Search Results (329)

Background/Objectives: The purpose of the study was to investigate the effects of a priming training session with either a light or heavy load snatch and clean pulls on weightlifting performance. Methods: Twelve well-trained weightlifters (seven males and five females) participated in the study. The athletes followed a counterbalanced study design comparing three treatments, including a day of rest (control) and two priming sessions involving two different weightlifting derivatives—the snatch and the clean pulls—which were performed either with 80% of the one-repetition maximum (1-RM) (LP) or with 110% of the 1-RM (HP). Twenty-four hours later, the 1-RM strength test for the snatch and clean and jerk, as well as the barbell kinematic characteristics at 100% of the 1-RM in the snatch and clean and jerk, were measured. The rate of perceived exertion (RPE) was measured following the priming sessions. Results: Performance in snatch remained unchanged following the LP and HP. However, performance in the clean and jerk increased significantly by 3.1% following the HP compared to the control. No significant differences were observed in barbell kinematics. The RPE was significantly higher for HP compared to LP. Conclusions: These results suggest that an HP performed 24 h prior to the 1-RM evaluation in weightlifting may have significantly increased performance in the clean and jerk. These changes may not be explained by barbell kinematics. Full article

Cybersickness remains a significant barrier to the widespread adoption of virtual reality (VR) technology. Traditional methods for predicting cybersickness rely on self-reported questionnaires or physiological signals from specialized sensors, which have their limitations. This study explores the potential of using real-time, easily acquired head-tracking data (HTD) from standard VR headsets as a scalable alternative for estimating cybersickness. Twelve participants engaged in a VR session using an Oculus Quest 2 headset while their HTD were recorded. Kinematic metrics such as linear and angular velocity, acceleration, and jerk were computed from the HTD, including positional and angular parameters. Participants’ cybersickness levels were assessed using the Virtual Reality Sickness Questionnaire. While exploratory data analysis revealed no significant direct correlation between individual kinematic variables and cybersickness scores, machine learning models were employed to identify predictive patterns. Subsequently, four regression models, including Random Forest, Gradient Boosting, K-Nearest Neighbors, and Support Vector Machines, were trained and evaluated using the computed kinematic features to predict the cybersickness score. Among these, the Gradient Boosting model demonstrated superior performance, accurately predicting cybersickness scores with normalized differences less than 3.08% on unseen data. This approach offers a scalable and practical solution for real-time cybersickness prediction in VR applications and compliments other techniques that rely on physiological sensors, hardware, or user profiles. Full article

By introducing fractional exponentiation into a three-dimensional chaotic system, a jerk system with only six terms is designed. It has the property of total amplitude control, where a single non-bifurcation parameter can directly rescale all system variables without affecting the dynamics. It also features two-dimensional offset boosting, where a single parameter can realize direct offset boosting while another provides interlocked cross-dimensional offset boosting. Furthermore, this jerk system has a parameter-dominated symmetric attractor, which means that symmetric attractors appear successively as the parameter changes from positive to negative. Circuit experiments confirm the feasibility of analog fractional exponentiation using the 444 circuit and the complete control, including amplitude control and offset boosting, of the resulting system. The proposed circuit may facilitate applications of chaotic signal generators where signal versatility is important and exemplifies the generative potential of analog fractional exponentiation. Full article

Purpose: This study examined the acute performance-enhancing effects and endocrinological responses of a supramaximal clean pull performed at 120% of clean and jerk, one repetition maximum, on clean performance. Methods: Eight (n = 8) ranked collegiate level weightlifters attended two days of testing in a randomised order. A control session was used to identify a baseline measure of kinetic and kinematic clean performance and endocrinological status following three cleans interspersed with one-minute recovery between repetitions. The experimental condition required participants to perform a single clean pull at 120% of clean and jerk, one repetition maximum, followed by three minutes recovery, prior to executing three cleans with one-minute recovery between repetitions. All cleans were performed on a dual force plate set up, synchronised with a 3D motion capture system to simultaneously record barbell and ground reaction force data. All endocrinological data were measured prior to the participant warming up and also following each testing protocol. Results: The results indicated that no significant differences were found between the control and PAP condition (p = 0.140–0.902); however, effect sizes from group analysis identified moderately negative to trivial effects across kinetic, kinematic and endocrinological variables (d = −0.30–0.14). Further analysis on an individual level demonstrated values, both negative and positive, ranging from extremely large (d = −4.10) to trivial (d = 0.04). Conclusions: The findings suggest a potentially negative affect of PAP on kinetic and kinematic measures of clean performance. However, individual responses varied, and thus some weightlifters may find this useful. Full article

To solve the nonlinear vibration problems of second- and third-order nonlinear oscillators, a modified harmonic balance method (HBM) is developed in this paper. In the linearized technique, we decompose the nonlinear terms of the governing equation on two sides via a constant weight factor; then, they are linearized with respect to a fundamental periodic function satisfying the specified initial conditions. The periodicity of nonlinear oscillation is reflected in the Mathieu-type ordinary differential equation (ODE) with periodic forcing terms appeared on the right-hand side. In each iteration of the linearized harmonic balance method (LHBM), we simply solve a small-size linear system to determine the Fourier coefficients and the vibration frequency. Because the algebraic manipulations required for the LHBM are quite saving, it converges fast with a few iterations. For the Duffing oscillator, a frequency–amplitude formula is derived in closed form, which improves the accuracy of frequency by about three orders compared to that obtained by the Hamiltonian-based frequency–amplitude formula. To reduce the computational cost of analytically solving the third-order nonlinear jerk equations, the LHBM invoking a linearization technique results in the Mathieu-type ODE again, of which the harmonic balance equations are easily deduced and solved. The LHBM can achieve quite accurate periodic solutions, whose accuracy is assessed by using the fourth-order Runge–Kutta numerical integration method. The optimal value of weight factor is chosen such that the absolute error of the periodic solution is minimized. Full article

TEB (timed elastic band) can efficiently generate optimal trajectories that match the motion characteristics of car-like robots. However, the quality of the generated trajectories is often unstable, and they sometimes violate boundary conditions. Therefore, this paper proposes a fuzzy logic control–TEB algorithm (FLC-TEB). This method adds smoothness and jerk objectives to make the trajectory generated by TEB smoother and the control more stable. Building on this, a fuzzy controller is proposed based on the kinematic constraints of car-like robots. It uses the narrowness and turning complexity of the trajectory as inputs to dynamically adjust the weights of TEB’s internal objectives to obtain stable and high-quality trajectories in different environments. The results of real car-like robot tests show that compared to the classical TEB, FLC-TEB increased the trajectory time by 16% but reduced the trajectory length by 16%. The trajectory smoothness was significantly improved, the change in the turning angle on the trajectory was reduced by 39%, the smoothness of the linear velocity increased by 71%, and the smoothness of the angular velocity increased by 38%, with no reverse movement occurring. This indicates that when planning trajectories for car-like mobile robots, while FLC-TEB slightly increases the total trajectory time, it provides more stable, smoother, and shorter trajectories compared to the classical TEB. Full article

The manipulator has been widely used in the wood processing industry; the main problem currently faced is optimizing the motion trajectory to enhance the processing efficiency and operational stability of the woodworking manipulator and worktable. A 5-7-5 piecewise polynomial interpolation method is proposed to construct the spatial trajectories of each joint. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to achieve a time–jerk multi-objective trajectory planning that can meet the dual requirements of minimal processing time and reduced motion impact. In order to address the limitations of the standard NSGA-II algorithm, which is prone to local optima and exhibits slow convergence, we propose a good point set method for multi-objective optimization population initialization and a linear ranking selection method to refine the parent selection process within the genetic algorithm. The improved NSGA-II algorithm markedly enhanced both the uniformity of the population distribution and convergence speed. In practical applications, selecting suitable weightings to construct a normalized weight function can identify the optimal solution from the Pareto frontier curve. A high-order continuous and smooth optimal trajectory without abrupt changes can be obtained. The simulation results demonstrated that the 5-7-5 piecewise polynomial interpolation curve effectively constructed a high-order smooth processing trajectory with continuous and smooth velocity, acceleration, and jerk, free from discontinuities. Moreover, the INSGA-II algorithm outperforms the original algorithm in terms of convergence and distribution, enabling the optimal time–jerk multi-objective trajectory planning that adheres to constraint conditions. Optimized by the improved NSGA-II algorithm, the optimal total running time is 4.5400 s, and the optimal jerk is 17.934 $\mathrm{m}\left(\mathrm{r}\mathrm{a}\mathrm{d}\right)/{\mathrm{s}}^3$. This provides a novel approach to solving the inefficiencies and operational instability prevalent in traditional woodworking equipment. Full article

Single lane changing is one of the typical scenarios in vehicle driving. Planning a suitable single lane changing trajectory and tracking that trajectory accurately is very important for intelligent vehicles. The contribution of this study is twofold: (i) to plan lane change trajectories that cater to different driving styles (including aspects such as safety, efficiency, comfort, and balanced performance) by a 7th-degree polynomial; and (ii) to track the predefined trajectory by model predictive control (MPC) through four-wheel steering. The growing complexity of autonomous driving systems requires precise and comfortable trajectory planning and tracking. While 5th-degree polynomials are commonly used for single-lane change maneuvers, they may fail to adequately address lateral jerk, resulting in less comfortable trajectories. The main challenges are: (i) trajectory planning and (ii) trajectory tracking. Front-wheel steering MPC, although widely used, struggles to accurately track trajectories from point mass models, especially when considering vehicle dynamics, leading to excessive lateral jerk. To address these issues, we propose a novel approach combining: (i) 7th-degree polynomial trajectory planning, which provides better control over lateral jerk for smoother and more comfortable maneuvers, and (ii) four-wheel steering MPC, which offers superior maneuverability and control compared to front-wheel steering, allowing for more precise trajectory tracking. Extensive MATLAB/Simulink simulations demonstrate the effectiveness of our approach, showing improved comfort and tracking performance. Key findings include: (i) improved trajectory tracking: Four-wheel steering MPC outperforms front-wheel steering in accurately following desired trajectories, especially when considering vehicle dynamics. (ii) better ride comfort: 7th-degree polynomial trajectories, with improved control over lateral jerk, result in a smoother driving experience. Combining these two techniques enables safer, more efficient, and more comfortable autonomous driving. Full article

The primary objective of this research was to determine coaches’ assessments of the key variables that define the success model in athletic throwing disciplines, as well as to evaluate differences between sexes in the disciplines of javelin, discus, shot put, and hammer throw. Thus, 35 elite coaches were asked about the influence of maximum strength and explosive power factors, manifested through various physical exercises, on final success in throwing disciplines. The questionnaire gathered general information about the coach’s achievements as an athlete and coach and key strength and power metrics, including knee lunge, knee jerk, back squat, bench press, deadlift, standing long jump, standing triple jump, and the 20 m sprint. A two-way within–within 2 × 4 ANOVA revealed a significant effect of sex (male, female) (p < 0.001, η² ranged 0.820–0.996) and discipline (javelin, discus, shot put, hammer) (p < 0.001, η² ranged 0.359–0.996) in all variables except triple standing jump. These findings offer valuable insights into how explosive power and maximum strength are perceived by elite coaches to affect success in different throwing disciplines. The results have practical applications, as they can inform the design and refinement of success models tailored to throwing disciplines, providing essential guidelines for optimizing contemporary training approaches in elite athletics and enhancing performance outcomes across genders and specific events. Full article

Background/Objectives: Cardiac arrest may cause significant hypoxic–ischemic injury leading to coma, seizures, myoclonic jerks, or status epilepticus. Mortality is high, but accurate prognostication is challenging. A multimodal approach is employed, in which electroencephalography (EEG) forms a key part with several recognised patterns of prognostic significance. Methods: In this retrospective study, clinical and qualitative features of the EEG of patients admitted to the Intensive Care Unit (ICU) at Kingston General Hospital following cardiac arrest from 2017 to 2020 were reviewed. The study included 81 adult patients (≥18 years). Outcome was assessed using the Cerebral Performance Category (CPC) as 1–2 (favourable) or 3–5 (unfavourable). EEG patterns were divided into groups within the highly malignant, malignant and benign patterns described in the literature. Results: There were a wide range of causes and 22% had a favourable outcome. Highly malignant, malignant and benign patterns were associated with survival in 0%, 70% and 100%, respectively, and favourable outcomes in 0%, 48% and 100%. All patients with seizures died, and 94% with myoclonus had unfavourable outcomes. In contrast, EEG reactivity and improvement on follow-up EEG were associated with a favourable outcome. Conclusions: Highly malignant EEG, seizures and myoclonus were associated with unfavourable outcomes, while patients with malignant EEG had better outcomes. Full article

This research presents the design of a brake fluid pressure warning and control system for autonomous vehicles (AVs) used on university campuses to control brake fluid pressure and measure the proximity of objects or obstacles in front of the vehicles using LiDAR. The goal was to reduce the jerking of the vehicle caused by the conventional braking system, which may cause danger to the user. We initially changed the existing brake system, which uses human braking force, to electric motor braking and tested it in a closed area (a test track) before actual use. This research was divided into two parts: Part 1—using LiDAR to create warnings in case there are obstacles in front of the vehicle and Part 2—controlling brake fluid pressure using a linear motor and a PD controller. Under the test conditions employed, at a speed of 20 km/h, the total load of passengers is 600 kg. The design results regarding the PD controller with the most suitable values of the system that prevent the vehicle from jerking are K_D = 27.9606 and K_P = 32.0490. The test was conducted while an object crossed the vehicle’s path at distances of 5, 10, 15, and 20 m, respectively. It was found that controlling brake fluid pressure by measuring the distance from the object helped reduce the braking time and jerking of the vehicle and could stop the vehicle before experiencing a collision. At a distance of 20 m, the vehicle could be stopped before the crash and was 3.7 m away from the object; at a distance of 15 m, the distance from the object was 3.1 m; and at a distance of 10 m, the distance from the object was 3 m. However, at a distance of 5 m, the brake system could not stop the vehicle, causing collision with the object because the distance from the object for braking was less than the designed distance. This shows that the warning system and the brake fluid pressure control system can operate in accordance with the corresponding conditions correctly, smoothly, and quickly within the specified distance and be applied to other types of vehicles. Full article

The control of the vehicle transmission system is of great significance to driving comfort. In order to design a controller for smooth shifting and comfortable driving, a dynamic model of dual-clutch transmission is established in this paper. An optimal control strategy for clutch oil pressure based on linear quadratics is proposed, which is used to optimally control the oil pressure of two clutches in the torque stage and inertia stage. The control strategy selects the slipping work and jerk as evaluation indices of shift quality and establishes an optimization objective function. On the premise of optimizing the input torque, the relative speed difference between the engine and the sliding clutch in the inertia stage is adjusted. Through the optimal trajectory control of the wet clutch oil pressure, slipping work and jerk are reduced, thereby improving driving comfort. The simulation results show that the slipping work and jerk generated by the system during the shift stage are reduced, and the shift quality is improved. Additionally, compared with the controller using the MATLAB particle swarm optimization algorithm, the response speed of the proposed controller is faster, the slipping work and jerk are better reduced, and the shift quality is improved. Full article

This study reinterprets the rear-end collision avoidance problem as a trajectory planning challenge, introducing an automatic braking control method based on seventh-degree polynomials. This approach effectively balances vehicle safety and comfort. Unlike traditional automatic braking control methods, e.g., time-to-collision or safety distance models, our method incorporates multiple constraints at both the initiation and conclusion of braking. Consequently, it significantly improves the braking comfort while ensuring collision avoidance; specifically, the braking deceleration changes smoothly rather than abruptly, greatly reducing the vehicle’s jerk value. In accordance with the Euro NCAP testing standards, three car-to-car rear (CCR) test scenarios, such as car-to-car rear stationary (CCRs), car-to-car rear moving (CCRm) and car-to-car rear braking (CCRb), were established within the CarSim environment. The proposed algorithm was rigorously evaluated through integrated simulations performed in CarSim and MATLAB/Simulink, demonstrating its effectiveness. Full article

The three performance indexes of the space robot, travel time, energy consumption, and smoothness, are the key to its important role in space exploration. Therefore, this paper proposes a multi-objective trajectory planning method for robots. Firstly, the kinematics and dynamics of the Puma560 robot are analyzed to lay the foundation for trajectory planning. Secondly, the joint space trajectory of the robot is constructed with fifth-order B-spline functions, realizing the continuous position, velocity, acceleration, and jerk of each joint. Then, the improved multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the trajectory, and the distribution uniformity, convergence, and diversity of the obtained Pareto front are good. The improved MOPSO algorithm can realize the optimization between multiple objectives and obtain the trajectory that meets the actual engineering requirements. Finally, this paper implements the visualization of the robot’s joints moving according to the optimal trajectory. Full article

Unmanned Aerial Vehicles (UAVs) have become essential tools in various industries for tasks such as inspection, maintenance, and surveillance. An Online Impedance Adaptive Controller (OIAC) is proposed for the online modulating of UAV control gains to obtain better performance and stability of tracking curved trajectories than the traditional methods, Model Reference Adaptive Controller (MRAC) and Proportional–Integral–Derivative (PID). Two UAV path planners with minimal jerk and snap were integrated into OIAC, MRAC, and PID. These six controllers were implemented and compared in a simulated UAV with perceptional noise, which follows curved pipelines and avoids obstacles. Experimental results show that the OIAC controller achieves at least an 80% improvement over the PID controller across all trajectory types in terms of the trajectory tracking error. Additionally, OIAC demonstrates an over 20% improvement in jerk trajectories and a more than 30% improvement in snap trajectories when compared to the MRAC controller. These results indicate that OIAC offers enhanced trajectory tracking accuracy and robustness against perceptual noise. Our work presents an advanced controller of a UAV and its preliminary validation in accurate and robust path tracking. Full article