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Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ...
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Chao He, Xinghua Zhang, Dongqing Song, Yingshan Shen, Chengjie Mao, Huosheng Wen, Dingju Zhu and Lihua Cai
With the popularization of better network access and the penetration of personal smartphones in today?s world, the explosion of multi-modal data, particularly opinionated video messages, has created urgent demands and immense opportunities for Multi-Moda...
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Despoina Nteli, Maria Nteli, Konstantinos Konstantinidis, Anastasia Foka, Foteini Charisi, Iliana Michailidou, Sotiria Stavropoulou De Lorenzo, Marina Boziki, Maria Tzitiridou-Chatzopoulou, Evangelia Spandou, Constantina Simeonidou, Christos Bakirtzis and Evangelia Kesidou
Argininemia or arginase-1 deficiency constitutes a rare, genetic, metabolic disorder caused by mutations in arginase 1?the last enzyme of the urea cycle?that hydrolyses L-arginine to ornithine and urea. The disease is associated with progressive developm...
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Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu
Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in ge...
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Tobias Zeulner, Gerhard Johann Hagerer, Moritz Müller, Ignacio Vazquez and Peter A. Gloor
Current methods for assessing individual well-being in team collaboration at the workplace often rely on manually collected surveys. This limits continuous real-world data collection and proactive measures to improve team member workplace satisfaction. W...
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Santiago Timón-Reina, Mariano Rincón, Rafael Martínez-Tomás, Bjørn-Eivind Kirsebom and Tormod Fladby
Applying knowledge graphs, graph analytics, and graph machine learning for integrating multi-modal dementia research data.
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Pei-Xuan Li, Yu-Yun Huang, Chris Shei and Hsun-Ping Hsieh
The growth of social platforms has lowered the barrier of entry into the media sector, allowing for the spread of false information and putting democratic politics and social security at peril. Preliminary analysis shows that posts sharing real news and ...
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Huansha Wang, Qinrang Liu, Ruiyang Huang and Jianpeng Zhang
Multi-modal entity alignment refers to identifying equivalent entities between two different multi-modal knowledge graphs that consist of multi-modal information such as structural triples and descriptive images. Most previous multi-modal entity alignmen...
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Xin Tong, Bo Jin, Jingya Wang, Ying Yang, Qiwei Suo and Yong Wu
In recent years, the number of malicious web pages has increased dramatically, posing a great challenge to network security. While current machine learning-based detection methods have emerged as a promising alternative to traditional detection technique...
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Song Yuan, Zexin Lu, Qiyuan Li and Jinguang Gu
Due to inter-modal effects hidden in multi-modalities and the impact of weak modalities on multi-modal entity alignment, a Multi-modal Entity Alignment Method with Inter-modal Enhancement (MEAIE) is proposed. This method introduces a unique modality call...
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