the initiation of coronal mass ejections (CMEs). Even so, there are events for which the source signatures are difficult to locate, while the CMEs can be clearly observed in coronagraph data. These events are therefore called ‘stealth’ CMEs. They are of particular interest to space weather forecasters, since eruptions are usually discarded from arrival predictions if they appear to be backsided, which means not presenting any clear low-coronal signatures on the visible solar disc. Such assumptions are not valid for stealth CMEs since they can originate from the front side of the Sun and be Earth-directed, but they remain undetected and can therefore trigger unpredicted geomagnetic storms. Aims. We numerically model and investigate the effects of shearing motion variations onto the resulting eruptions and we focus in particular on obtaining a stealth CME in the trailing current sheet of a previous ejection. Methods. We used the 2.5D magnetohydrodynamics package of the code MPI-AMRVAC to numerically simulate consecutive CMEs by imposing shearing motions onto the inner boundary, which represents, in our case, the low corona. The initial magnetic configuration consists of a triple arcade structure embedded into a bimodal solar wind, and the sheared polarity inversion line is found in the southern loop system. The mesh was continuously adapted through a refinement method that applies to current carrying structures, allowing us to easily track the CMEs in high resolution, without resolving the grid in the entire domain. We also compared the obtained eruptions with the observed directions of propagation, determined using a forward modelling reconstruction technique based on a graduated cylindrical shell geometry, of an initial multiple coronal mass ejection (MCME) event that occurred in September 2009. We further analysed the simulated ejections by tracking the centre of their flux ropes in latitude and their total speed. Radial Poynting flux computation was employed as well to follow the evolution of electromagnetic energy introduced into the system. Results. Changes within 1% in the shearing speed result in three different scenarios for the second CME, although the preceding eruption seems insusceptible to such small variations. Depending on the applied shearing speed, we thus obtain a failed eruption, a stealth, or a CME driven by the imposed shear, as the second ejection. The dynamics of all eruptions are compared with the observed directions of propagation of an MCME event and a good correlation is achieved. The Poynting flux analysis reveals the temporal variation of the important steps of eruptions. Conclusions. For the first time, a stealth CME is simulated in the aftermath of a first eruption, originating from an asymmetric streamer configuration, through changes in the applied shearing speed, indicating it is not necessary for a closed streamer to exist high in the corona for such an event to occur. We also emphasise the high sensitivity of the corona to small changes in motions at the photosphere, or in our simulations, at the low corona.

Liquefaction of a sloping deposit: LEAP-2017 centrifuge tests at Rensselaer Polytechnic Institute

A series of centrifuge tests of a sloping ground were conducted at Rensselaer Polytechnic Institute (RPI). These tests were used to monitor and assess the soil response, in terms of generated accelerations, excess pore water pressure (EPWP) and associated lateral spreading, as a function of variations in the dynamic input motion and soil relative density. This series of tests are part of the Liquefaction Experiments and Analysis Projects (LEAP-2017), an international effort to assess the repeatability and reproducibility of centrifuge experimental results, and verify and validate soil liquefaction numerical tools using the experimental data.

Development of cycle-to-cycle variation of the tumble flow motion in a cylinder of a spark ignition internal combustion engine with Miller cycle

Reducing the cycle-to-cycle variation in an engine is a key to expanding the operational limits of high-efficiency engines such as lean-burn engines. The cycle-to-cycle variation of the engine output is caused by unstable combustion and is especially induced by the cycle-to-cycle variation of the in-cylinder flow. This investigation aims to clarify how the cycle-to-cycle variation of in-cylinder flow develops during intake and compression strokes. To achieve this aim, 12 kHz time-resolved particle image velocimetry measurements were conducted on the symmetrical vertical plane in a four-valve, four-stroke optically accessible engine. This study focuses on the relationship between the flow at the plug position at the ignition timing and the flow distribution in the intake and compression stroke. Correlation map analysis reveals this relationship, and some flow distributions are extracted. The fluctuations in the flow distribution induce the cycle-to-cycle variation of the flow direction at the plug position at the ignition timing, the position of the stagnation plane between the intake flow from the intake valves and the upper side of the tumble vortex, the strength of the blowback flow into the intake port generated by the Miller cycle, and the position of the tumble vortex in the late compression stroke. The flow distributions extracted by the correlation map analysis clearly change between cycles. These results also suggest that correlation map analysis is an effective way to elucidate the factors that induce the cycle-to-cycle variation of the in-cylinder flow.

Bias thermal stability improvement of MEMS gyroscope with quadrature motion correction and temperature self‐sensing compensation

Bias thermal stability of microelectromechanical system (MEMS) gyroscope is a significant performance parameter for industrial and tactical applications. The quadrature coupling motion and demodulation phase error are two main sources of bias drift. This work presents a MEMS tuning fork gyroscope with dedicated electrostatic correction combs finger structure that can be implemented to suppress the quadrature motion. By utilising a closed-loop control for the coupling stiffness, the temperature variation of quadrature motion achieves >260 times of magnitude reduction, resulting in the thermal bias drift decreased from 0.98 to 0.18°/s with 5.4 times improvement over the temperature from −40 to 60°C. The results indicate that the variation of the quadrature motion is the dominant factor that determines the temperature bias drift of the custom-designed gyroscope. The compensated bias stability (1σ) is measured to be ∼8.6°/h by using temperature self-sensing compensation technique over the whole temperature operating range, which demonstrates a considerably competitive result for the tactical-grade MEMS gyroscope.

The Dynamic Characteristics of a Small Hydraulic Poppet Safety Relief Valve

Hydraulic poppet pressure relief valve, which has the advantages of fast response and good sealing performance, is extensively used in the hydraulic industry. In this paper, a two-dimensional axisymmetric geometry model of the hydraulic poppet safety relief valve with a small size is established. Dynamic mesh, along with UDF in FLUENT software, is used in this study. The dynamic characteristics of a hydraulic poppet safety relief valve using CFD are investigated under different conditions. For incompressible hydraulic oil, a sharp force rise and collapse caused by a redirection of the fluid flow due to inertia forces is depicted, and the variation of the poppet motion under the influence of the back pressure is analyzed based on the flow information. The dynamic behavior of the hydraulic poppet relief valve under different set pressure is investigated. In the end, a numerical study on the instability of the poppet relief valve supplying a constant volumetric flow rate is performed, and the chatter frequency is obtained.

Robust Visual Tracking Based on Fusional Multi-Correlation-Filters with a High-Confidence Judgement Mechanism

Visual object trackers based on correlation filters have recently demonstrated substantial robustness to challenging conditions with variations in illumination and motion blur. Nonetheless, the models depend strongly on the spatial layout and are highly sensitive to deformation, scale, and occlusion. As presented and discussed in this paper, the colour attributes are combined due to their complementary characteristics to handle variations in shape well. In addition, a novel approach for robust scale estimation is proposed for mitigatinge the problems caused by fast motion and scale variations. Moreover, feedback from high-confidence tracking results was also utilized to prevent model corruption. The evaluation results for our tracker demonstrate that it performed outstandingly in terms of both precision and accuracy with enhancements of approximately 25% and 49%, respectively, in authoritative benchmarks compared to those for other popular correlation- filter-based trackers. Finally, the proposed tracker has demonstrated strong robustness, which has enabled online object tracking under various scenarios at a real-time frame rate of approximately 65 frames per second (FPS).

Order patterns, their variation and change points in financial time series and Brownian motion

Order patterns and permutation entropy have become useful tools for studying biomedical, geophysical or climate time series. Here we study day-to-day market data, and Brownian motion which is a good model for their order patterns. A crucial point is that for small lags (1 up to 6 days), pattern frequencies in financial data remain essentially constant. The two most important order parameters of a time series are turning rate and up-down balance. For change points in EEG brain data, turning rate is excellent while for financial data, up-down balance seems the best. The fit of Brownian motion with respect to these parameters is tested, providing a new version of a forgotten test by Bienaymé.

Berry-Esséen bounds and almost sure CLT for the quadratic variation of the sub-bifractional Brownian motion

Let be the sub-bifractional Brownian motion(sbBm) of dimension 1, with indices and By using the Malliavin calculus and the Stein’s method, we mainly obtain Berry-Esséen bounds and prove the almost sure central limit theorem (ASCLT) for the quadratic variation of the sub-bifractional Brownian motion.

Analysis and modeling of ground motion coherency at uniform site conditions

In this work, nonstationary ground motion coherency analysis and modeling are performed using wavelet analysis and relevance vector machine regression. Earthquake ground motion data from four events recorded at dense seismograph SMART-1 array in north-south and east-west horizontal directions are used to investigate the lagged coherency behavior. Wavelet transform is used to compute the nonstationary lagged coherency that characterizes the space-time variation of seismic ground motion. Lagged coherency behavior with frequency, distance, and time is examined. It is shown that the lagged coherency is a time-varying quantity. The results implied that the lagged coherency on uniform soil is relatively insensitive to the earthquake events, and depends mainly on time, frequency, and separation distance. Relevance Vector Machines (RVM) regression is used to develop a model for nonstationary lagged coherency that characterizes the space-time variation of seismic ground motion. Earthquake ground motion in the in the north-south and the first principal directions is used to determine the lagged coherency model. The proposed model does not require a fixed parametric functional form. The developed model can estimate the lagged coherency for different separation distances at different time instants and frequencies.

Ship roll restoring moment calculation in beam sea condition

Accurate calculation of restoring moment, virtual mass moment of inertia and damping moment increases the accuracy of a ship’s dynamic stability simulation. The current methods of approximating the roll restoring moment are based on hydrostatic calculations. These methods fail to consider the dynamic conditions and variation of upward buoyancy and wave location with respect to the model. In the current study, experimental and numerical simulations are conducted at beam sea condition to investigate the behaviour of model. The model is excited by regular waves at different heights and frequencies to measure the motion characteristics and the restoring moment in dynamic conditions. The motion characteristics of the model obtained from the numerical simulation are compared against the experimental measurements, and a good agreement is found. The results show that the restoring moments in the dynamic condition have significant differences compared to the static condition. The magnitude of restoring moment in dynamic condition is measured based on the variation of heave motion of the model and the location of the wave’s crest and trough with respect to the model.