卷 6 ， 期 17 ， 2023
- 摘要：Aiming at the problems of low recognition rate of traditional voiceprint recognition methods and complicated implementation process, a voiceprint recognition method based on SE-B-ResNet-50 is proposed. The method is based on ResNet-50. First, the first layer of the model is optimized by combining the voiceprint features. At the same time, a global cross-scale connection is added between the first layer of the model and other layers, and then SE-Net is integrated on the basis of the model. The method used the establishment of dependencies on the feature channels in the network, used global information to enhance useful features, while suppressing useless features, and obtains deep voiceprint features through the feature extraction method combined with B-ResNet and SE-Net. The experimental results show that the recognition accuracy of the voiceprint recognition method using SE-B-ResNet-50 reaches more than 97%, which is much higher than the baseline method ResNet-50.关键词：Voiceprint Recognition;ResNet-50;SE-Net;SE-B-ResNet-5033|8|0更新时间：2025-03-26
- 摘要：The construction of task-based dialogue systems for vertical domains suffers from lack of labeled data, poor generalization performance, and inability to start cold. Recently, with the proposal of large language models such as ChatGPT, there have been many new advances in the field of natural language processing. However, there are fewer studies exploring the emergent capabilities of large language models applied to the construction of task-based dialog systems in vertical domains. In this paper, we propose a approach for intent detection and slot filling based on large language models to address the challenges of building task-based dialog systems in vertical domains, specifically three points: (1) fine-tuning the large language models to improve the performance of intent detection and slot filling; (2) adopting multiple rounds of interactions with large language models to enhance the recognition effect; and (3) generating training data based on the large language models for data augmentation. The combined application of these methods can provide an efficient solution for the construction of dialog systems in vertical domains, reduce the reliance on manually labeled data, and improve the accuracy of dialog systems in few-shot and zero-shot situations.关键词：large language model;task-based dialogue systems;model fine-tuning;data enhancement;intent detection;slot filling57|221|0更新时间：2025-03-26
- 摘要：This research aims to analyze the risks associated with cross-border flow of industrial data between China and Europe, and propose corresponding countermeasures. In the context of globalization and digitalization, cross-border flow of industrial data has become an integral part of industrial cooperation between China and Europe. This research provides a comprehensive analysis of the cross-border risks associated with industrial data between China and Europe, and presents corresponding countermeasures. These recommendations will contribute to better risk management and control in cross-border data flow, and enhance cooperation efficiency and sustainable development between China and Europe. However, it is important to note that these recommendations should be adapted and implemented according to the specific circumstances considering the political, legal, and cultural differences between China and Europe.关键词：cross-border data;data security;data transmission;industrial data;data supervison16|60|0更新时间：2025-03-26
RESEARCH PAPER
- 摘要：This paper proposes a digital platform design scheme for clean control and electrostatic protection based on the Internet of things and various sensor technologies. The platform uses technologies such as IOT (Internet Of Things) sensing, big data and artificial intelligence, to realize the clean control of the production environment, and the real-time monitoring of electrostatic protection, real-time alarm, intelligent alarm and online collaborative control through intelligent point detector, voltmeter, current-meter and grounding resistance real-time monitoring instrument, combined with edge computing and control equipment, effectively solving the problems of data acquisition difficulty, incomplete monitoring, poor real-time performance, and uncontrollable safety in traditional environmental control and traditional electrostatic discharge (ESD) monitoring systems; At the same time, in order to achieve the integration of different devices and third-party systems, a unified access gateway has been established, and a new digital platform for clean control and electrostatic protection has been designed, providing reference for research and application in related fields.关键词：clean control;electrostatic monitoring;electrostatic protection;IoT;digital system74|1|0更新时间：2025-03-26
- 摘要：With the continuous development of light emitting diode (LED) display screen technology, its application fields are becoming more and more extensive, and people's requirements for its performance are becoming higher and higher. Its application environment is becoming increasingly demanding. The internal structure of LED display screens is complex and variable, which is include of a large number of devices and cables interconnected. What devices and factors affect the reliability of LED display screens have become hot topics in the current LED display screen industry research. How to design reliable LED display screen products is also an urgent problem to be solved in LED display industry. This article conducts a technical evaluation of LED display screens' Mean Time Between Failures (MTBF), which is made up of LED PCBA, PSU, cabinet structure, control card: thermal design, protection, and material choice. According to the requirements of the National Military Standards and provides relevant suggestions.关键词：LED display;Mean Time between Failures;reliability54|7|0更新时间：2025-03-26
- 摘要：With the rapid development of the Industrial Internet, the categorization of materials in industrial supply chain plays a crucial role in precise supply-demand matching and data standardization. However, traditional material classification methods heavily rely on manual experience and conventional techniques, resulting in limited efficiency and accuracy. This study proposes a material classification system based on multi-dimensional feature fusion and state-of-the-art large language model technology. By integrating deep learning with domain pre-training, the system enhances domain adaptability and semantic understanding. The approach employs multi-dimensional feature fusion, a retrieval system recall verification mechanism, and large language model key entity extraction technology. This combination forms a more precise, stable, and efficient solution for industrial material classification, thereby facilitating the digital transformation of industrial supply chain operations such as procurement and sourcing. This research contributes to the advancement of digitalization in the industrial sector.关键词：Digital Transformation;Industrial Supply Chain;Material Classification;Feature Fusion;Large Language Model139|174|0更新时间：2025-03-26
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