The Tuned Liquid Damper (TLD) method offers a practical and cost-effective solution for seismic design. Accurate modeling of the TLD system’s dynamic behavior is crucial for optimizing its performance. In this study, the nonlinear dynamics of the TLD system are characterized using the Housner model, with parameters estimated via a nonlinear state estimation approach. To address challenges associated with model discretization and unknown noise processes, we introduce a Robust Extended Kalman Filter (REKF) that incrementally incorporates uncertainties to more accurately capture system dynamics. The proposed method is evaluated through real-time hybrid simulation, employing seismic input sign... More >

To find an approach that combines standardization and personalization, the course resources and teaching modes are explored by generative artificial intelligence. By researching and summarizing the problems and solutions in the course teaching process, it is proposed to set up an assessment way based on key nodes. Then, targeted analysis action of students who did not pass the assessment will be assisted with the effective linkage of generative artificial intelligence technology, teacher and students to achieve the expected goals. Research has shown that with the effective linkage, it can provide advanced assistance for multi-level and personalized teaching in terms of broadening horizons, i... More >

Indoor scene recognition poses considerable hurdles, especially in cluttered and visually analogous settings. Although several current recognition systems perform well in outside settings, there is a distinct necessity for enhanced precision in inside scene detection, particularly for robotics and automation applications. This research presents a revolutionary deep Convolutional Neural Network (CNN) model tailored with bespoke parameters to improve indoor picture comprehension. Our proprietary dataset consists of seven unique interior scene types, and our deep CNN model is trained to attain excellent accuracy in classification tasks. The model exhibited exceptional performance, achieving a t... More >

The sharing of data and private information has been greatly improved by Industry 4.0's broad usage of cloud technologies. In their quest to improve their services, many firms have made automation and effective authentication a priority. As a result, in Industry 4.0, Attribute-Based Encryption (ABE) and Attribute-Based Authentication (ABA) have established themselves as dependable models for data sharing across cloud environments. For difficult situations like fine-grained access control and secure authentication, these models offer practical answers. Organizations can utilize ABA to specifically authenticate people based on their attributes, ensuring appropriate and safe access to critical... More >

Precision plant protection, a crucial facet of precision agriculture, assumes a paramount role throughout diverse stages of agricultural pesticide utilization. It not only furnishes indispensable reference parameters for agricultural production but also minimizes the employment of pesticides and their environmental footprint. This investigation employs a laser particle size analyzer to gauge the particle size information of the atomization field under assorted conditions, commencing with ground plant protection. The findings reveal that particle size escalates with the ascent of spray pressure and spray angle while diminishing with their augmentation. It proposes that pressure adjustments ca... More >