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Localization is one of the critical issues in Ocean Internet of Things (OITs). The existing research results of localization in OITs are very limited. It poses many challenges due to the difficulty of deploy beacon accurately, the difficulty of transmission distance estimation in harsh ocean environment and the underwater node mobility. This paper aims to provide a novel localization algorithm to solve these problems.

This paper takes the ship with accurate position as a beacon, analyzes the relationship between underwater energy attenuation and node distance and takes them into OITs localization algorithm design. Then, it studies the movement regulation of underwater nodes in the action of ocean current, and designs an Energy-aware Localization Algorithm (ELA) for OITs.

Proposing an ELA. ELA takes the ship with accurate position information as a beacon to solve the problem of beacon deployment. ELA does not need to calculate the information transmission distance which solves the problem of distance estimation. It takes underwater node movement regulation into computation to solve the problem of node mobility.

This paper provides an ELA based on the relationship between propagation energy attenuation and node distance for OITs. It solves the problem of localization in dynamic underwater networks.

In response to the severe lag in tracking the response of the Stewart stability platform after adding overload, as well as the impact of nonlinear factors such as load and friction on stability accuracy, a new error attenuation function and a parallel stable platform active disturbance rejection control (ADRC) strategy combining cascade extended state observer (ESO) are proposed.

First, through kinematic modeling of the Stewart platform, the relationship between the desired pose and the control quantities of the six hydraulic cylinders is obtained. Then, a linear nonlinear disturbance observer was established to observe noise and load, to enhance the system’s anti-interference ability. Finally, verification was conducted through simulation.

Finally, stability analysis was conducted on the cascaded observer. Experiments were carried out on a parallel stable platform with six degrees of freedom involving rotation and translation. In comparison to traditional PID and ADRC control methods, the proposed control strategy not only endows the stable platform with strong antiload disturbance capability but also exhibits faster response speed and higher stability accuracy.

A new error attenuation function is designed to address the lack of smoothness at d in the error attenuation function of the ADRC controller, reducing the system ripple caused by it. Finally, a combination of linear and nonlinear ESOs is introduced to enhance the system's response speed and its ability to observe noise and load disturbances. Stability analysis of the cascade observer is carried out, and experiments are conducted on a six-degree-of-freedom parallel stable platform with both rotational and translational motion.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

To study the spatial layout of urban sports parks, the constraint graph model was used to quantitatively analyze the construction of urban sports parks in China. At the same time, theories on the construction and development of urban sports parks and urban renewal at home and abroad were reviewed. The construction status of urban sports parks in China was systematically studied. Foreign case cities were investigated. Finally, the case cities in our country were discussed. The results showed that in addition to the influence of certain policies and economic factors, the development of sports parks was affected by factors such as urban space development, population size and living distribution, urban culture, regional environmental characteristics and the layout of original sports resources. Therefore, the impact of the above factors should be considered in the development of sports parks and their spatial layout. The layout of the sports park should be balanced to meet the diverse needs of the residents.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

Considering that uncertain factors widely exist in engineering practice, an adaptive collocation method (ACM) is developed for the structural fuzzy uncertainty analysis.

ACM arranges points in the axis of the membership adaptively. Through the adaptive collocation procedure, ACM can arrange more points in the axis of the membership where the membership function changes sharply and fewer points in the axis of the membership where the membership function changes slowly. At each point arranged in the axis of the membership, the level-cut strategy is used to obtain the cut-level interval of the uncertain variables; besides, the vertex method and the Chebyshev interval uncertainty analysis method are used to conduct the cut-level interval uncertainty analysis.

The proposed ACM has a high accuracy without too much additional computational efforts.

A novel ACM is developed for the structural fuzzy uncertainty analysis.

The purpose of this paper is to develop a multifaceted perspective on e-maintenance research and practice over 12 years from 2002 to 2013.

A qualitative research approach is conducted through analysing e-maintenance literature published in peer-review journals from 2002 to 2013 in operations management, information systems, computer science and engineering disciplines.

A multifaceted perspective that reflects evolutionary, managerial, and technological domains of e-maintenance research has been emerged and explained. In addition, stages of e-maintenance process (i.e. integration, aggregation, and prediction) tend to synchronize with organizational levels (i.e. strategic, tactical, and operational) and stimulate the value of e-maintenance practices across the enterprise. However, there are many managerial and technological challenges that inhibit successful implementation of e-maintenance system.

The present research offers managers and vendors a frame of reference that facilitates e-maintenance adoption and implementation. In addition, there is a need for theoretical as well as empirical research in the future to validate the multifaceted perspective in the present study and to obtain more insight into the nature of e-maintenance issues in various settings.

The present paper is one of the first attempts to bridge the gaps in a currently cluttered field of e-maintenance research. It also provides both academics and practitioners with a useful framework that sustains rigorous e-maintenance research and practice.