A5059493647- Semantic Web and Ontologies
- Biomedical Text Mining and Ontologies
- Scientific Computing and Data Management
- Advanced Graph Neural Networks
- Data-Driven Disease Surveillance
- Silk-based biomaterials and applications
- Open Education and E-Learning
- Data Quality and Management
- Biochemical and Structural Characterization
- Advanced Text Analysis Techniques
- Natural Language Processing Techniques
- Human Mobility and Location-Based Analysis
- Skin Protection and Aging
- Phytochemical compounds biological activities
- Advanced optical system design
- COVID-19 epidemiological studies
- Service-Oriented Architecture and Web Services
- Mental Health Research Topics
- Bee Products Chemical Analysis
- Topic Modeling
- Complex Network Analysis Techniques
- scientometrics and bibliometrics research
- Optical Coatings and Gratings
- Web Data Mining and Analysis
Prague University of Economics and Business
2020-2023
Can Tho University
2022-2023
Polish Academy of Sciences
2019
Horizon House
2017
Leibniz-Zentrum Moderner Orient
2017
L'Oréal (France)
2017
L'Oreal (United States)
2017
Dyckerhoff (Germany)
2015
Wedelia trilobata L. (WT), a common herbal plant in Vietnam, is popularly used as strong antioxidant Vietnamese folk medicine. However, limited studies have reported the application of WT flower cosmeceutical area.This study explored potentials loaded fibroin microparticles (FMPs-WT) novel anti-aging product.The was firstly extracted by maceration with methanol, ethanol 60%, and 96%, its chemical compositions total polyphenol content were investigated. Then, FMPs-WT developed desolvation...
In this paper, we introduce Temporal Multiresolution Graph Neural Networks (TMGNN), the first architecture that both learns to construct multiscale and multiresolution graph structures incorporates time-series signals capture temporal changes of dynamic graphs. We have applied our proposed model task predicting future spreading epidemic pandemic based on historical data collected from actual COVID-19 chickenpox in several European countries, obtained competitive results comparison other...
Modeling and simulations of pandemic dynamics play an essential role in understanding addressing the spreading highly infectious diseases such as COVID-19. In this work, we propose a novel deep learning architecture named Attention-based Multiresolution Graph Neural Networks (ATMGNN) that learns to combine spatial graph information, i.e. geographical data, with temporal timeseries data number COVID-19 cases, predict future pandemic. The key innovation is our method can capture multiscale...
When reusing existing ontologies for publishing a dataset in RDF (or developing new ontology), preference may be given to those providing extensive subcategorization important classes (denoted as focus classes). The subcategories consist not only of named but also compound class expressions. We define the notion focused categorization power ontology, with respect and concept expression language, (estimated) weighted count categories that can built from ontology’s signature, conform are...
One of the grand challenges discussed during Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on Semantic Web" and described in its report is that a: "Public FAIR Graph Everything: We increasingly see creation knowledge graphs capture information about entirety a class entities. [...] This challenge extends this further by asking if we can create graph "everything" ranging from common sense concepts to location based should be "open public" manner democratizing...
Support for PhD students and their advisors in decision-making before along journeys requires providing them with a deep understanding knowledge of the life-cycle PhD. This means giving access to thorough causal relations between events, decisions, possible outcome. can be attained primarily from insider stories, study reports, communications threads colleagues, interviews, scholarly databases. However, it is unclear how give this reasonable structure (due heterogeneity concepts data...