Knowledge management for TEXPROS

Most of the document processing systems today have applied Al technologies to support their system intelligent behaviors. For the application of Al technologies in such systems, the core problem is how to represent and manage different kinds of knowledge to support their inference engine components\u27 functionalities. In other words, knowledge management has become a critical issue in the document processing systems. In this dissertation, within the scope of the TEXt PROcessing System (TEXPROS), we identify knowledge of various kinds that are applicable in the system. We investigate several problems of managing this knowledge and then develop a knowledge base for TEXPROS. In developing this knowledge base, we present approaches to representing and managing different kinds of knowledge to support its inference engine components\u27 functionalities. In TEXPROS, a dual-model paradigm is used, which contains the folder organization and the document type hierarchy, to represent and manage documents. We introduce a new System Catalog structure to represent and manage the knowledge for TEXPROS. This knowledge includes the system-level information of the folder organization and the document type hierarchy, and the operational level information of the document base itself. A unified storage approach is employed to store both the operational level information and system level information. Such storage is to house the frame template base and frame instance base. An enhanced two-level thesaurus model is presented in this dissertation. When dealing with special kinds of data in processing documents, a new structure DataDomain is presented, which supports the extended thesaurus functionalities, pattern recognition and data type operations. Based on the dual-model paradigm of TEXPROS, a concept of “Semantic Range” is presented to solve the sense ambiguity problems. In this dissertation, we also present the approaches to implement the general KeyTerm transformation and approximate term matching of TEXPROS. Finally, a new component “Registration Center” at the knowledge management level of TEXPROS is presented. The registration center aims to help users handle knowledge packages for specific working domain and to solve the knowledge porting problem for TEXPROS. This dissertation is concluded with the future research work

A CFD approach to reduce the risk of Covid-19 airborne transmission in a typical office

The Covid-19 virus can spread rapidly in the air and cause the epidemic to rage around the world. This study takes a typical office as the research object and proposes four different partition settings to suppress the spread of the virus in the air based on displacement ventilation. And these strategies are verified by DPM model simulations of two daily situations of indexed person for coughing and talking. This study then employed a modified Wells-Riley model to evaluate the effectiveness of these strategies in mitigating the risk of viral infection. As expected, in the absence of a partition, a susceptible person at the other end of the seat greatly increased the risk of infection. Partitions can significantly reduce the risk of infection (100% → 20%), while partitions with a full-wrapped structure can reduce the risk of infection to less than 1%. For the instantaneous release scenario of coughing, the barrier can capture a large particle diameter (>50 μm) particles, and the smaller particle diameter can be discharged out of the room with the thermal plume. The strategies provided in this study can provide recommendations for indoor epidemic prevention and control in the context of the Covid-19 pandemic

Research progress and prospects of ecosystem carbon sequestration under climate change (1992–2022)

Climate change is extensively affecting the global ecosystem, especially the ecosystem carbon sequestration and sequestration potential, which are issues of global concern. The proposed concept of “carbon neutrality” in 2020 has brought ecological carbon sequestration to the forefront. Therefore, the research on climate change and ecosystem carbon sequestration need to be systematically reviewed, summarized, and examined. Based on the Web of Science database, this paper analyzed 4005 articles (1992–2022 year) after rigorous screening via a bibliometrics analysis and then presented the research trends and future research focus of ecological carbon sequestration. The following conclusions are drawn: (1) the research over the last 30 years has steadily improved, and the annual number of publications has increased in a cubic polynomial fashion (R2 = 0.9937), with 87.57 % of the total publications appearing after 2009. Global Change Biology and Science of the Total Environment are the most influential journals in the field; (2) participation in such research is becoming increasingly common with expanding research areas covering Eurasia, America, Oceania, and Africa. The United States and China are the most productive and influential countries; (3) the diversity of this research is increasing, and the research content is becoming more explicit and systematic. Most research focuses on climate change, carbon sequestration, management, land-use changes, and nitrogen and soil organic carbon; (4) although traditional ecological evaluation techniques were essential early on, remote sensing and modeling have become the primary methods for assessment; (5) keyword clustering allows the classification of the research into six relatively independent subtopics: climate change and terrestrial ecosystems, sequestration and organic-carbon, ecosystem services, nitrogen and carbon cycling, biomass and forest, and blue carbon, which provides a reference for further research on ecological carbon sequestration and carbon neutrality