Rotational Invariance Research Articles

Compressive Behaviors of Steel Braces with Different Sectional Shapes

AbstractSteel braces are an essential structural element to resist lateral seismic forces and widely utilized in various types of buildings. The primary source of load carrying capacity in steel braced frames is through buckling and yielding of diagonal braces. Hysteretic behaviors of steel braces exhibit unsymmetric properties in tension and compression. Especially, they show significant strength degradation when loaded into the inelastic range in compression. Therefore, the governing failure modes of steel braces shall be global buckling in compression and this phenomenon shall occur prior to brittle limit states such as net section rupture or local buckling of elements. Except for effects of material properties, most of influential parameters is strongly related to the configuration and sectional shape of steel braces. Of them, the objective of this study is to investigate effects of sectional shapes on compressive behaviors of steel braces. Especially, this study focuses on the variation in the plastic hinge rotation and residual deformation of steel braces with representative sectional shapes which are typically applied on the construction field.

Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers

Passive image forgery detection methods that identify forgeries without prior knowledge have become a key research focus. In copy-move forgery, the assailant intends to hide a portion of an image by pasting other portions of the same image. The detection of such manipulations in images has great demand in legal evidence, forensic investigation, and many other fields. The paper aims to present copy-move forgery detection algorithms with the help of advanced feature descriptors, such as local ternary pattern, local phase quantization, local Gabor binary pattern histogram sequence, Weber local descriptor, and local monotonic pattern, and classifiers such as optimized support vector machine and optimized NBC. The proposed algorithms can classify an image efficiently as either copy-move forged or authenticated, even if the test image is subjected to attacks such as JPEG compression, scaling, rotation, and brightness variation. CoMoFoD, CASIA, and MICC datasets and a combination of CoMoFoD and CASIA datasets images are used to quantify the performance of the proposed algorithms. The proposed algorithms are more efficient than state-of-the-art algorithms even though the suspected image is post-processed.

A Two-Stage Data-Driven Method for Estimating the System Inertia Utilizing Event-Driven PMU Measurements

With the increasing penetration level of renewable energy resources with less system inertia, accurate estimation of the power system inertia has become a critical issue for maintaining the frequency stability of the entire power system. To tackle out this challenging task, a two-stage data-driven method is proposed in this paper for estimating the system inertia from disturbed PMU measurements. First, by integrating its low-order system frequency response model with the first-order turbine model, analytical expressions of the frequency response under the steady-state and these transient oscillatory components are derived. Then, based on this parametric model, a two-stage estimation algorithm will be developed. At the first stage, system parameters of oscillatory components can be extracted from PMU measurements by Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT). By utilizing frequency measurement data from PMUs and those estimated parameters from the ESPRIT algorithm, a weighted nonlinear least square approach is applied at the second stage to estimate physical parameters such as system inertia, damping coefficient, turbine time constant, and regulation coefficient. To validate the effectiveness of the proposed method, simulation studies of IEEE 39- bus system is investigated. Historical PMU measurements from various contingencies of Taiwan Power System will also be explored. All of these results demonstrated that the proposed method provides satisfactory performances with the mean relative error less than 10%. Comparisons with other existing methods are performed to demonstrate the advantage of the proposed method.

A strongly universal cellular automaton on the heptagrid with five states, but with not rotation invariance of the rules

ABSTRACT In this paper, we prove that there is a strongly universal cellular automaton on the heptagrid with five states under the relaxation of the assumption of rotation invariance for the rules. The result is different from that of a previous paper of the author with six states but with rotationally invariant rules. Here, the structures is more constrained than in the quoted paper with six states and rotation invariance of the rules.

Polarization Direction of Arrival Estimation Using Dual Algorithms Based on Time-Frequency Cross Terms

In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effective method to deal with nonstationary signals. In the last decade, spatial time-frequency distributions (STFDs) have been proposed for multiple dual-polarization antenna arrays and efficaciously used for nonstationary signal DOA estimation. In this article, we introduced a novelty means for estimating weak nonstationary polarization signal DOA by utilizing spatial polarimetric time-frequency distributions (SPTFDs) of cross terms when there are strong nonstationary polarization interference signals and additive Gaussian white noise. The cross terms’ SPTFDs are considered via a replaceability matrix for data covariance in multiple signal classification (MUSIC) and the estimation of signal parameters using the rotational invariance technique (ESPRIT). Combining the STFDs of cross terms with polarization information about weak nonstationary signals improves signal DOA estimation accuracy. The combined MUSIC and ESPRIT are used in the algorithm to further ensure the success probability and accuracy of DOA estimation. Through simulation analyses, the proposed algorithm is more suitable for the required application scenarios than other algorithms and is superior to other algorithms.

SKELTER: unsupervised skeleton action denoising and recognition using transformers

Unsupervised Human Action Recognition (U-HAR) methods currently leverage large-scale datasets of human poses to solve this challenging problem. As most of the approaches are dedicated to reaching the best recognition accuracies, no attention has been put into analyzing the resilience of such methods given perturbed data, a likely occurrence in real in-the-wild testing scenarios. Our first contribution is to systematically validate the decrease in performance of current U-HAR state-of-the-art using perturbed or altered data (e.g., obtained by removing some skeletal joints, rotating the entire pose, and injecting geometrical aberrations). Then, we propose a novel framework based on a transformer encoder–decoder with remarkable de-noising capabilities to counter such perturbations effectively. Moreover, we also present additional losses to have robust representations against rotation variances and provide temporal motion consistency. Our model, SKELTER, shows limited drops in performance when skeleton noise is present compared with previous approaches, favoring its use in challenging in-the-wild settings.

Two-stage PV grid-connected control strategy based on adaptive virtual inertia and damping control for DC-link capacitor dynamics self-synchronization

Conventional DC-link voltage-controlled voltage source converter (VQ-VSC) controls DC-link capacitor voltage and reactive power output by using phase locked loop (PLL) for synchronous grid connection of new energy sources such as PV. However, the deterioration of dynamic performance in PLL can lead to instability in VQ-VSC control within a weak grid. To improve the stability of VQ-VSC grid connection, the DC-link capacitor dynamic self-synchronous grid-connected control strategy without using PLL is proposed in this paper. The converter virtual rotational inertia variability and virtual inertia damping frequency characteristics are analyzed based on the synchronous generator rotor rotation characteristics. The proposed control strategy provides adaptive virtual inertia and damping coefficients for DC-link capacitor self-synchronous units to dynamically match the inertia and damping requirements during frequency synchronization, and enables VQ-VSC to operate in grid-forming mode without changing the grid synchronization unit. Compared with constant virtual inertia-damping control and adaptive virtual inertia-damping control based on change rate of frequency, the simulation results demonstrate the effectiveness of the proposed control strategy, which significantly improves the grid connection stability of PV systems in weak grids.

An Improved Two-Stage Spherical Harmonic ESPRIT-Type Algorithm

Sensor arrays are gradually becoming a current research hotspot due to their flexible beam control, high signal gain, robustness against extreme interference, and high spatial resolution. Among them, spherical microphone arrays with complex rotational symmetry can capture more sound field information than planar arrays and can convert the collected multiple speech signals into the spherical harmonic domain for processing through spherical modal decomposition. The subspace class direction of arrival (DOA) estimation algorithm is sensitive to noise and reverberation, and its performance can be improved by introducing relative sound pressure and frequency-smoothing techniques. The introduction of the relative sound pressure can increase the difference between the eigenvalues corresponding to the signal subspace and the noise subspace, which is helpful to estimate the number of active sound sources. The eigenbeam estimation of signal parameters via the rotational invariance technique (EB-ESPRIT) is a well-known subspace-based algorithm for a spherical microphone array. The EB-ESPRIT cannot estimate the DOA when the elevation angle approaches 90°. Huang et al. proposed a two-step ESPRIT (TS-ESPRIT) algorithm to solve this problem. The TS-ESPRIT algorithm estimates the elevation and azimuth angles of the signal independently, so there is a problem with DOA parameter pairing. In this paper, the DOA parameter pairing problem of the TS-ESPRIT algorithm is solved by introducing generalized eigenvalue decomposition without increasing the computation of the algorithm. At the same time, the estimation of the elevation angle is given by the arctan function, which increases the estimation accuracy of the elevation angle of the algorithm. The robustness of the algorithm in a noisy environment is also enhanced by introducing the relative sound pressure into the algorithm. Finally, the simulation and field-testing results show that the proposed method not only solves the problem of DOA parameter pairing, but also outperforms the traditional methods in DOA estimation accuracy.

Variability Catalog of Stars Observed during the TESS Prime Mission

During its 2 yr Prime Mission, TESS observed over 232,000 stars at a 2 minute cadence across ∼70% of the sky. These data provide a record of photometric variability across a range of astrophysically interesting timescales, probing stellar rotation, stellar binarity, and pulsations. We have analyzed the TESS 2 minute light curves to identify periodic variability on timescales of 0.01–13 days, and explored the results across various stellar properties. We have identified over 46,000 periodic variables with high confidence, and another 38,000 with moderate confidence. These light curves show differences in variability type across the Hertzsprung–Russell diagram, with distinct groupings of rotational, eclipsing, and pulsational variables. We also see interesting patterns across period–luminosity space, with clear correlations between period and luminosity for high-mass pulsators, evolved stars, and contact binary systems, a discontinuity corresponding to the Kraft break, and a lower occurrence of periodic variability in main-sequence stars on timescales of 1.5–2 days. The variable stars identified in this work are cross-identified with several other variability catalogs, from which we find good agreement between the measured periods of variability. There are ∼65,000 variable stars that are newly identified in this work, which includes the rotation rates of low-mass stars, high-frequency pulsation periods for high-mass stars, and a variety of giant star variability.

Fast and accurate computation of polar harmonic Fourier moments for image description.

Continuous orthogonal moments are widely used in various image techniques due to their simplicity and good rotational invariance and stability. In recent years, numerous excellent continuous orthogonal moments have been developed, among which polar harmonic Fourier moments (PHFMs) exhibit strong image description capabilities. However, the numerical integration error is large in the calculation, which seriously affects the calculation accuracy, especially in higher-order calculation. In this paper, a continuous orthogonal moments-fast and accurate PHFM (FAPHFM) is proposed. It utilizes the polar pixel tiling technique to reduce numerical errors in the computation; this method particularly improves the accuracy of higher-order moments of traditional PHFMs. However, as accuracy increases, calculation complexity also increases. To address this issue, an eight-way symmetric/anti-symmetric calculation of the angular and radial functions was performed using the symmetry and anti-symmetry of traditional PHFMs, and clustering of pixels was performed as a way to improve the computational speed. The experimental results show that FAPHFMs perform better in image reconstruction (including noise), with higher computational accuracy, lower time complexity, and better image description ability.

A Depression Recognition Method Based on the Alteration of Video Temporal Angle Features

In recent years, significant progress has been made in the auxiliary diagnosis system for depression. However, most of the research has focused on combining features from multiple modes to enhance classification accuracy. This approach results in increased space-time overhead and feature synchronization problems. To address this issue, this paper presents a single-modal framework for detecting depression based on changes in facial expressions. Firstly, we propose a robust method for extracting angle features from facial landmarks. Theoretical evidence is provided to demonstrate the translation and rotation invariance of these features. Additionally, we introduce a flip correction method to mitigate angle deviations caused by head flips. The proposed method not only preserves the spatial topological relationship of facial landmarks, but also maintains the temporal correlation between frames preceding and following the facial landmarks. Finally, the GhostNet network is employed for depression detection, and the effectiveness of various modal data is compared. In the depression binary classification task using the DAIC-WOZ dataset, our proposed framework significantly improves the classification performance, achieving an F1 value of 0.80 for depression detection. Experimental results demonstrate that our method outperforms other existing depression detection models based on a single modality.

Modeling of toroidal momentum transport induced by neoclassical toroidal viscosity torque for ITER scenarios

Neoclassical toroidal viscosity (NTV) torque caused by resonant magnetic perturbation (RMP) and the induced toroidal momentum transport are investigated for International Thermonuclear Experimental Reactor (ITER) scenarios through numerical modeling. The NTV torque is calculated using the NTVTOK code including the bounce-drift resonant effect, and the toroidal rotation evolution is modeled by solving a toroidal momentum transport equation that couples momentum source (NTV torque) and the momentum diffusion effect. The variation of RMP coil phasing (defined as toroidal phase difference between different rows of RMP coils) results in different types of plasma response and hence different features of NTV torque and toroidal momentum transport. The bounce-drift resonant effect enhances NTV torque and induces more significant toroidal rotation variation than simulations that adopt the bounce-averaged NTV model. With the initial rotation of the ITER design, plasma rotation is braked by NTV torque, but it may be sustained at moderate amplitude due to electron contributions to NTV torque. It is also found that initially static or slowly rotating plasma can be accelerated by NTV torque either toward co- Ip or counter- Ip ( Ip indicates plasma current) direction, indicating that NTV torque can be regarded as a momentum source for plasma with low torque injection; for instance, radio-frequency heated plasma.

Theoretical examination of QED Hamiltonian in relativistic molecular orbital theory.

Theoretical discussions are given on issues in relativistic molecular orbital theory to which the quantum electrodynamics (QED) Hamiltonian is applied. First, several QED Hamiltonians previously proposed are sifted by the orbital rotation invariance, the charge conjugation and time reversal invariance, and the nonrelativistic limit. The discussion on orbital rotation invariance shows that orbitals giving a stationary point of total energy should be adopted for QED Hamiltonians that are not orbital rotation invariant. A new total energy expression is then proposed, in which a counter term corresponding to the energy of the polarized vacuum is subtracted from the total energy. This expression prevents the possibility of total energy divergence due to electron correlations, stemming from the fact that the QED Hamiltonian does not conserve the number of particles. Finally, based on the Hamiltonian and energy expression, the Dirac-Hartree-Fock (DHF) and electron correlation methods are reintroduced. The QED-based DHF equation is shown to give information on positrons from negative-energy orbitals while having the same form as the conventional DHF equation. Three electron correlation methods are derived: the QED-based configuration interactions and single- and multireference perturbation methods. Numerical calculations show that the total energy of the QED Hamiltonian indeed diverged and that the counter term is effective in avoiding the divergence. The relativistic molecular orbital theory presented in this article also provides a methodology for dealing with systems containing positrons based on the QED Hamiltonian.

Triple-spherical Bessel function integrals with exponential and Gaussian damping: towards an analytic N-point correlation function covariance model

Spherical Bessel functions (sBFs) appear commonly in many areas of physics wherein there is both translation and rotation invariance, and often integrals over products of several arise. Thus, analytic evaluation of such integrals with different weighting functions (which appear as toy models of a given physical observable, such as the galaxy power spectrum) is useful. Here, we present a generalization of a recursion-based method for evaluating such integrals. It gives relatively simple closed-form results in terms of Legendre functions (for the exponentially damped case) and Gamma, incomplete Gamma, and hypergeometric functions (for the Gaussian-damped case). We also present a new, non-recursive method to evaluate integrals of products of sBFs with Gaussian damping in terms of incomplete Gamma functions and hypergeometric functions.

The Behavior of Bp He-weak Stars in the Far-UV—Paper XII: HD 175156

The analysis of four spectra of the B5 He-variable star HD 175156 recorded by the SWP camera on board the International Ultraviolet Explorer reveals one possible instance of variations of the far-ultraviolet spectral energy distribution shortwards of 1700 Å in spectra separated by 5 yr. Spectra collected over 4 consecutive days with identical exposure times do not vary, which probably rules out the possibility that HD 175156 be a rotational variable. The modeling of the Space Telescope Imaging Spectrograph spectrum reveals the presence of interesting resonance or low lying transitions of C i, N i, S i, P ii and several iron-peak elements, which provide interesting diagnostics of the atmosphere of this evolved sub-giant.

Real-time tool detection in smart manufacturing using You-Only-Look-Once (YOLO)v5

Computer vision plays an essential role in Industry 4.0 by enabling machinery to perceive, analyze, and control production processes. Object detection, a computer vision technique that accurately classifies and localizes objects within images, has gained significant interest. This technique can be applied in various domains, including manufacturing, to assist in the detection of different tools. In this paper, You-Only-Look-Once (YOLO)v5 real-time object detection technique has been developed and optimized, to detect different tool types and their locations in a manufacturing setting. To train the neural network, a dataset of 3,286 tool images from the internet has been collected and annotated. To enhance the model's ability in generalization, three augmented variants of each image have been created to improve rotation invariance. The model's training scheme has been further optimized with stochastic gradient descent after configuring different hyperparameters such as learning rate and momentum. The fine-tuned model achieved a mean average accuracy of 98.3 %, demonstrating the high precision of the model in detecting different tool types and their locations in real-time.

Assessment and Validation of Anterior Humeral Line for Diagnosing Supracondylar Humerus Fractures in the Pediatric Population.

Pediatric supracondylar humerus fractures are commonly evaluated using the anterior humeral line (AHL) on a lateral radiograph. Rotational variations in radiographic projection are common due to child discomfort and could lead to changes in management based on where the AHL intersects the capitellum. The purpose of this study was to establish whether rotational variations in elbow rotation leads to significant changes in AHL position and whether drawing the AHL based on the distal humerus versus shaft is more tolerant to rotation. Fifty children with nonoperative supracondylar humerus fractures were identified with sub optimally positioned injury and well positioned follow-up lateral radiographs. The proportion of the bone anterior to the intersection of the AHL and the capitellum was measured using the humeral shaft versus distal humerus to guide position of the AHL. This process was repeated on ten pediatric humerus dry cadaveric specimens which were imaged in 5-degree rotational increments along the axis of the humeral shaft from -20 to +20 degrees. AHL position correlated poorly when measured on rotated lateral radiographs of clinical patients versus non-rotated lateral radiographs when using the distal humerus as a guide (intraclass correlation coefficient 0.14), compared with when using the humeral shaft as a guide (intraclass correlation coefficient 0.81). When assessing the pediatric humerus dry cadavers between the 2 techniques, there was greater statistically significant variation in rotated positions compared with the neutral position in the distal humerus AHL measurement approach compared with the humeral shaft AHL measurement approach, with the mean AHL within the central third of the capitellum for more rotational positions when using the shaft compared with the distal humerus. With rotated lateral elbow radiographs in supracondylar humerus fractures, utilizing the humeral shaft provides more consistent AHL measurements than utilizing the distal humerus, and thus drawing the line starting at the shaft of the humerus is recommended for surgical decision making.

3D geometry‐based UAV to vehicle multiple‐input multiple‐output channel model incorporating Unmanned aerial vehicle heaving motion

AbstractUnmanned aerial vehicles (UAVs) play a vital role in the beyond fifth‐generation (B5G) and sixth‐generation (6G) wireless communication scenarios. This paper proposes a non‐stationary three‐dimensional (3D) geometry‐based multiple‐input multiple‐output channel model for UAV to vehicle (U2V) communications considering UAV heaving motion. The proposed model incorporates the effects of UAV heaving along with the rotation, acceleration, and 3D velocity variation for matching the realistic U2V communication scenarios. The computation methods for time variant channel parameters such as Doppler frequencies, angle of arrival, and angle of departure are given and analysed. The theoretical and statistical properties, including spatial temporal correlation function, TCF, level crossing rate, average fade duration, and Doppler power spectral density are derived and analysed aiming to evaluate the proposed model. Simulation results show that the output statistical characteristics agree with the hypothetical and simulated outcomes, which shows the validity of both the channel model and theoretical derivations.The cover image is based on the Research Article 3D geometry‐based UAV to vehicle multiple‐input multiple‐output channel model incorporating Unmanned aerial vehicle heaving motion by Naeem Ahmed et al., https://doi.org/10.1049/mia2.12393

EMaGer: A Wearable Full-Circumference HD-EMG Sensor and Data Augmentation Method for Robust Hand Gesture Recognition.

This work presents EMaGer, a new 360° 64-channel high-density electromyography (HD-EMG) bracelet combined with an original data augmentation method for improved robustness in gesture recognition. By leveraging homogeneous electrode density and powerful deep learning techniques, the sensor is capable of rotation invariance around the arm axis, thus increasing gesture recognition robustness to electrode movement and inter-session evaluation. The system is made of a 4x16 electrode array covering the full circumference of the limb, and uses a sampling frequency of 1 kHz and a 16-bit resolution. The sensor's uniform and adjustable geometry paired with an array barrel shifting data augmentation (ABSDA) technique allows a convolutional neural network to maintain a 76.98% inter-session classification accuracy for a 6 gestures dataset, from a baseline intra-session accuracy of 93.75%. High inter-session classification accuracy decreases the training burden for users of EMG control systems such as myoelectric prostheses by minimizing calibration requirements. The same methods applied with different state-of-the-art sensors are demonstrated to be less effective. Thus, this work evidences the importance of co-designing the EMG sensor system with the gesture inference algorithms to leverage synergistic properties and solve state-of-the-art challenges.Clinical relevance- This paper establishes a method that alleviates clinical manipulations in setting up and calibrating myoelectric prosthetic devices.

A cross-sectional methodological study: evaluation of the examiner performance on the Dix-Hallpike test

Purpose The Dix-Hallpike test is recommended to diagnose Benign Paroxysmal Positional Vertigo (BPPV). This research aimed to quantify the movement of a healthy subject during the Dix-Hallpike test and determine what factors contribute to performance variation from the recommended head position with 20° cervical extension, 45° cervical rotation, and a brisk movement velocity. Materials and methods Examiners performed the Dix-Hallpike test 10 times. The examinee’s movement was recorded with Qualisys and processed with Visual3D. The proportion of variation in test performance within examiners, between examiners, and due to examiner position was calculated. Results Thirteen participants, 54% male and mean age 40, performed 50 cranial and 77 lateral Dix-Hallpike tests. Head position differed significantly from the recommendations with the cranial tests for extension (mean difference [MD] = 11.6°, p < 0.001) and rotation (MD = 4.8°, p < 0.001) and with lateral tests for extension (MD = 13.3°, p < 0.001). The largest proportion of variation was between examiners (60–91%), followed by within-examiners (3–16%). The examiner position contributed to 20% of the variation in the cervical rotation achieved. Tests lasted, on average, 1.80 s. Conclusions Differences within and between examiners visually estimating the Dix-Hallpike test endpoints may impede BPPV diagnosis accuracy.