作者：
Hu, RuijieFaculty of Science and Technology
Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai China
With the rapid development of financial markets, stock price prediction, as a highly complex and challenging topic, has attracted more and more attention from academia and industry. This study aims to use multiple mac...
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The impediments with 6G network construction have encouraged the activity of Machine Learning Resource Allocation Algorithms (MLRA). In terms of flexibility and ability utilisation., MLRA outperforms more normal algor...
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Skills in the field of computerscience (CS) are increasingly in demand. Often traditional teaching approaches are not sufficient to teach complex computational concepts. Interactive and digital learning experiences h...
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ISBN:
(纸本)9783031804748;9783031804755
Skills in the field of computerscience (CS) are increasingly in demand. Often traditional teaching approaches are not sufficient to teach complex computational concepts. Interactive and digital learning experiences have been shown as valuable tools to support learners in understanding. However, the missing social interaction affects the quality of the learning experience. Adding collaborative and competitive elements can make the virtual learning environment even more social, engaging, and motivating for learners. In this paper, we explore the potential of collaborative and competitive elements in an interactive virtual laboratory environment with a focus on computerscience education. In an AB study with 35 CS students, we investigated the effectiveness of collaborative and competitive elements in a virtual laboratory using interactive visualizations of sorting algorithms.
Since the 18th National Congress of the Communist Party of China, the President of China has personally arranged the issues related to the Belt and Road Initiative, enhanced the ties between China and other countries,...
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To resolve the tension between edge computing service providers who aim to reduce energy use and users who prioritize enhanced service quality, we introduce an innovative edge computing resource allocation model utili...
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Text classification is a challenging task in the field of Natural Language Processing (NLP), and significant progress has been made using deep learning methods. Traditional deep-learning approaches for text classifica...
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At present, the prediction effect of using deep learning to predict futures prices is usually not good. A Multi Contract LSTM model (MC-LSTM) was designed and implemented to predict futures prices by utilizing actual ...
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Traffic accidents are one of the top ten causes of death, with driver fatigue accounting for a significant proportion. Fatigue can lead to reduced attention and slower reaction times. Many professions require frequent...
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ISBN:
(纸本)9783031709654;9783031709661
Traffic accidents are one of the top ten causes of death, with driver fatigue accounting for a significant proportion. Fatigue can lead to reduced attention and slower reaction times. Many professions require frequent nighttime driving, such as truck and taxi drivers, making them particularly a high risk group. Therefore, preventing accidents caused by driver fatigue, especially during nighttime, is a crucial task. Currently, there is limited research and datasets focused on fatigue driving in nighttime scenes. To address this gap we collect nighttime fatigue driving data using an infrared (IR) camera, and propose Unbalanced LocalCNNs for fatigue driving detection in this work. The network architecture can effectively direct the network's attention to different regions based on specific actions caused by fatigue, and result in a 1.6% improvement in accuracy compared to the original models. Furthermore, an adversarial learning mechanism is introduced to enhance the network's robustness, ensuring effective feature extraction in both day and night scenarios. Compared to models without adversarial learning, the overall accuracy is improved by 1.5%. The code is available at https://***/KaiChun-Tu/slow fastDrowsyDriver.
As a crucial component of the digital economy, the market price fluctuations of Non-Fungible Tokens (NFTs) are influenced by various factors, making accurate prediction extremely important. This paper leverages a Grap...
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Based on the design concept of "human-computer collaboration", this research aims to design intelligent college English teaching assistants with the core goal of promoting the deep integration of technical w...
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