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Md Easin Hasan and Amy Wagler
Neuroimaging experts in biotech industries can benefit from using cutting-edge artificial intelligence techniques for Alzheimer?s disease (AD)- and dementia-stage prediction, even though it is difficult to anticipate the precise stage of dementia and AD....
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Guy Austern, Tanya Bloch and Yael Abulafia
The application of machine learning (ML) for the automatic classification of building elements is a powerful technique for ensuring information integrity in building information models (BIMs). Previous work has demonstrated the favorable performance of s...
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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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Sen Xue, Chengyu Wu, Jing Han and Ao Zhan
How to select the transmitting path in MPTCP scheduling is an important but open problem. This paper proposes an intelligent data scheduling algorithm using spatiotemporal synchronous graph attention neural networks to improve MPTCP scheduling. By exploi...
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Jun Peng and Baohua Su
The task of aspect-based sentiment analysis (ASBA) is to identify all the sentiment analyses expressed by specific aspect words in the text. How to identify specific objects (i.e., aspect words), describe the modifiers of the specific objects (i.e., opin...
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Weijun Li, Jintong Liu, Yuxiao Gao, Xinyong Zhang and Jianlai Gu
The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is ca...
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Nikolaos Zafeiropoulos, Pavlos Bitilis, George E. Tsekouras and Konstantinos Kotis
In the realm of Parkinson?s Disease (PD) research, the integration of wearable sensor data with personal health records (PHR) has emerged as a pivotal avenue for patient alerting and monitoring. This study delves into the complex domain of PD patient car...
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Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
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Xin Tian and Yuan Meng
Multi-relational graph neural networks (GNNs) have found widespread application in tasks involving enhancing knowledge representation and knowledge graph (KG) reasoning. However, existing multi-relational GNNs still face limitations in modeling the excha...
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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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