A5036100827- Advanced Graph Neural Networks
- Topic Modeling
- Simulation Techniques and Applications
- Data Quality and Management
- Advanced Queuing Theory Analysis
- Graph Theory and Algorithms
- Image and Signal Denoising Methods
- Business Process Modeling and Analysis
- Petri Nets in System Modeling
- Software-Defined Networks and 5G
- Advanced Electrical Measurement Techniques
- Cloud Computing and Resource Management
- Phonocardiography and Auscultation Techniques
- ECG Monitoring and Analysis
- Complex Network Analysis Techniques
- Green IT and Sustainability
- Machine Fault Diagnosis Techniques
- Opportunistic and Delay-Tolerant Networks
- Non-Invasive Vital Sign Monitoring
- Caching and Content Delivery
Chongqing University
2024
Tokyo Metropolitan University
2022-2023
University of Science and Technology Beijing
2020-2021
Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components next-generation wireless networks. This paper focuses on influences different strategies Device-to-Device (D2D) We model D2D User Equipments (DUEs) Gauss determinantal point process considering repulsion between DUEs, well replacement a many-to-many matching game. By analyzing existing placement strategies, new strategy proposed, which...
The knowledge graph can be used as a corpus of cognitive computing, in this paper we mainly focus on the temporal graph. Temporal graph(TKG), an extension static graph(KG), to deal with dynamic and time-varying real scenario, because many relations are only valid for certain period, so it ensure time consistency. Therefore, TKG has received more attention. KG embedding (KGE) is enabling technique completion(KGC), complete missing entities tuples by discovering latent between representations....
This paper proposes a simple Knowledge Graph Embedding (KGE) framework that considers the entity types. The KGE finds appropriate representations of entities and relations by learning structured information in triples uses these to predict missing links knowledge graph (KG). types are included many KGs, but most existing methods ignored its potential for link prediction task. proposed framework, which is called EETCRL (Entity Entity Type Composition Representation Learning), learns way....
Impedance cardiography (ICG) is a clinical tool used to assess cardiac systolic and diastolic functions, as well other function parameters. However, its accuracy based on the effective localization of feature points reflecting function. Moreover, signal processing methods in practice eliminate effects random noise breathing artifacts can easily cause deviations or distortions amplitude time characteristics ICG signals. To solve this problem, paper studies artifact elimination method ICEEMDAN...
This paper proposes a simple knowledge graph embedding (KGE) framework that considers the entity type information without additional resources. The KGE is used to obtain vector representations of entities and relations by learning structured in triples. obtained vectors are predict missing links (KG). Although many KGs contain information, most existing methods ignored potential for link prediction task. proposed framework, which called composition representation (EETCRL), obtains both...