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Rainbow particle tracking velocimetry can be used to measure 3D3C flow velocity vectors with a single color camera. The particle depth position is calculated from the hue degree of a particle color. A liquid–crystal display (LCD) projector can be used conveniently as a light source of the color pattern in place of the spectral diffraction of white light. Another advantage of using an LCD projector is the ability to change the RGB components of the color pattern. In this study, the rainbow color pattern was modified to increase available color. Colors with the same hue degree but different saturations were used in the color pattern. Using color space enhanced positional resolution in the color change direction. The parameters of new color patterns were number of cycles, saturation continuity and range of color space. They were designed and their performances were compared. The effective resolution in color change direction enhanced 2.4 times from original patten (single cycle rainbow), and velocity vector acquisition rate improved, in particular, for the range of small amount movement per step. [ABSTRACT FROM AUTHOR]

To accelerate the convergence rate of high-dimensional optimization problems, inspired by the cooperative hunting process of spider colonies named Anelosimus eximius, a new A. eximius colony algorithm (AECA) was proposed to solve combinatorial optimization problems. In the AECA, a certain direction component of the problem solution is represented as a certain direction in which a spider travels, so that a high-dimensional optimization problem can be transformed into multiple low-dimensional optimization problems. The AECA includes two intelligent behaviors: the random walk of spiders and the summoning of the initiator. The random walk of spiders ensures the diversity of spider colonies, whereas the summoning of the initiator can accelerate the convergence rate. We theoretically proved that the AECA is globally convergent. The inversion method of asteroid spectrum reflectance template can be used to solve the problem that the measured planetary spectrum is affected by the asteroid absorption effect and improves the accuracy of celestial Doppler difference velocimetry, which uses celestial spectrum to provide the information of velocity measurement for navigation. The essence of this method is the optimal combination problem of intrinsic mode functions (IMFs). We applied the AECA to the inversion of the planetary spectrum reflectance template. Experimental results show that, compared with genetic algorithms (GAs), the AECA can obtain the optimal combination of spectrum reflectance templates faster. In addition, to verify the universality of the AECA, for the classical knapsack problem, the AECA has a better optimization effect, faster convergence rate, and higher stability than other swarm intelligence algorithms such as GA, discrete particle swarm optimization, and the quantum genetic algorithm. [ABSTRACT FROM AUTHOR]

The performance of Doppler velocity logs (DVLs) in terms of velocity estimate error is directly linked to the geometry of the beam and the pulse transmitted. Beyond a specific transmitted bandwidth, the phase‐shift beamformer can introduce significant errors in velocity estimation. To delineate the operating mechanism of phase‐shift errors within a phased array of acoustic DVLs, the correlation between bottom echo and velocity distribution, in conjunction with the power‐weighted function, was initially examined predicated on spectral estimation theory. Subsequently, numerical and analytical models of the Gaussian‐shaped Doppler spectrum were formulated. The models are employed to evaluate the velocity estimation inaccuracies attributed to phase shifts in extant DVLs, and the comparative results with field experiments corroborate the model's efficacy in forecasting errors. The theoretical findings evaluate the performance limitations of the current phased array transducer design and provide insights for developing new designs. Pool experimental results show that this design effectively reduces the velocity estimation error caused by phase shift under static conditions and in the presence of Doppler frequencies to a level of almost complete elimination of the error compared to conventional configurations. [ABSTRACT FROM AUTHOR]

Purpose: This study analyzed the acute mechanical response to three workouts of the day (WOD) protocols in as many repetitions as possible (AMRAP), every minute on the minute (EMOM), and for time (FT) models by quantifying the degree of mechanical fatigue induced by popular resistance exercises in the Cross modalities, front squat (FS), and shoulder press (SP). We also analyzed whether the exercises' fastest velocity (Vfastest) could be an objective indicator of relative intensity (%1RM). Methods: Nine trained men performed three FS and SP exercises protocols. The degree of fatigue was quantified by the velocity loss (VL) achieved in both exercises and the velocity loss achieved in the WOD (VLWOD). Results: The VLWOD in the AMRAP, EMOM, and FT protocols was 73.2 ± 10.9%, 61.6 ± 15.1%, and 76.1 ± 8.8%, respectively. In the AMRAP and FT protocol, the Vfastest showed very strong relationships with the %1RM for FS and SP (r = -0.83, -0.75, respectively, p < .01); while in the EMOM protocol, there was a strong relationship between these variables, only for the SP (r = -0.61, p < .05). In the FT protocol, we observed an extremely strong relationship for FS (r = -0.91, p < .001) and very strong (r = -0.71, p < .05) for SP between these variables. Conclusion: Therefore, the AMRAP and FT training models induce the highest degrees of mechanical fatigue in the FS and SP exercises, and the Vfastest is a reliable tool for estimating relative intensity in resistance exercises of Cross modalities. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To assess the validity of different commercial portable velocity testing devices in strength training by systematic and Meta-analysis method. METHODS: Related articles were searched in Web of Science, PubMed, and CNKI databases. “Appraisal of Study Design for Psychometric Articles” was used as a scale to evaluate the quality of the included studies. In both fixed and random effect models, the Pearson correlated coefficient (r) was aggregated by R language to conduct a Meta-analysis of different types of speed measurement devices. RESULTS: A total of 44 and 16 studies were included for qualitative and quantitative analysis, respectively. The general quality of included studies was moderate. Twenty-six brands of velocity testing devices were involved. Qualitative findings in validity: line position transducers and video-based devices < iPhone APP and accelerators, Smith machine > free weight. Quantitative findings in validity: GymAware had high validity for measuring mean velocity [low intensity: r=0.98, 95% confidence interval (CI): 0.95-0.99; medium intensity: r=0.98, 95% CI: 0.95-0.99; high intensity: r=0.98, 95% CI: 0.96-0.99] and peak velocity (low intensity: r=0.99, 95% CI: 0.97-0.99; medium intensity: r=0.98, 95% CI: 0.97-0.99; high intensity: r=0.95, 95% CI: 0.97-0.99) in free weight, with a positive correlation with the gold standard (P=0.001). Push had poor validity for measuring mean velocity (low intensity: r=0.69, 95% CI: 0.49-0.82; medium intensity: r=0.69, 95% CI: 0.37-0.86; high intensity: r=0.48, 95% CI: 0.21-0.68) and peak velocity (low intensity: r=0.71, 95% CI: 0.52-0.83; medium intensity: r=0.82, 95% CI: 0.69-0.89; high intensity: r=0.68, 95% CI: 0.37-0.85) in free weight, with a positive correlation with the gold standard (P=0.001). CONCLUSION: Existing evidence has confirmed that line position transducer and video-based device have the highest validity, iPhone APP takes the second place, and accelerators are poor in validity. High-valid line position transducers and video-based devices should be applied in velocity-based training rather than accelerators. [ABSTRACT FROM AUTHOR]

An integrated interferometric fiber optic velocimetry sensor has been proposed and demonstrated at the central wavelength of 638 nm. The sensor is based on the principle of two laser-beams' interference. The light signal scattered from the particles or vapor is demodulated to measure the water surface velocity and water vapor velocity. Three velocity measurement experiments are carried out to measure the velocity, and the experimental data shows that the velocity increases linearly in the range of 4 mm·s−1 to 100 mm·s−1, with a slope of linear fitting curve of 0.99777 and the R-Square of 1.00000. The velocity calculated from frequency shift fits well with the reference velocity. The maximum average relative error in the three velocity measurements is less than 2.5%. In addition, the maximum speed of 4.398 m·s−1 is confirmed in the rotating disk calibration experiment, which expands the sensor's velocity measurement range. To solve the problem that it is difficult to directly measure the velocity of small-scale water surface flow velocity, especially from the aspect of the low velocity of air-water surface, the interferometric fiber optic sensor can be applied to the measurement of water surface velocity and wind velocity on the water surface. [ABSTRACT FROM AUTHOR]

We have developed a new method for measuring temperature and velocity at a high spatial resolution (minimum 2.56 mm pitch along an optical fiber). The developed method uses the same principle as a hot wire anemometer, where the velocity perpendicular to an optical fiber is estimated as a function of the cooling curve of a gold-coated layer on the optical fiber Joule-heated intermittently. The developed optical fiber sensor demonstrated the ability to acquire a transient velocity profile in airflow experiments with high repeatability and accuracy. This paper describes optical fiber-based velocity measurement in the velocity range of approximately 0–7 m/s with an error of approximately 10% compared to a hot wire anemometer and a new method for simultaneous temperature and velocity measurements. Applicability to velocity distribution measurements and seconds transient velocity changes are also described. [ABSTRACT FROM AUTHOR]

In this paper, based on the principle of charge induction, a new velocity measurement method is proposed. A moving target generates a low-frequency electric field, which can be induced with an electrode and detection frontend. Velocity measurements are achieved by placing two electrodes at a fixed distance to detect the characteristic times. Firstly, the electric field generated by the moving target is modeled, and the theoretical output of the detection frontend is obtained via a simulation of the target passing by a single electrode. Then, according to the theoretical output, the velocity measurement simulation results of double electrodes are given for various driving conditions, such as a single vehicle driving in a single lane, a single vehicle changing lanes, two vehicles driving close together, and a multiple-vehicle situation. Finally, the above driving conditions are experimentally verified in sunny weather, windy and rainy weather, and a night environment. [ABSTRACT FROM AUTHOR]

• Arrayed fibers and a line scan camera are used for the transmission and acquisition of signals. • The system uses the high line rate of the line scan camera to measure the velocity. • It uses arrayed fibers with known spacing to measure the dimension. • The results are analyzed with digital image processing techniques. This paper presents a laser screen imaging measurement system (LSIMS) based on arrayed fibers to measure the velocity and dimension of a flying object. A laser diode is connected to the emission module of the laser screen via a single-mode fiber, then the emitted light beam is collimated into a parallel beam with a lens, this structure is arrayed to form the laser screen. The receiving module of the laser screen employs a cylindrical lens array to converge the collimated beams into a focal line. The input ends of the plastic fibers are arrayed along this focal line, while the output ends are imaged on the sensor of a line scan camera (LSC) through a lens. The LSIMS effectively modulates the process of a flying object passing through the laser screen into the light intensity change in the plastic fibers. The velocity and dimension of the flying object are subsequently measured through the analysis of the image obtained by the LSC. The timing accuracy of the LSIMS is verified through experiments. The velocity and diameter of pellets launched by a slingshot are measured and analyzed for errors. [ABSTRACT FROM AUTHOR]

As an important part of hydrometry, river discharge monitoring plays an irreplaceable role in the planning and management of water resources and is an essential element and necessary means of river management. Due to its benefits of simplicity, efficiency and safety, Space-Time Image Velocimetry (STIV) has attracted attention from all around the world. The most crucial component of the STIV is the detection of the Main Orientation of Texture (MOT), and the precision of detection directly affects the results of calculations. However, due to the complicated river flow characteristics and the harsh testing environment in the field, a large amount of noise and interfering textures show up in the space-time images, which affects the detection results of the MOT. In response to the shortage of noise and interference texture, a new non-contact image analysis method is developed. Firstly, Multi-scale Retinex (MSR) is proposed to pre-process the images for contrast enhancement; secondly, a fourth-order Gaussian derivative steerable filter is employed to enhance the structure of the texture; next, based on the probability density distribution function and the orientations of the enhanced images, the noise suppression function and the orientation-filtering function are designed to filter out the noise to highlight the texture. Finally, the Fourier Maximum Angle Analysis (FMAA) is used to filter out the noise further and obtain the clear orientations to achieve the measurement of velocity and discharge. The experimental results show that, compared with the widely used image velocimetry measurements, the accuracy of our method in the average velocity and flow discharge is significantly improved, and the real-time performance is excellent. [ABSTRACT FROM AUTHOR]

We formulate a physics-informed compressed sensing (PICS) method for the reconstruction of velocity fields from noisy and sparse phase-contrast magnetic resonance signals. The method solves an inverse Navier-Stokes boundary value problem, which permits us to jointly reconstruct and segment the velocity field, and at the same time infer hidden quantities such as the hydrodynamic pressure and the wall shear stress. Using a Bayesian framework, we regularize the problem by introducing a priori information about the unknown parameters in the form of Gaussian random fields. This prior information is updated using the Navier-Stokes problem, an energy-based segmentation functional, and by requiring that the reconstruction is consistent with the $k$ -space signals. We create an algorithm that solves this inverse problem, and test it for noisy and sparse $k$ -space signals of the flow through a converging nozzle. We find that the method is capable of reconstructing and segmenting the velocity fields from sparsely-sampled (15% $k$ -space coverage), low ($\sim 10$) signal-to-noise ratio (SNR) signals, and that the reconstructed velocity field compares well with that derived from fully-sampled (100% $k$ -space coverage) high ($> 40$) SNR signals of the same flow. [ABSTRACT FROM AUTHOR]

In this work, we propose a novel deep learning reconstruction framework for rapid and accurate reconstruction of 4D flow MRI data. Reconstruction is performed on a slice-by-slice basis by reducing artifacts in zero-filled reconstructed complex images obtained from undersampled k-space. A deep residual attention network FlowRAU-Net is proposed, trained separately for each encoding direction with 2D complex image slices extracted from complex 4D images at each temporal frame and slice position. The network was trained and tested on 4D flow MRI data of aortic valvular flow in 18 human subjects. Performance of the reconstructions was measured in terms of image quality, 3-D velocity vector accuracy, and accuracy in hemodynamic parameters. Reconstruction performance was measured for three different k-space undersamplings and compared with one state of the art compressed sensing reconstruction method and three deep learning-based reconstruction methods. The proposed method outperforms state of the art methods in all performance measures for all three different k-space undersamplings. Hemodynamic parameters such as blood flow rate and peak velocity from the proposed technique show good agreement with reference flow parameters. Visualization of the reconstructed image and velocity magnitude also shows excellent agreement with the fully sampled reference dataset. Moreover, the proposed method is computationally fast. Total 4D flow data (including all slices in space and time) for a subject can be reconstructed in 69 seconds on a single GPU. Although the proposed method has been applied to 4D flow MRI of aortic valvular flows, given a sufficient number of training samples, it should be applicable to other arterial flows. [ABSTRACT FROM AUTHOR]

Different models have been used to evaluate the interfacial Dzyaloshinskii–Moriya interaction (DMI) from the asymmetric bubble expansion method using magneto-optics. Here, we investigate the most promising candidates over a range of different magnetic multilayers with perpendicular anisotropy. Models based on the standard creep hypothesis are not able to reproduce the domain wall (DW) velocity profile when the DW roughness is high. Our results demonstrate that the DW roughness and the interface roughness of the sample layers are correlated. Furthermore, we give guidance on how to obtain reliable results for the DMI value with this popular method. A comparison of the results with Brillouin light scattering (BLS) measurements on the same samples shows that the BLS approach often results in higher measured values of DMI. [ABSTRACT FROM AUTHOR]

This article presents the novel structure of an eddy current sensor for linear speed measurements. The sensor has one excitation coil and two pairs of antiserially connected pick-up coils, which are located inside and outside the excitation coil. The design and modeling of the sensor are considered with an air core and with a magnetic yoke (core) to compare their performances in terms of sensitivity and nonlinearity error. The experiments and the analysis are performed at different excitation frequencies and speeds. A novel three-dimensional analytical method is developed and utilized for parametric analysis and for the design of this sensor. The simulation results are compared with measurements up to 16.7 m/s (60 km/h). The achieved nonlinearity error is as low as 0.3%. [ABSTRACT FROM AUTHOR]

As the higher order or generalized extended state observer (ESO), generalized proportional-integral (GPI) observer (GPIO) haves been proposed to enhance the active disturbance rejection (ADR) control (ADRC) system's disturbance rejection ability. However, different ADR controllers can be deduced based on the same order GPIO, resulting in different dynamic performances. In this article, ten different ADR controllers based on the fourth order GPIO are present. In order to reveal the relationship between these ADR controllers and the conventional ADR controllers based on the third order ESO, six different third-order-ESO-based ADR controllers are present and compared with the fourth-order-ESO-based ADR controllers. To ease the comparison between different ADRC systems, a common expression is built for different ADR controllers. A novel frequency-domain analysis method is also introduced to reveal how the observer and feedback control law affects the closed-loop control system's dynamic performance. The effectiveness of the proposed method is verified on the test bench based on dSPACE DS1103. [ABSTRACT FROM AUTHOR]

Millimeter-wave vehicle-to-vehicle communication systems with multiple-input multiple-output antenna array have drawn significant attention because it is expected to satisfy the growing bandwidth requirements for the cooperative intelligent transportation systems. However, maintaining high-quality communication links between communicating vehicles without high overhead is a challenging problem due to the high mobility of vehicles. In this paper, we propose a beam management algorithm with spatially distributed antenna subarrays instead of a single co-located antenna array. Unlike existing methods, we use distributed antenna subarrays to exploit the geometric relationship of the beam directions and the relative distance between communicating vehicles. We reduce the beam alignment errors by minimizing the sum of squared errors between the estimated beam direction after the beam training process and the refined beam direction derived from the measured position and velocity data. Additionally, a position data request protocol is devised to reduce the beam refining errors. Numerical results demonstrate that the proposed beam management algorithm successfully reduces the beam alignment errors and it is robust to position and velocity measurement errors. [ABSTRACT FROM AUTHOR]

Human-on-the-loop (HOTL) system is regarded as a promising technology to allow autonomous underwater vehicle (AUV) to track the most adequate target point as soon as possible. However, the unique characteristics of the underwater environment make it challenging to perform the tracking task. This article is concerned with a finite-time tracking control issue for AUV, subjected to unavailable velocity signals in the measurement side and uncertain model parameters in physical side. A HOTL system, including operator, buoys, AUV and sensors, is first provided to construct a cooperative tracking network. For such system, operator in surface control center decides the tracking mission based on all available data. Then, a buoy-assisted localization estimator is utilized by AUV to acquire its position, through which a fast terminal sliding mode observer is developed to estimate the velocity of AUV in finite time. With the estimated velocity information, an adaptive-nonsingular fast terminal sliding mode tracking controller is designed to drive AUV to the target point in finite time. For the proposed velocity observer and tracking controller, the signum and differential functions are employed together to improve the convergence speed and reduce the chattering. Besides that, the proposed solution can not only guarantee finite-time velocity observation, but also achieve finite-time tracking control. Finally, simulation and experimental results are both presented to verify the effectiveness. [ABSTRACT FROM AUTHOR]

Single-cut techniques allow for fast antenna characterization by measuring and transforming to far-field individual pattern cuts instead of the full sphere. The cut fields are expanded in a reduced set of cylindrical coefficients, which can be used to accurately compute the far-field in the main pattern cuts for antennas with separable aperture distributions. This communication introduces a fast single-cut near-field to far-field transformation method using amplitude-only data. The technique is based on the measurement of the near-field magnitude in two concentric cuts and starts an iterative propagation process to retrieve their phases. This technique becomes a fast tool for antenna characterization when one is interested in a few cardinal plane cuts of the antenna and only magnitude measurements are available. The proposed single-cut phaseless technique is tested using simulated and measured data, and it shows its potential for fast and more reliable amplitude-only measurements. [ABSTRACT FROM AUTHOR]

Row–column (RC) arrays have the potential to yield full 3-D ultrasound imaging with a greatly reduced number of elements compared to fully populated arrays. They, however, have several challenges due to their special geometry. This review article summarizes the current literature for RC imaging and demonstrates that full anatomic and functional imaging can attain a high quality using synthetic aperture (SA) sequences and modified delay-and-sum beamforming. Resolution can approach the diffraction limit with an isotropic resolution of half a wavelength with low sidelobe levels, and the field of view can be expanded by using convex or lensed RC probes. GPU beamforming allows for three orthogonal planes to be beamformed at 30 Hz, providing near real-time imaging ideal for positioning the probe and improving the operator’s workflow. Functional imaging is also attainable using transverse oscillation and dedicated SA sequence for tensor velocity imaging for revealing the full 3-D velocity vector as a function of spatial position and time for both blood velocity and tissue motion estimation. Using RC arrays with commercial contrast agents can reveal super-resolution imaging (SRI) with isotropic resolution below $20~ \mu \text{m}$. RC arrays can, thus, yield full 3-D imaging at high resolution, contrast, and volumetric rates for both anatomic and functional imaging with the same number of receive channels as current commercial 1-D arrays. [ABSTRACT FROM AUTHOR]

In this study, a finite-time velocity-free rendezvous control method is considered for multiple autonomous underwater vehicle (AUV) systems with intermittent undirected communication. First, we develop a distributed finite-time observer for each AUV to estimate its own state information. Second, we design a rendezvous control algorithm that utilizes the estimated state information intermittently through a communication network in the absence of velocity measurement. A homogeneous method is used to prove that all AUVs in the group can achieve rendezvous in finite time for a network with intermittent communication, even without velocity measurements. The proposed method is shown to reduce the communication load of the system. More importantly, the control algorithm achieves the control goal of the system and is proven to be viable for many practical applications of multiple AUV systems from both economic and security perspectives. Finally, the effectiveness of the proposed control protocol is demonstrated via numerical simulations. [ABSTRACT FROM AUTHOR]

Expressions for particle image velocimetry (PIV) mean error and error variance are derived for iterative deformation method algorithms. The analytical expressions explicitly account for the role of in- and out-of-plane displacements, displacement gradients, particle image diameter, fill factor of the imaging sensor, image noise, light sheet intensity distribution, seeding particle concentration, the interpolation function used to deform PIV images, and the interrogation window size and weighting window. The newly derived analytical expressions show good agreement with errors estimated using synthetic image sets. [ABSTRACT FROM AUTHOR]

When ice forms on lakes, dissolved salts are rejected, which can lead to under‐ice salt finger formation. We performed a series of laboratory experiments to visualize these fingers. While we detected salt fingers in our camera recordings, the signal of these fingers is nearly absent in the temperature record. We quantify the velocity of the salt‐plumes and measure the bottom salinity increase from these fingers. Further, we estimate that the salinity is often distributed evenly with depth. Comparing the salt fluxes in our experiments with a typical salt flux in lakes, we suggest that conditions are favorable for salt fingering in most seasonally ice‐covered lakes. Plain Language Summary: When ice forms on the surface of lakes, dissolved salts are expelled from the ice into the liquid water below. If enough salt is rejected from the ice, the excess weight of the salt can lead to long "fingers" of salty fluid moving from the ice into the water below. We ran a series of experiments to investigate these "fingers", and conclude that this process likely occurs in most freshwater lakes that freeze annually. This process is important for the evolution of lakes and will change as fewer lakes freeze. Key Points: Cryoconcentration produces gradients in solutes under the ice in freshwater lakesLaboratory experiments indicate that salt fingers, enabled by contrasting gradients in solutes and temperature, may be common in ice‐covered lakesSalt fingers may not obviously perturb the temperature stratification [ABSTRACT FROM AUTHOR]

The exit velocity of the armature is an important indicator in measuring the launching performance of the electromagnetic gun. The non-contact photoelectric detection technology with the use of a laser screen was applied to the measurement of the armature velocity of the electromagnetic gun. By means of taking the signals that pass through the laser screen obtained by the velocity measurement system as the research object, we solved problems such as the harsh test environment of the launch armature velocity of the electromagnetic gun, the interferences on the armature signal passing through the laser screen unavoidably caused by various factors such as vibration, electromagnetic interference, shock wave, flare, smoke and fragments, and even the non-recognition of the signal passing through the laser screen in severe cases. A data-processing algorithm that combines the Ensemble Empirical Mode Decomposition (EEMD) with Correlation Algorithm (CA) was proposed, with the aim of processing the signals passing through the laser screen, while using the maximum slope point as the time passing through the laser screen so as to calculate the velocity of the armature passing the laser screen. This method can effectively reduce the influence of interference on the test results, and the test results from two sets of velocity measuring systems show that the velocity obtained by the proposed approach is highly consistent. [ABSTRACT FROM AUTHOR]

Determining brain hemodynamics plays a critical role in the diagnosis and treatment of various cerebrovascular diseases. In this work, we put forth a physics-informed deep learning framework that augments sparse clinical measurements with one-dimensional (1D) reduced-order model (ROM) simulations to generate physically consistent brain hemodynamic parameters with high spatiotemporal resolution. Transcranial Doppler (TCD) ultrasound is one of the most common techniques in the current clinical workflow that enables noninvasive and instantaneous evaluation of blood flow velocity within the cerebral arteries. However, it is spatially limited to only a handful of locations across the cerebrovasculature due to the constrained accessibility through the skull’s acoustic windows. Our deep learning framework uses in vivo real-time TCD velocity measurements at several locations in the brain combined with baseline vessel cross-sectional areas acquired from 3D angiography images and provides high-resolution maps of velocity, area, and pressure in the entire brain vasculature. We validate the predictions of our model against in vivo velocity measurements obtained via four-dimensional (4D) flow magnetic resonance imaging (MRI) scans. We then showcase the clinical significance of this technique in diagnosing cerebral vasospasm (CVS) by successfully predicting the changes in vasospastic local vessel diameters based on corresponding sparse velocity measurements. We show this capability by generating synthetic blood flow data after cerebral vasospasm at various levels of stenosis. Here, we demonstrate that the physics-based deep learning approach can estimate and quantify the subject-specific cerebral hemodynamic variables with high accuracy despite lacking knowledge of inlet and outlet boundary conditions, which is a significant limitation for the accuracy of the conventional purely physics-based computational models. [ABSTRACT FROM AUTHOR]

Transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) enables the noninvasive treatment of the deep brain. This capacity relies on the ability to focus acoustic energy through the in-tact skull, a feat that requires accurate estimates of the acoustic velocity in individual patient skulls. In current practice, these estimates are generated using a pretreatment computed tomography (CT) scan and then registered to a magnetic resonance (MR) dataset on the day of the treatment. Treatment safety and efficacy can be improved by eliminating the need to register the CT data to the MR images and by improving the accuracy of acoustic velocity measurements. In this study, we examine the capacity of MR to supplement or replace CT as a means of estimating velocity in the skull. We find that MR can predict velocity with less but comparable accuracy to CT. We then use micro-CT imaging to better understand the limitations of Hounsfield unit (HU)-based estimates of velocity, demonstrating that the macrostructure of pores in the skull contributes to the acoustic velocity of the bone. We find evidence that detailed T2 measurements provide information about pore macrostructure similar to the information obtained with micro-CT, offering a potential clinical mechanism for improving patient-specific estimates of acoustic velocity in the human skull. [ABSTRACT FROM AUTHOR]

This article presents an input-and-measurement event-triggered output-feedback chattering reduction control for microelectromechanical system (MEMS) gyroscopes. To realize online estimation with decreased communication burden along sensor-to-control channel, a switching threshold-based sampler is embedded to achieve an intermittent measurement-based extended state observer (IMESO) capable of synchronously observing unavailable velocity states and disturbances, meanwhile, a mathematical presentation reflecting the interaction between design parameters and upper boundary of estimation errors is deduced to make argument tuning easy. Next, an event-triggered output-feedback control rule is developed in the controller-to-actuator channel to obtain a discrete control signal with less occupation on communication resources without inducing Zeno phenomena. Besides, to enforce system profiles evolve within the predefined performance boundaries with reduced chattering, a tracking differentiator (TD)-based prescribed performance control (TDPPC) is proposed, where the time differentiation of the preselected envelopes can be managed with smooth transient, and a balance between system performance and sampling cost can be ensured. Finally, a sigmoid function-based TD (STD), rather than dynamic surface control, is utilized to overcome the complexity explosion. Comparison simulations are performed to show the superiorities and effectiveness of the established controller. [ABSTRACT FROM AUTHOR]

The velocity of ultrasound longitudinal waves (speed of sound) is emerging as a valuable biomarker for a wide range of diseases, including musculoskeletal disorders. Muscles are fiber-rich tissues that exhibit anisotropic behavior, meaning that velocities vary with the wave-propagation direction. Therefore, quantifying anisotropy is essential to improve velocity estimates while providing a new metric related to muscle composition and architecture. For the first time, this work presents a method to estimate speed-of-sound anisotropy in transversely isotropic tissues using pulse-echo ultrasound. We assume elliptical anisotropy and consider an experimental setup with a flat reflector parallel to the linear probe, with the muscle in between. This setup allows us to measure first-arrival reflection traveltimes using multistatic operation. Unknown muscle parameters are the orientation angle of the anisotropy symmetry axis and the velocities along and across this axis. We derive analytical expressions for the nonlinear relationship between traveltimes and anisotropy parameters, including reflector inclinations. These equations are exact for homogeneous media and are useful to estimate the effective average anisotropy in muscles. To analyze the structure of this forward problem, we formulate the inversion statistically using the Bayesian framework. We demonstrate that anisotropy parameters can be uniquely constrained by combining traveltimes from different reflector inclinations. Numerical results from wide-ranging acquisition and anisotropy properties show that uncertainties in velocity estimates are substantially lower than expected velocity differences in the muscle. Thus, our approach could provide meaningful muscle anisotropy estimates in future clinical applications. [ABSTRACT FROM AUTHOR]

The experimental evidence of the decreased heterodyne-detection efficiency caused by the lag angle is shown using a long-range wind sensing coherent Doppler lidar (CDL) with fast beam scanning. The recovery of the efficiency with the lag-angle compensation is also demonstrated. The receiving beam alignment method synchronized with the beam scanner is used. The measurable range of 12 km with the fast beam scanning of 20°/s in the case of 8-Hz line-of-sight (LOS) update rate was demonstrated with the compensation. This demonstration shows the potential for the wind sensing CDL to satisfy all requirements of long-range, real-time, and fast beam scanning measurement. [ABSTRACT FROM AUTHOR]

This article presents a new method to retrieve dynamic information from spaceborne Doppler radar observations. The method is based on a complex convolution Doppler resampling (CConDoR) formulation, which links the spaceborne pulse-pair (PP) correlation measurements to high-resolution PP products that are not affected by the spacecraft motion. The CConDoR formalism allows to easily simulate Doppler products via convolution products. The CConDoR representation enables also retrievals by deconvolution. This approach is illustrated using a Wiener deconvolution algorithm. Results are shown for simulations of the radar of the Earth Cloud Aerosol Radiation Explorer (EarthCARE; developed by the European and Japanese space agencies). The proposed corrections improve the accuracy of the measured mean velocities (by correcting for nonuniform beam-filling (NUBF) biases) and spectral widths (by correcting for the spectral broadening), which to the best of the authors’ knowledge is novel. [ABSTRACT FROM AUTHOR]

• Emission angles of sources affect the accuracy of solid velocity measurement. • Deviation of incidence from critical angles reduces wave amplitude and frequency. • Adjusting offsets or incidence help P wave velocity extraction of slow solids. • Using S-wave first jump can avoid the interference of the leaky Rayleigh wave. Numerical analyses are performed to investigate ultrasonic wave propagation in fluid–solid half-spaces subject to a directional source. This research is particularly concerned with the behavior of refracted waves within fluid mediums and their utility in determining the acoustic velocities of solid materials. The simulations encompass solids with various mechanical parameters and highlight the influence of incident angles on wave propagation. The analysis reveals that as the disparity between incident and critical angles increases, both the dominant frequencies and amplitudes of the corresponding refracted waves decrease substantially, which is detrimental to the accurate extraction of solid velocities. For the low-velocity solid characterized by its shear wave velocity being less than the fluid's acoustic velocity, refracted longitudinal waves are susceptible to interference from direct and reflected waves. This interference often results in underestimated velocity measurements. The challenge can be addressed by either extending the source-receiver offset or by adjusting the incident angle closer to the critical angle. Regarding solids with shear wave velocities exceeding the fluid's acoustic velocity, although the velocity–time correlation (VTC) method can accurately determine longitudinal wave velocities, shear wave velocity extraction may be compromised by the presence of the leaky Rayleigh wave. We further compare velocities calculated by dividing the spacing distance of two receivers by the time difference of their respective wave packet arrivals. Results indicate that the initial trough and peak of the S wave packet are predominantly influenced by refracted shear waves and the leaky Rayleigh wave, respectively. This occurs because refracted shear waves propagate slightly faster than the leaky Rayleigh wave. Consequently, using the first trough of the shear wave packet as the wave onset can mitigate the impact of the leaky Rayleigh wave, yielding precise shear wave velocity measurements. These studies are of considerable importance for applications in geophysical downhole measurements and nondestructive testing. [ABSTRACT FROM AUTHOR]

• Turbulence evolution regularly exaggerates the flue gas flow velocity. • Optimal monitoring height exceeds 6 times the equivalent diameter. • Established load, temperature and ideal chord angle influence laws systematically. • A stepped number of deployment points based on the log-linear method is optimal. • The correlation between estimation error and monitoring height is established. CO 2 online monitoring provides a method to obtain carbon emissions by directly quantifying the flue gas flow rate and CO 2 concentration. However, significant flow rate measurement errors arise due to the complexity of turbulence in large-diameter stacks. To address the issue, this study utilizes turbulence numerical simulation combined with mean velocity estimation error analysis to investigate the flow field of typical stacks in coal-fired power plants. The simulation results demonstrated that the evolution of turbulence exaggerates velocities. The flow field exhibits stable turbulence characteristics in a single-introduced stack, while in the double-introduced stack, the flow field dynamically evolves due to asymmetric collisions and abrupt expansions. Furthermore, the effects of load and temperature on the estimation error of flow velocity are established. The optimum monitoring height, the ideal chord angle and the stepped number of deployment points based on the log-linear method are determined. Within the single-introduced stack, a correction factor is introduced and a corresponding formula is established that links estimation errors with monitoring heights. This resulted in a dramatic reduction of the maximum estimation error from 14% to 0.3%. Finally, the systematic and simplified optimization scheme for estimating mean flow velocity is summarised, which provides a powerful reference for flow rate measurement for online CO 2 monitoring in coal-fired power plants. [ABSTRACT FROM AUTHOR]

Following an unforeseen disturbance in a power system, the system state should be known to extract the emergency voltage restoration strategy. Such a condition does not usually hold in distribution systems due to the lack of enough measurements. Here, the joint probability density function (pdf) of uncertain parameters is extracted from historical data. This pdf is updated to comply with the measurements. A set of samples is then generated that best models the updated pdf. These data reconciliation and sampling techniques enable the functioning of the emergency voltage control (evc) with measurement scarcity. They are designed to be fast enough to meet the quasi-real-time requirements of the intended application. The evc problem is cast as a stochastic programming problem. The resultant problem is a mixed-integer non-convex (and hence, NP-hard) optimization problem. It is solved using five distinct sms based on relaxation/approximation of the non-convex constraints. The results show that a novel combination of relaxation and approximation aimed at respectively mitigating the emergency under- and over-voltages outperforms the others. The propounded stochastic evc is validated through numerical studies. [ABSTRACT FROM AUTHOR]

We present a model to estimate the bias error of 4D flow magnetic resonance imaging (MRI) velocity measurements. The local instantaneous bias error is defined as the difference between the expectation of the voxel’s measured velocity and actual velocity at the voxel center. The model accounts for bias error introduced by the intra-voxel velocity distribution and partial volume (PV) effects. We assess the intra-voxel velocity distribution using a 3D Taylor Series expansion. PV effects and numerical errors are considered using a Richardson extrapolation. The model is applied to synthetic Womersley flow and in vitro and in vivo 4D flow MRI measurements in a cerebral aneurysm. The bias error model is valid for measurements with at least 3.75 voxels across the vessel diameter and signal-to-noise ratio greater than 5. All test cases exceeded this diameter to voxel size ratio with diameters, isotropic voxel sizes, and velocity ranging from 3-15mm, 0.5-1mm, and 0-60cm/s, respectively. The model accurately estimates the bias error in voxels not affected by PV effects. In PV voxels, the bias error is an order of magnitude higher, and the accuracy of the bias error estimation in PV voxels ranges from 67.3% to 108% relative to the actual bias error. The bias error estimated for in vivo measurements increased two-fold at systole compared to diastole in partial volume and non-partial volume voxels, suggesting the bias error varies over the cardiac cycle. This bias error model quantifies 4D flow MRI measurement accuracy and can help plan 4D flow MRI scans. [ABSTRACT FROM AUTHOR]

This article describes a novel technique to estimate static Young’s modulus of stress-sensitive rocks using dynamic linear and nonlinear constants estimated from borehole sonic data. Two linear and three nonlinear constants are estimated from the transit time of compressional headwaves and inversion of borehole-guided Stoneley and crossdipole dispersions in tectonically stressed formations. A major advantage of this technique is that the rock static Young’s modulus is determined from the dynamic elastic constants measured at a chosen reference state that is rather close to the in situ conditions. These dynamic elastic constants are used in the nonlinear constitutive relations for poroelastic rocks subject to finite deformations. These relations express the second Piola–Kirchhoff axial stresses in terms of elastic constants together with up to quadratic terms in Lagrangian axial strains. Strain derivatives of the second Piola–Kirchhoff stress yield the static Young’s modulus as a function of incremental axial strains from a chosen reference state. Consequently, static Young’s modulus can also be determined at other depths with different overburden stresses and associated incremental axial strains from a chosen reference state. In contrast, strain derivative of the second Piola–Kirchhoff axial stress expressed in terms of linear elastic constants and only linear terms in axial strain provides the dynamic Young’s modulus. Two useful outputs from this workflow are the static stress–strain deformation curves for a core plug and static Young’s modulus under in situ conditions as a function of logging depth. The proposed technique has been validated with the available experimental stress–strain data from Castlegate and Berea sandstones core plugs. Results have been obtained for the static Young’s modulus and finite deformation stress–strain curves for two different stress-sensitive poroelastic formations using borehole sonic data. [ABSTRACT FROM AUTHOR]

In this article, an $SE(3)$ -constrained extended Kalman filter is proposed in continuous time as well as in a more practical continuous-discrete framework. The filter allows for the state estimation of the 6-DOF rigid body motion while accounting for measurement error statistics and using the rotation matrix instead of quaternions or other attitude parameterizations. The proposed filter differs from the recently proposed $SO(3)$ -constrained attitude filter in that only a subset of the configuration states are constrained in the present filter. Its effectiveness is demonstrated in a numerical example in which its performance is compared with that of an existing $SE(3)$ estimator from the literature and a Monte Carlo simulation is carried out to provide credence to the accuracy of the proposed filter. [ABSTRACT FROM AUTHOR]

In this article, we study the cooperative formation tracking problem of clustered quadrotors without velocity and angular velocity measurements. In particular, the clustered quadrotors are required to track a reference trajectory while preserving a well-defined formation shape. However, the information interaction among the quadrotors is local and the reference trajectory information is only known to partial quadrotors. To overcome the aforementioned dilemmas caused by measurement incompleteness and interaction restriction, a distributed output-feedback control algorithm is proposed based on the cascaded framework. To be specific, by introducing two auxiliary dynamics with saturation constraints on their states, a distributed command force with a saturation attribute is first developed in the outer position loop. Next, in terms of a self-contained selection criterion of the control parameters, a bounded applied thrust and a nonsingular command attitude are extracted from the developed command force. Whereafter, an applied torque resorting to another auxiliary dynamics is developed in the inner attitude loop for the purpose of tracking the command attitude. It is shown that, despite the absence of the velocity and angular velocity information of clustered quadrotors, the concerned cooperative formation tracking objective is fulfilled by the proposed distributed control algorithm. Finally, simulations are performed to validate the built theoretical results. [ABSTRACT FROM AUTHOR]

With higher demand for sensor development, piezoelectric materials with advanced performance and wide availability draw more attention today. Accurate second-order material constants are necessary for modeling and mechanical design of sensors that make use of langanite (La3Ga5.5Nb0.5O14, LGN) crystals. We report here on room temperature LGN bulk acoustic wave (BAW) velocities obtained with reduced uncertainties using ultrasound measurements and taking advantage of the cross correlation signal processing technique, and a full set of LGN material constants extracted from the BAW velocity results. Our results compare favorably with prior results assessed as using a reliable measurement technique, and differ in expected fashion from other results based on techniques that do not address a known weakness in the measurement technique. [ABSTRACT FROM AUTHOR]

The spatial disturbance, which depends on position rather than time, is widespread in rotary machines. In this article, an improved control method named accurate cycle aligned repetitive control (ACARC) is proposed to deal with its suppression. In the ACARC, the data-storage technique is used to realize the spatial internal model and a design requirement is presented for the rejection of spatial disturbance with a better response. Further, the cycle offset, caused by the auxiliary stabilizing compensator, is significantly reduced by the combination of a spatial low-pass compensator and a time-advance element. Moreover, a cascaded structure of ACARCs is presented together with a detailed design procedure for disturbance with multiple components occurring in actual rotary systems. The effectiveness and superiority of the proposed control method are verified and compared with other methods by the simulations and experiments. [ABSTRACT FROM AUTHOR]

In this article, an in-motion coarse alignment method in the polar region is proposed. Different from the traditional coarse alignment method, the vector observation is constructed with the grid frame. Thus, the calculated singularity in the polar region, which is easy to see in the navigational frame, is suppressed. Considering the GPS measurements, the velocity errors are assumed in the GPS measurements. Since the characteristics of the observation vectors, the initial velocity error always exists during the whole alignment process. To address the initial velocity error, a simple method with the vector subtraction operation is used to construct the new observation vector. In the new observation vector, the initial velocity is eliminated. Thus, the initial velocity error is suppressed. To verify the performance of the proposed method, a virtual polar region method is proposed to transform the experimental data of the field tests in the low and middle latitude region. The simulation and field tests are shown that the proposed method can get more accurate alignment results than the traditional methods. [ABSTRACT FROM AUTHOR]

We revisit the outlier hypothesis testing framework of Li et al. (TIT 2014) and derive fundamental limits for the optimal test under the generalized Neyman-Pearson criterion. In outlier hypothesis testing, one is given multiple observed sequences, where most sequences are generated i.i.d. from a nominal distribution. The task is to discern the set of outlying sequences that are generated from anomalous distributions. The nominal and anomalous distributions are unknown. We study the tradeoff among the probabilities of misclassification error, false alarm and false reject for tests that satisfy weak conditions on the rate of decrease of these error probabilities as a function of sequence length. Specifically, we propose a threshold-based test that ensures exponential decay of misclassification error and false alarm probabilities. We study two constraints on the false reject probability, with one constraint being that it is a non-vanishing constant and the other being that it has an exponential decay rate. For both cases, we characterize bounds on the false reject probability, as a function of the threshold, for each pair of nominal and anomalous distributions and demonstrate the optimality of our test under the generalized Neyman-Pearson criterion. We first consider the case of at most one outlying sequence and then generalize our results to the case of multiple outlying sequences where the number of outlying sequences is unknown and each outlying sequence can follow a different anomalous distribution. [ABSTRACT FROM AUTHOR]

In order to solve the collaborative navigation problems in challenging environments such as insufficient visible satellites, obstacle reflections and multipath errors, and in order to improve the accuracy, usability, and stability of collaborative navigation and positioning, we propose a dual-way asynchronous precision communication–timing–measurement system (DWAPC-TSM) LEO constellation multi-aircraft cooperative navigation and positioning algorithm which gives the principle, algorithm structure, and error analysis of the DWAPC-TSM system. In addition, we also analyze the effect of vehicle separation range on satellite observability. The DWAPC-TSM system can achieve high-precision ranging and time synchronization accuracy. With the help of this system, by adding relative ranging and speed measurement observations in an unscented Kalman filter (UKF), the multi-aircraft coordinated navigation and positioning of aircraft is finally realized. The simulation results show that, even without the aid of an altimeter, the multi-aircraft cooperative navigation and positioning algorithm based on the DWAPC-TSM system can achieve good navigation and positioning results, and with the aid of the altimeter, the cooperative navigation and positioning accuracy can be effectively improved. For the formation flight configurations of horizontal collinear and vertical collinear, the algorithm is universal, and in the case of vertical collinear, the navigation performance of the formation members tends to be consistent. Under different relative measurement accuracy, the algorithm can maintain good robustness; compared with some existing classical algorithms, it can significantly improve the navigation and positioning accuracy. A reference scheme for exploring the feasibility of a new cooperative navigation and positioning mode for LEO communication satellites is presented. [ABSTRACT FROM AUTHOR]

In this work, an adaptive generalized cross-correlation (AGCC) method is proposed that focuses on the problem of the conventional cross-correlation method not effectively realizing the time delay estimation of signals with strong periodicity. With the proposed method, the periodicity of signals is judged and the center frequencies of the strongly periodical components are determined through the spectral analysis of the input signals. Band-stop filters that are used to suppress the strongly periodical components are designed and the mutual power spectral density of the input signals that is processed by the band-stop filters is calculated. Then, the cross-correlation function that is processed is the inverse Fourier transform of the mutual power spectral density. Finally, the time delay is estimated by seeking the peak position of the processed cross-correlation function. Simulation experiments and practical velocity measurement experiments were carried out to verify the effectiveness of the proposed AGCC method. The experimental results showed that the new AGCC method could effectively realize the time delay estimation of signals with strong periodicity. In the simulation experiments, the new method could realize the effective time delay estimation of signals with strong periodicity when the energy ratio of the strongly periodical component to the aperiodic component was under 150. Meanwhile, the cross-correlation method and other generalized cross-correlation methods fail in time delay estimation when the energy ratio is higher than 30. In the practical experiments, the velocity measurement of slug flow with strong periodicity was implemented in small channels with inner diameters of 2.0 mm, 2.5 mm and 3.0 mm. With the proposed method, the relative errors of the velocity measurement were less than 4.50%. [ABSTRACT FROM AUTHOR]

The uniform and linear wind models have been commonly used for wind field retrieval in meteorological community. However, the accuracy and robustness of the retrieval results can be quite unsatisfactory due to the mismatch between these models and the real wind distribution, especially under complex wind conditions. In this article, a nonlinear model based on high-order Taylor expansion is proposed to deal with this limitation, and the combination of ridge regression and decomposition-iteration process (denoted as Ridge-DI method) is further introduced to solve the model with high accuracy and robustness. A case study on simulation and field experiment shows that the proposed method with the third-order Taylor expansion can reduce the mean root-mean-square errors (RMSEs) of the retrieved velocities by more than 16.84% in comparison with traditional methods. [ABSTRACT FROM AUTHOR]

Differential synthetic aperture radar interferometry (DInSAR) allows for retrieval of ice velocity measurements of high resolution and accuracy. One of the main error sources in DInSAR is the phase unwrapping procedure. Unwrapping errors may be caused by several processes, including shear stresses associated with large motion gradients, which lead to loss of interferometric coherence. In many cases, unwrapping errors reach magnitudes corresponding to velocities of tens or even hundreds of meters per year. Traditional DInSAR implementations include pixel masking based on coherence thresholding; however, such a masking is not always sufficient. Consequently, the state-of-the-art for ice velocity retrievals involves either manual inspection of individual measurements or simply discarding measurements in regions where ice flow exceeds a predefined threshold. Here, we instead apply a masking based on thresholding of a pixel connectivity estimate with respect to a reference point, which aims to detect unwrapping errors based only on the estimated coherence pattern. The method is tested on both simulated and real data Sentinel-1 data from the Greenland Ice Sheet and effectively detects the majority of unwrapping errors (recall of 0.84 for the best performing threshold), although with a relatively low precision (0.52 for the best performing threshold). Importantly, higher magnitude unwrapping errors are associated with lower connectivity values, meaning that undetected errors have a significantly lower magnitude (median of 1.7 m/y, corresponding to a single phase cycle, compared with 40.5 m/y with no masking). [ABSTRACT FROM AUTHOR]

This article investigates the distributed average tracking (DAT) problem for disturbed second-order multiagent systems, where a crowd of agents is required to track the average of the multiple time-varying signals. First, a new kind of distributed average estimator is developed for each agent to estimate the average of the multiple time-varying signals in finite time. The protocol possesses the distinguished feature of robustness to initialization errors, which can recover from network alterations. Then, an observer-based finite-time tracking protocol is proposed to make each agent exactly track the average of the multiple time-varying signals in finite time in the absence of velocity measurement. By carefully analyzing the dynamic properties of the tracking error system, a suitable Lyapunov function is constructed to estimate the settling time for convergence of the tracking error system theoretically. Furthermore, an adaptive DAT protocol is proposed, which is a fully distributed protocol because it can solve the DAT problem without using any global information. Finally, two simulation examples are provided to verify the effectiveness of the methods. [ABSTRACT FROM AUTHOR]

In this article, a constrained image-based visual servoing control method for the shipboard landing problem of unmanned helicopters is proposed. First, the pitch and roll motion of ship are predicted by an autoregressive (AR) model to determine an appropriate period for landing. Subsequently, a novel robust sliding mode controller without linear velocity measurements is developed on the basis of the perspective image feature in a virtual image plane. Meanwhile, a modified Chebyshev neural network (CNN) is proposed to estimate the uncertainties, including the linear acceleration of ship and translational perturbation, while an adaptive law is employed to compensate the influence of rotational disturbances. The whole controller only requires the measurements feedback of a vision sensor and an inertial measurement unit (IMU). Ulteriorly, to prevent the visual target on the ship from going beyond the field of view of camera, the constrained controller is developed by a control barrier function and a quadratic programming, where the unknown relative velocity is estimated by a velocity observer. Finally, simulations are implemented to substantiate the capability of the presented shipboard landing control method. [ABSTRACT FROM AUTHOR]