To mitigate the interference of waves on an offshore operation ship, heave compensation systems find widespread application. The performance of heave compensation systems significantly influences the efficiency and safety of maritime operations. This study established a mathematical model for a winch-based active heave compensation system. It introduced a three-loop active disturbance rejection control (ADRC) strategy that encompasses piston position control, winch speed control, and load-displacement control to enable the real-time estimation and compensation of system disturbances, thereby enhancing the performance of the heave compensation system. To assess the effectiveness of this control strategy, this study employed Matlab/Simulink and AMESim to construct a co-simulation model and conducted a comparative analysis with traditional proportional integral derivative (PID) control systems. The research findings indicate that the three-loop ADRC position control strategy consistently delivered superior compensation performance across various operational scenarios.
This study addresses the challenges of predicting ship heave motion in real time, which is essential for mitigating sensor–actuator delays in high-performance active compensation control. Traditional methods often fall short due to training on specific sea conditions, and they lack real-time prediction capabilities. To overcome these limitations, this study introduces a multi-step prediction model based on a Seq2Seq framework, training with heave data taken from various sea conditions. The model features a long-term encoder with attention-enhanced Bi-LSTM, a short-term encoder with Gated CNN, and a decoder composed of multiple fully connected layers. The long-term encoder and short-term encoder are designed to maximize the extraction of global characteristics and multi-scale short-term features of heave data, respectively. An optimized Huber loss function is used to improve the fitting performance in peak and valley regions. The experimental results demonstrate that this model outperforms baseline methods across all metrics, providing precise predictions for high-sampling-rate real-time applications. Trained on simulated sea conditions and fine-tuned through transfer learning on actual ship data, the proposed model shows strong generalization with prediction errors smaller than 0.02 m. Based on both results from the regular test and the generalization test, the model’s predictive performance is shown to meet the necessary criteria for active heave compensation control.
Using the results obtained on the relationship between motor skills and self-regulation of behavior, examine the relationship between kindergarten children's manipulative skills and self-regulation of behavior. Presenting the results of scientific and technological research in the form of graphs, charts, pictures and tables is easier to understand. Infographics have gained popularity in recent years for their effectiveness in conveying information. In a combination of random and cluster sampling, Unk's "Test of Gross Motor Development" and the "Head-Toes-Knees-Shoulders" procedures were used to test self-regulation of behavior and manipulation skills. (1) The development levels of manipulation skills between male and female children were significantly different in terms of their two-handed ball-catching action. There were also notable gender variations in kindergarten students' developmental stages of behavioral self-regulation. (2) In young children, there was a highly significant low-positive connection found between manipulation skill scores and the behaviors of two-handed ball catching and underhand ball tossing. As the children grew older, their behavioral self-regulation and manipulation skills both increased. (3) There were differences between the manipulation skill groups and behavioral self-regulation scores, with two-handed ball-catching and underhand ball-throwing actions having a more prominent effect on behavioral self-regulation in young children. The combined findings highlight the significant relationship between manipulation skills and behavioral self-regulation, which is expected to guide early academic achievement in young children.
Real-time DOA (direction of arrival) estimation of surface or underwater targets is of great significance to the research of marine environment and national security protection. When conducting real-time DOA estimation of underwater targets, it can be difficult to extract the prior characteristics of noise due to the complexity and variability of the marine environment. Therefore, the accuracy of target orientation in the absence of a known noise is significantly reduced, thereby presenting an additional challenge for the DOA estimation of the marine targets in real-time. Aiming at the problem of real-time DOA estimation of acoustic targets in complex environments, this paper applies the MEMS vector hydrophone with a small size and high sensitivity to sense the conditions of the ocean environment and change the structural parameters in the adaptive adjustments system itself to obtain the desired target signal, proposes a signal processing method when the prior characteristics of noise are unknown. Theoretical analysis and experimental verification show that the method can achieve accurate real-time DOA estimation of the target, achieve an error within 3.1° under the SNR (signal-to-noise ratio) of the X channel of −17 dB, and maintain a stable value when the SNR continues to decrease. The results show that this method has a very broad application prospect in the field of ocean monitoring.
Purpose The purpose of this paper is to investigate the influence of employees’ trait rumination on the variability of their state rumination and the continuing influence on their negative affect at home. Design/methodology/approach A time-lagged experience sampling method was used for the data collection from full-time employees in the hotel industry. The hypotheses were tested with multilevel modeling using a random coefficient modeling approach. Findings Hotel employees who are high in trait rumination generally show high levels of state rumination and greater within-person variability in state rumination over time. Additionally, the negative effects of workplace state rumination can last until employees come home and the next day before going to work. Furthermore, employees who are high in trait rumination are more likely to be influenced by state rumination, as they experience more negative affect after arriving home. Practical implications Rumination has been shown to decrease hotel employee overall well-being. The findings of this study provide suggestions for remedial measures that can be taken by hotel organizations to help employees address ruminative thinking. Originality/value Drawing on response styles and work/family border theories, this study contributes to the rumination literature by considering both trait rumination and state rumination in a broader context. For a comprehensive understanding of the dynamic temporal characteristics of state rumination, this study considers the net intraindividual variability of state rumination as the outcome of trait rumination.
Summary The dual-frequency induced polarization method has been applied in geophysical exploration for many years. Pseudo-3D dual-frequency IP array has also been improved based on the traditional 2D IP data acquisition system. In this study, we employed the method in the dam leakage detection. However, due to the limitation of the topography of the surveying field, 3D array is not the efficient way to acquire the dam leakage data. Based on the 3D resistivity cube, we infer the channel of the leakage in the dam. We give two possibilities of the dam leakage path.
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