Qingying Zhi
Abstract.The high complexity and uncertainty of financial markets make it difficult for predictive models that rely on a single data source to effectively address these challenges. Multimodal information fusion, by integrating heterogeneous data sources such as text, numerical data, images, and time series, reveals hidden connections and opens new avenues for improving the accuracy and robustness of financial forecasts. This paper systematically analyzes the theoretical foundations, key technical approaches, and typical scenarios for applying multimodal information fusion to financial forecasting. The …
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Meng Xia
Abstract.Virtual-physical fusion advertising production integrates physical filming with virtual elements, presenting new challenges for resource management. This paper proposes a dynamic resource scheduling model for virtual-physical fusion advertising production, employing a three-tier resource pool architecture design to establish multi-dimensional resource profiles and real-time status monitoring mechanisms. An adaptive scheduling strategy engine was developed to achieve data-driven decision optimisation and feedback control, effectively addressing issues such as fluctuating computing power, …
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Zhiqing Guo, Junpeng Yuan, Hang Zeng, Yiting Qiu, Lanqin Wang, Jiaxin Huang, Chentong Wen, Xiaolu Zou, Jingmin Lan, Tingyan Wang, Manni Li, Zhe Li
Abstract.In recent years, social media platforms have profoundly affected people's social interactions and information acquisition, precisely analysing users' needs to achieve efficient matching of content supply, promoting positive ecological cycles, and ultimately enhancing the competitiveness of platforms and commercial value. This paper focuses on the prediction task of "the number of new followers of each blogger", integrates dynamic Bayesian network and collaborative filtering concepts, constructs the "blogger-user interaction matrix", extracts 9-dimensional sliding window differential features …
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Xiaoshuo Shen, Huan Chang, Wenbo He
Abstract.This paper proposes a resource optimization allocation model for wireless communication system, focusing on the resource block allocation and performance optimization method with multi-algorithm fusion. Firstly, the channel model and rate calculation mechanism are constructed to calculate SINR based on path loss and Rayleigh fading, and the transmission rate is determined by Shannon's formula, which provides basic parameters for resource allocation. Secondly, multi-layer optimization strategy is adopted: greedy algorithm completes the initial resource block allocation by priority, linear …
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Enhui Liu
Abstract.Based on provincial panel data from 2011 to 2022 and employing a two-way fixed effects model, this paper empirically examines the mechanism and spatial heterogeneity of the impact of AI industrialization on new quality productive forces. AI has become a key driver of new quality productive forces; however, policy design must be cautious of fiscal dependency risks and fully account for regional disparities to optimize institutional compatibility. Future research may further explore micro-behavioral mechanisms and cross-national comparative perspectives.
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Yun Wang
Abstract.This paper proposes a deep learning-based algorithm for detecting students' mobile phone usage behavior in classroom settings. The approach employs a serial architecture combining the lightweight object detection model PP-YOLO Tiny with the image recognition model MobileNet, enabling real-time and accurate identification of mobile phone usage during class. By optimizing model architecture and implementing data augmentation strategies, the solution addresses the inefficiencies of manual supervision and high false detection rates inherent in traditional methods. Experimental results demonstrate …
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Ziwei Wu, Junyong Liang, Yurui Yuan, Meixue Lai
Abstract.The production of prefabricated components constitutes a crucial step in construction industrialization, where the scientificity and rationality of production scheduling can significantly influence project costs and progress. However, the prefabricated component manufacturing process commonly faces challenges including complex procedures, multiple resource constraints, extended cycles, and high costs. Furthermore, traditional scheduling approaches have become inadequate in meeting current demands for efficient and flexible production scheduling. This study aims to enhance prefabricated …
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Han Zhou, Zhikai Zhuang, Changqing Dong, Haoyan Zhang, Mingkai Yan, Xianzhao Xia
Abstract.With the development of automobile electronization and intelligence, the reliability and performance of automobile grade chip are very important. This article provides an in-depth exploration of the current status, challenges, and applications of automotive specification chip testing technology. Firstly, the traditional testing methods, such as functional verification, performance evaluation, single chip testing, defect screening and electrical parameter verification, are summarized, and the advanced testing technologies, including energy-saving test optimization, multi-layer and vertical chip …
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Hong Yang, Yanan Zhang, Chunxiu Su
Abstract.To break through the technical bottlenecks of traditional UAVs in scene reproduction accuracy, situational awareness efficiency, and real-time data processing, and to promote the development of UAV technology towards intelligence, collaboration, and high precision, this paper systematically develops and elaborates on three core technology systems: real-scene multi-modal AI fusion modeling technology, global situational intelligent perception and collaboration technology, and multi-modal data real-time fusion technology based on sparse representation. In terms of technical performance, the …
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Beibei Hou, Tiansong Sheng
Abstract.Brain tumor segmentation is essential in medical image analysis for clinical diagnosis, treatment planning, and prognosis. Despite significant progress, challenges remain, including limited data annotation, high computational costs, and poor model generalization. To address these, researchers have proposed CNN-based models (e.g., FCN, U-Net, U-Net++) and advanced architectures like large kernel convolution (LKC), deformable convolution (DCN), and CNN-transformer hybrids. This paper examines the widely used BraTS dataset and evaluation metrics such as Dice coefficients and Hausdorff distances, …
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