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Advancements in tracking technologies like GPS, RFID and mobile devices have made trajectory data collection widespread. This surge in tracking device usage and location-based services popularity has greatly increased moving object trajectory data availability. The ontological modelling of this kind of data is of paramount importance in understanding and utilising such data effectively. By incorporating maximum semantic data into this model, a variety of essential elements related to mobile object trajectories can be captured. An ontology model rich in semantics not only accurately represents trajectory characteristics but also links them to other relevant elements such as spatial and temporal contexts, movement types and mobile object behaviours. This semantic richness grants the model great adaptability, allowing it to be reused in various contexts related to object mobility and making it generic. Moreover, by integrating this semantic data, the process of analysis and decision-making experiences significant improvement, as it relies on more comprehensive and well-structured information, thereby facilitating informed conclusions and effective strategy implementation. Our objective is to propose a generic ontological model for trajectory data that is rich in semantics and considers the various aspects of moving objects, their movements, their trajectories and their interactions with their environment, aiming to fill the gap identified in other models proposed in the literature.

Water entry problems are very common in engineering and sciences. When objects move with relatively high speed, bubble cavities will be generated, and the behavior of moving objects will also be affected conversely. In this paper, the water entry problems are studied using smoothed particle hydrodynamics (SPH) method, which has special advantages in modeling free surfaces, moving interfaces. First, an improved fluid–solid interface treatment algorithm is presented, whose effectiveness is validated by a water entry of a buoyant cylinder. Then the water entry with different velocities and directions are researched. It is found that the velocities and angles of the moving objects will affect the movement of the object greatly, and the SPH model can give optimal predication of these corresponding conditions.

Tracking imaging attitude control of video satellite for uncooperative moving object is studied in the paper. The effect of satellite attitude adjustment during tracking imaging on image is analyzed quantitatively, and based on it tracking imaging feedback control strategy considering the delay of actuator is proposed in the case of having detected the object in video image. The control law for the reaction wheels is designed, whose asymptotic stability is proved using Lyapunov stability theory. Numerical simulation results show that the presented approach is effective for video satellite achieving tracking imaging of uncooperative moving object.