Centroid Speed Research Articles

The centroid speed as a characteristic of the group speed of solar coronal fast magnetoacoustic wave trains

ABSTRACT The highly filamented nature of the coronal plasma significantly influences dynamic processes in the corona such as magnetohydrodynamic waves and oscillations. Fast magnetoacoustic waves, guided by coronal plasma non-uniformities, exhibit strong geometric dispersion, forming quasi-periodic fast-propagating (QFP) wave trains. QFP wave trains are observed in extreme-ultraviolet imaging data and indirectly in microwaves and low-frequency radio, aiding in understanding the magnetic connectivity, energy, and mass transport in the corona. However, measuring the field-aligned group speed of QFP wave trains, as a key parameter for seismological analysis, is challenging due to strong dispersion and associated rapid evolution of the wave train envelope. We demonstrate that the group speed of QFP wave trains formed in plane low-β coronal plasma non-uniformities can be assessed through the propagation of the wave train’s effective centre of mass, referred to as the wave train’s centroid speed. This centroid speed, as a potential observable, is shown empirically to correspond to the group speed of the most energetic Fourier harmonic in the wave train. The centroid speed is found to be almost insensitive to the waveguide density contrast with the ambient corona, and to vary with the steepness of the transverse density profile. The discrepancy between the centroid speed as the group speed measure and the phase speed at the corresponding wavelength is shown to reach 70 per cent, which is crucial for the energy flux estimation and interpretation of observations.

Exploratory Behavior and the Temporal Structure of Soccer Small-Sided Games to Evaluate Creativity in Children

ABSTRACT In this work, the position of the goals was modified to analyze the effects on the exploratory behavior and the team tactical pattern, which can be meaningful variables to study creativity in team sports. Twenty-four male soccer school players under the age of 12 participated in this study. Participants were divided into four teams of one goalkeeper and 5 players. Each team played six small-sided games of 5 min in three different goals positioning situations. The positioning-derived data of each player were collected using 10 Hz GPS units, were exported, and then computed using Matlab® dedicated routines. The positioning-derived variables were: team length and width, sector and corridor, centroid speed and its distance to the own goal, the centroid angle, and the speed of spread rate. They were analyzed by means of a PCA and the dynamic overlap order parameter. Results showed that changing the position of goals did not affect significantly the exploratory behavior. PCA analysis and Tucker’s Congruence Coefficient revealed that the task constraints could be characterized by a high mutual atypicality, and hence, originality. The use of the dynamic overlap, the PCA, hPCA, andTucker’s Congruence Coefficient to assess the degree of creativity in team sports were discussed. In conclusion, modifying the position of the goals can foster original behaviors of young athletes and increase the tactical repertoire of players.

Fall Detection Based on Dual-Channel Feature Integration

Falls have caught great harm to the elderly living alone at home. This paper presents a novel visual-based fall detection approach by Dual-Channel Feature Integration. The proposed approach divides the fall event into two parts: falling-state and fallen-state, which describes the fall events from dynamic and static perspectives. Firstly, the object detection model (Yolo) and the human posture detection model (OpenPose) are used for preprocessing to obtain key points and the position information of a human body. Then, a dual-channel sliding window model is designed to extract the dynamic features of the human body (centroid speed, upper limb velocity) and static features (human external ellipse). After that, MLP (Multilayer Perceptron) and Random Forest are applied to classify the dynamic and static feature data separately. Finally, the classification results are combined for fall detection. Experimental results show that the proposed approach achieves an accuracy of 97.33% and 96.91% when tested with UR Fall Detection Dataset and Le2i Fall Detection Dataset.

Automatic Detection of Crucial Areas Based on Speed Correlation in Video Sequences

Based on video frame differential optical flow field, a method of crucial area detection for surveillance video images of examination room is proposed in this paper. Firstly, the optical flow field was calculated with the difference between two adjacent frames. Secondly, the scene was divided roughly into several blocks, and the blocks of which centroid speed is higher than given threshold were further divided into fine sub-blocks, and furthermore, the sub-block which has maximum centroid speed in the block was marked as the area of abnormal target. Finally, the sub-blocks with exceptional speed in the same observation time slice were judged to be the correlate areas with abnormal speed (CAAS), and the intersection of adjacent CAAS were determined as the crucial area. Experimental results show that the proposed method can effectively detect the abnormal movement area, and can accurately position the crucial area affecting other targets movement.

“Blob” analysis of auroral substorm dynamics

One month's worth of Polar ultraviolet imager (UVI) data were subjected to a “blob” analysis to determine the statistical dynamics of substorm features observed in the Lyman‐Birge‐Hopfield long (LBHL) band (152–188 nm). Adapted from similar DoD analyses of target images, the analysis consists of finding, on a frame‐by‐frame basis beginning at substorm onset, the following aspects of an individual auroral feature: peak power (i.e., power of precipitating electrons), total power, centroid location (magnetic local time (MLT) and magnetic latitude (MLAT), and speed of centroid. Over 120 individual auroral features were successfully acquired at onset and tracked until dissipation during January 1997. The power in the peak pixel and total power were random in time but displayed transient spikes that lasted 5–10 min. Over the course of a substorm, the total energy of blobs averaged ∼2.0 − 104 GJ. A histogram of these energies suggests no preferred energy but that lower energies were more common than higher energies. Analysis of the blob positional dynamics generally supports a poleward and westward movement. During the course of a substorm, 90% of the blobs moved poleward, while over 60% moved westward. However, these movements were not steady and displayed random components. Furthermore, a sizable minority (∼35%) of the blobs moved eastward, which does not agree with the conventional picture of auroral surges. Blob speeds varied from essentially zero up to several kilometers per second. However, during the January substorms the blobs did appear to have a preferred speed of 0.84 ± 0.34 km s−1.