Correlation dimension and entropy in the assessment of sex differences based on human gait data.

Introduction: It is proved that there are differences between gait performed by females and males, which appear in movements of selected body parts. Despite numerous state-of-the-art studies related to the discriminative analysis of motion capture data, the question of whether measures of signal complexity and uncertainty can extract valuable features for the problem of sex distinction still remains open. It is the subject of the paper.

Explicit face memory abilities are positively related to the non-intentional encoding of faces: Behavioral and ERP evidence.

Individual differences in face memory abilities have been shown to be related to individual differences in brain activity. The present study investigated brain-behavior relationships for the N250 component in event-related brain potentials, which is taken as a neural sign of face familiarity. We used a task in which a designated, typical target face and several (high- and low-distinctive) nontarget faces had to be distinguished during multiple presentations across a session.

YOLOv5 Drone Detection Using Multimodal Data Registered by the Vicon System.

This work is focused on the preliminary stage of the 3D drone tracking challenge, namely the precise detection of drones on images obtained from a synchronized multi-camera system. The YOLOv5 deep network with different input resolutions is trained and tested on the basis of real, multimodal data containing synchronized video sequences and precise motion capture data as a ground truth reference. The bounding boxes are determined based on the 3D position and orientation of an asymmetric cross attached to the top of the tracked object with known translation to the object's center.

Datasets for learning of unknown characteristics of dynamical systems.

The ability to uncover characteristics based on empirical measurement is an important step in understanding the underlying system that gives rise to an observed time series. This is especially important for biological signals whose characteristic contributes to the underlying dynamics of the physiological processes. Therefore, by studying such signals, the physiological systems that generate them can be better understood.

Intelligent Sensors for Human Motion Analysis.

Currently, the analysis of human motion is one of the most interesting and active research topics in computer science, especially in computer vision [...

Assessment of Local Dynamic Stability in Gait Based on Univariate and Multivariate Time Series.

The ability of the locomotor system to maintain continuous walking despite very small external or internal disturbances is called local dynamic stability (LDS). The importance of the LDS requires constantly working on different aspects of its assessment method which is based on the short-term largest Lyapunov exponent (LLE). A state space structure is a vital aspect of the LDS assessment because the algorithm of the LLE computation for experimental data requires a reconstruction of a state space trajectory.

The expanded invasive weed optimization metaheuristic for solving continuous and discrete optimization problems.

This paper introduces an expanded version of the Invasive Weed Optimization algorithm (exIWO) distinguished by the hybrid strategy of the search space exploration proposed by the authors. The algorithm is evaluated by solving three well-known optimization problems: minimization of numerical functions, feature selection, and the Mona Lisa TSP Challenge as one of the instances of the traveling salesman problem. The achieved results are compared with analogous outcomes produced by other optimization methods reported in the literature.