With the rapid growth of the Internet economy and the rising rate of urbanization, urban residents' travel modes have become increasingly diversified, with taxis featuring online booking becoming a common choice for daily commuting. Taxis meet the residents' "door-to-door" travel needs, but their travel modes exhibit significant randomness and uncertainty. Moreover, there are often imbalances in supply and demand, such as "difficult to hail a taxi" and "long-distance orders". Therefore, accurate and rapid prediction of taxi demand is crucial for improving regional transport capacity and achieving a "win-win" situation for platforms, drivers, and passengers. This paper uses the "New York City Taxi and Limousine Commission (TLC) Green Taxi Trip Data for April 2015" dataset, applying data mining techniques based on the LSTM taxi demand prediction model to forecast single-region taxi demand and regional OD matrix. The paper selects real network car order data to validate the model’s effectiveness. Additionally, different prediction models are compared to determine the optimal forecasting model.

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Somatosensory interaction technology is an important pathway driving the development of artificial intelligence that meets societal needs, and the application of robots in human society is becoming increasingly widespread. This study aims to systematically review and evaluate the current state of artificial intelligence research based on somatosensory interaction technology, particularly its applications in the field of automated robotics. Using a literature review methodology, this paper elaborates on how automated robotics technology integrates somatosensory interaction to achieve natural human-machine interaction. It provides a comparative analysis of the progress made in current applications, existing limitations, and potential future development directions, followed by a comprehensive summary. The research indicates that somatosensory interaction technology offers a more intuitive and natural means of interaction for automated robots, achieving significant results across various fields. However, challenges remain in terms of technical precision, environmental adaptability, and cost. It is hoped that this study will provide valuable insights for the development of related technologies in China.

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This paper systematically reviews the evolution of Environmental, Social, and Governance (ESG) model construction and traces the development of ESG disclosure and supervision, highlighting regional differences. It further unpacks the core components of the three ESG dimensions and, on this basis, examines their nonlinear interactions. The paper argues that environment, society, and governance do not operate in isolation; rather, through a “boundary–baseline–mechanism” closed loop, they jointly constitute the core framework for corporate sustainable development. Finally, the paper summarizes the opportunities and challenges facing ESG and points out that ESG is poised to become a powerful engine driving the next generation of global growth.

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With the development of millimeter-wave technology, the miniaturization and integration of antennas have become key requirements. This paper presents a millimeter-wave second-order fractal antenna, including its structural design, fabrication method, and application in a silicon-based three-dimensional integrated structure. This antenna realizes a miniaturized structure with a Peano fractal curve on the substrate, featuring a novel structure, small size, and compatibility with other devices and chip processes. Meanwhile, a large-thickness BCB dielectric layer is adopted, which contributes to the miniaturization and integrated integration of the system. By elaborating on the design principle, fabrication steps, and performance of the antenna in the three-dimensional integrated structure, this paper provides a valuable reference for the development of millimeter-wave three-dimensional integration technology.

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