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The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.

The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.

The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.

Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.

Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.

This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.

The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.

This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

This study aims to design and validate a theoretical model for capacitive imaging (CI) sensors that incorporates the interelectrode shielding and surrounding shielding electrodes. Through experimental verification, the effectiveness of the theoretical model in evaluating CI sensors equipped with shielding electrodes has been demonstrated.

The study begins by incorporating the interelectrode shielding and surrounding shielding electrodes of CI sensors into the theoretical model. A method for deriving the semianalytical model is proposed, using the renormalization group method and physical model. Based on random geometric parameters of CI sensors, capacitance values are calculated using both simulation models and theoretical models. Three different types of CI sensors with varying geometric parameters are designed and manufactured for experimental testing.

The study’s results indicate that the errors of the semianalytical model for the CI sensor are predominantly below 5%, with all errors falling below 10%. This suggests that the semianalytical model, derived using the renormalization group method, effectively evaluates CI sensors equipped with shielding electrodes. The experimental results demonstrate the efficacy of the theoretical model in accurately predicting the capacitance values of the CI sensors.

The theoretical model of CI sensors is described by incorporating the interelectrode shielding and surrounding shielding electrodes into the model. This comprehensive approach allows for a more accurate evaluation of the detecting capability of CI sensors, as well as optimization of their performance.

A switching depth controller based on a variable buoyancy system (VBS) is proposed to improve the performance of small autonomous underwater vehicles (AUVs). First, the requirements of VBS for small AUVs are analyzed. Second, a modular VBS with high extensibility and easy integration is proposed based on the concepts of generality and interchangeability. Subsequently, a depth-switching controller is proposed based on the modular VBS, which combines the best features of the linear active disturbance rejection controller and the nonlinear active disturbance rejection controller.

The controller design and endurance of tiny AUVs are challenging because of their low environmental adaptation, limited energy resources and nonlinear dynamics. Traditional and single linear controllers cannot solve these problems efficiently. Although the VBS can improve the endurance of AUVs, the current VBS is not extensible for small AUVs in terms of the differences in individuals and operating environments.

The switching controller’s performance was examined using simulation with water flow and external disturbances, and the controller’s performance was compared in pool experiments. The results show that switching controllers have greater effectiveness, disturbance rejection capability and robustness even in the face of various disturbances.

A high degree of standardization and integration of VBS significantly enhances the performance of small AUVs. This will help expand the market for small AUV applications.

This solution improves the extensibility of the VBS, making it easier to integrate into different models of small AUVs. The device enhances the endurance and maneuverability of the small AUVs by adjusting buoyancy and center of gravity for low-power hovering and pitch angle control.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

A distinctive feature of tilt-rotor UAVs is that they can be fully actuated, whereas in fixed-angle rotor UAVs (e.g. common-type quadrotors, octorotors, etc.), the associated dynamic model is characterized by underactuation. Because of the existence of more control inputs, in tilt-rotor UAVs, there is more flexibility in the solution of the associated nonlinear control problem. On the other side, the dynamic model of the tilt-rotor UAVs remains nonlinear and multivariable and this imposes difficulty in the drone's controller design. This paper aims to achieve simultaneously precise tracking of trajectories and minimization of energy dissipation by the UAV's rotors. To this end elaborated control methods have to be developed.

A solution of the nonlinear control problem of tilt-rotor UAVs is attempted using a novel nonlinear optimal control method. This method is characterized by computational simplicity, clear implementation stages and proven global stability properties. At the first stage, approximate linearization is performed on the dynamic model of the tilt-rotor UAV with the use of first-order Taylor series expansion and through the computation of the system's Jacobian matrices. This linearization process is carried out at each sampling instance, around a temporary operating point which is defined by the present value of the tilt-rotor UAV's state vector and by the last sampled value of the control inputs vector. At the second stage, an H-infinity stabilizing controller is designed for the approximately linearized model of the tilt-rotor UAV. To find the feedback gains of the controller, an algebraic Riccati equation is repetitively solved, at each time-step of the control method. Lyapunov stability analysis is used to prove the global stability properties of the control scheme. Moreover, the H-infinity Kalman filter is used as a robust observer so as to enable state estimation-based control. The paper's nonlinear optimal control approach achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs. Finally, the nonlinear optimal control approach for UAVs with tilting rotors is compared against flatness-based control in successive loops, with the latter method to be also exhibiting satisfactory performance.

So far, nonlinear model predictive control (NMPC) methods have been of questionable performance in treating the nonlinear optimal control problem for tilt-rotor UAVs because NMPC's convergence to optimum depends often on the empirical selection of parameters while also lacking a global stability proof. In the present paper, a novel nonlinear optimal control method is proposed for solving the nonlinear optimal control problem of tilt rotor UAVs. Firstly, by following the assumption of small tilting angles, the state-space model of the UAV is formulated and conditions of differential flatness are given about it. Next, to implement the nonlinear optimal control method, the dynamic model of the tilt-rotor UAV undergoes approximate linearization at each sampling instance around a temporary operating point which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. The linearization process is based on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms from the Taylor series, is considered to be a perturbation that is asymptotically compensated by the robustness of the control scheme. For the linearized model of the UAV, an H-infinity stabilizing feedback controller is designed. To select the feedback gains of the H-infinity controller, an algebraic Riccati equation has to be repetitively solved at each time-step of the control method. The stability properties of the control scheme are analysed with the Lyapunov method.

There are no research limitations in the nonlinear optimal control method for tilt-rotor UAVs. The proposed nonlinear optimal control method achieves fast and accurate tracking of setpoints by all state variables of the tilt-rotor UAV under moderate variations of the control inputs. Compared to past approaches for treating the nonlinear optimal (H-infinity) control problem, the paper's approach is applicable also to dynamical systems which have a non-constant control inputs gain matrix. Furthermore, it uses a new Riccati equation to compute the controller's gains and follows a novel Lyapunov analysis to prove global stability for the control loop.

There are no practical implications in the application of the nonlinear optimal control method for tilt-rotor UAVs. On the contrary, the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems which can be transformed to the linear parameter varying (LPV) form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions. The stability properties of the Galerkin series expansion-based optimal control approaches are still unproven.

The proposed nonlinear optimal control method is suitable for using in various types of robots, including robotic manipulators and autonomous vehicles. By treating nonlinear control problems for complicated robotic systems, the proposed nonlinear optimal control method can have a positive impact towards economic development. So far the method has been used successfully in (1) industrial robotics: robotic manipulators and networked robotic systems. One can note applications to fully actuated robotic manipulators, redundant manipulators, underactuated manipulators, cranes and load handling systems, time-delayed robotic systems, closed kinematic chain manipulators, flexible-link manipulators and micromanipulators and (2) transportation systems: autonomous vehicles and mobile robots. Besides, one can note applications to two-wheel and unicycle-type vehicles, four-wheel drive vehicles, four-wheel steering vehicles, articulated vehicles, truck and trailer systems, unmanned aerial vehicles, unmanned surface vessels, autonomous underwater vessels and underactuated vessels.

The proposed nonlinear optimal control method is a novel and genuine result and is used for the first time in the dynamic model of tilt-rotor UAVs. The nonlinear optimal control approach exhibits advantages against other control schemes one could have considered for the tilt-rotor UAV dynamics. For instance, (1) compared to the global linearization-based control schemes (such as Lie algebra-based control or flatness-based control), it does not require complicated changes of state variables (diffeomorphisms) and transformation of the system's state-space description. Consequently, it also avoids inverse transformations which may come against singularity problems, (2) compared to NMPC, the proposed nonlinear optimal control method is of proven global stability and the convergence of its iterative search for an optimum does not depend on initialization and controller's parametrization, (3) compared to sliding-mode control and backstepping control the application of the nonlinear optimal control method is not constrained into dynamical systems of a specific state-space form. It is known that unless the controlled system is found in the input–output linearized form, the definition of the associated sliding surfaces is an empirical procedure. Besides, unless the controlled system is found in the backstepping integral (triangular) form, the application of backstepping control is not possible, (4) compared to PID control, the nonlinear optimal control method is of proven global stability and its performance is not dependent on heuristics-based selection of parameters of the controller and (5) compared to multiple-model-based optimal control, the nonlinear optimal control method requires the computation of only one linearization point and the solution of only one Riccati equation.

This study investigates the consequences of anthropogenic disturbance caused by dolphin-watching boats on the local spinner dolphin population in Lovina, Bali. It proposes recommendations for developing sustainable destination practices that influence boatmen and tourists to minimise the negative impacts of tourism activities on the dolphins.

Data was collected on boat-dolphin distances, boatmen's behaviour, dolphin behaviour, and underwater noise levels using an unmanned aerial vehicle (UAV) and a hydrophone. The triple-bottom-line framework was applied to analyse the findings and propose recommendations for developing sustainable destination practices.

The study reveals a consistent breach of national and international guidelines, with boats approaching dolphins at distances well below the recommended minimum. Undesirable boatmen’s behaviours and signs of distress and avoidance in dolphins were frequently observed. The findings highlight the need for stakeholders to develop and implement sustainable practices that influence boatmen and tourists to minimise their impact on the dolphins.

This study provides novel insights into the anthropogenic disturbance caused by dolphin-watching boats in Lovina, Bali. It proposes actionable recommendations for developing sustainable destination practices that influence boatmen and tourists. It contributes to the growing body of knowledge on sustainable wildlife tourism management.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

Recreational scuba diving is one of the fastest growing tourism industries around the world and has become a popular activity in Taiwan. Few studies focus on enduring involvement with a high risk or difficult activity specialization, so this study aims to explore the causal relationship between enduring involvement and specialization and seeks to explain sustained involvement in scuba diving activity as a recreation specialization.

This research selects four diving sites in Taiwan as survey locations, specifically Yeliou, Longdong, Kenting and Green Island. The questionnaire consists of three sections, including demographic information, enduring involvement and specialization. By analyzing the data collected from 810 scuba divers in Taiwan, structural equation modeling is used to examine the causal relationships among the variables.

The primary findings of this study are as follows: attraction positively affects divers’ commitment and lifestyle through joy, relaxation and sharing diving experiences; the results indicate that self-expression is associated with past experience of participating in scuba diving activity; and centrality indicates that participants’ daily life and recreation are related to each other and become central to their life. Results show that most theoretical hypotheses are supported, but there is no significant evidence of attraction impacting past experience or self-expression influencing commitment and lifestyle.

To the best of the authors’ knowledge, this study is the first to examine the causal influence of enduring involvement and specialization in the scuba diving context. The findings provide a solid theoretical basis for the study of sustained involvement motivation and behavior on specialization. Implications and recommendations for future research are discussed.

休闲水肺潜水是全球发展最快的旅游业之一, 已成为台湾的热门活动。很少有研究关注持续涉入高风险或困难活动的专门化, 因此本研究探讨持续涉入和专门化之间的因果关系, 并试图解释持续参与水肺潜水活动作为休闲专门化。

这项研究选择了台湾的四个潜水地点作为调查地点, 特别是野柳, 龙洞, 垦丁和绿岛。问卷分为三个部分, 包括人口统计信息, 持续参与和专门化。通过分析从台湾810名潜水员那里收集的数据, 使用结构方程模型检查变量之间的因果关系。

这项研究的主要发现是：（1）吸引力通过愉悦, 放松和分享潜水经历积极影响潜水员的承诺和生活方式; （2）结果表明自我表达与过去参加水肺潜水活动的经历有关（3）中心性表示参与者的日常生活和娱乐彼此相关, 并成为他们生活的中心。结果表明, 大多数理论假设均得到支持, 但没有显着证据表明吸引力会影响过去的经历或自我表达影响承诺和生活方式。

据我们所知, 本研究是第一个研究在潜水环境中持续涉入和专门化的因果关系影响的研究。研究结果为专门化持续参与动机和行为的研究提供了坚实的理论基础。 讨论了对未来研究的影响和建议。

El buceo recreativo es una de las industrias turísticas de más rápido crecimiento en todo el mundo y se ha convertido en una actividad popular en Taiwán. Pocos estudios se centran en la participación duradera con una especialización de actividad difícil o de alto riesgo, por lo que este estudio explora la relación causal entre la participación duradera y la especialización y busca explicar la participación sostenida en la actividad de buceo como una especialización recreativa.

Esta investigación selecciona cuatro sitios de buceo en Taiwán como lugares de estudio, específicamente Yeliou, Longdong, Kenting y Green Island. El cuestionario consta de tres secciones, que incluyen información demográfica, participación duradera y especialización. Al analizar los datos recopilados de 810 buzos en Taiwán, se utiliza un modelo de ecuaciones estructurales para examinar las relaciones causales entre las variables.

Los hallazgos principales de este estudio son: (1) la atracción afecta positivamente el compromiso y el estilo de vida de los buceadores a través de la alegría, la relajación y el intercambio de experiencias de buceo, (2) los resultados indican que la autoexpresión está asociada con la experiencia pasada de participar en actividades de buceo., y (3) la centralidad indica que la vida diaria y la recreación de los participantes están relacionadas entre sí y se vuelven centrales en su vida. Los resultados muestran que la mayoría de las hipótesis teóricas están respaldadas, pero no hay evidencia significativa de que la atracción afecte la experiencia pasada o la autoexpresión que influya en el compromiso y el estilo de vida.

Hasta donde sabemos, este estudio es el primero en examinar la influencia causal de la participación y la especialización duraderas en el contexto del buceo. Los hallazgos proporcionan una base teórica sólida para el estudio de la motivación y el comportamiento de participación sostenida en la especialización. Se discuten las implicaciones y recomendaciones para futuras investigaciones.