Objective:To explore the obstructive factors in the behavior of medical staff during the implementation of respiratory rehabilitation process,and to provide a basis for the rehabilitation management intervention of CO...Objective:To explore the obstructive factors in the behavior of medical staff during the implementation of respiratory rehabilitation process,and to provide a basis for the rehabilitation management intervention of COPD.Methods:A descriptive nature research method was adopted.An interview outline was formulated based on the theoretical domain framework.From October to December 2024,15 medical staff from the respiratory department of a tertiary hospital in Shaanxi Province were selected for semi-structured interviews.The interview data were analyzed using the Colaizzi 7-step analysis method.Result:The analysis of this study found that the obstructive factors for medical staff to implement respiratory rehabilitation include five theoretical domains.The problems are respectively the lack of knowledge about respiratory rehabilitation and insufficient training intensity,the insufficient self-recognition of implementing respiratory rehabilitation,the low awareness rate of patients and the low cooperation degree,the insufficient provision of instruments and facilities,the lack of rehabilitation training venues and respiratory rehabilitation clinics,and the lack of scientific and standardized respiratory rehabilitation management processes.Conclusion:There are many obstructive factors affecting the implementation of respiratory rehabilitation by medical staff.Clinical managers should take corresponding measures,continuously improve the rehabilitation management strategies for COPD,and promote the clinical application of the best evidence for respiratory rehabilitation.展开更多
The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge ...The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was展开更多
With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. Fir...With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.展开更多
人工智能技术的迅猛发展为教育领域注入了新的活力,但其融入教学仍面临技术适配性不强、理论框架缺失及学习者认知发展关注不足等问题。本文以基于“浙大先生”的某国家级教学名师的“计算机体系结构”课程为例,基于领域学习模型MDL(Mod...人工智能技术的迅猛发展为教育领域注入了新的活力,但其融入教学仍面临技术适配性不强、理论框架缺失及学习者认知发展关注不足等问题。本文以基于“浙大先生”的某国家级教学名师的“计算机体系结构”课程为例,基于领域学习模型MDL(Model of Domain Learning)和COST(Content-Others-Self-Task)教学设计框架,系统探讨人工智能深度融入教学的理论与实践路径。通过整合多模态数字资源与知识图谱、数字教师与虚拟学伴等人工智能工具,课程设计旨在促进学习者系统化知识的构建、个人专业兴趣的形成以及深度学习策略的掌握。研究指出,未来研究应进一步探索情感支持机制与复杂工程场景模拟,以推动人工智能与教育的深度融合与创新发展。展开更多
基金Shaanxi Provincial People’s Hospital Science and Technology Development Incubation Fund Program 2023(Project No.:2023HL-12)。
文摘Objective:To explore the obstructive factors in the behavior of medical staff during the implementation of respiratory rehabilitation process,and to provide a basis for the rehabilitation management intervention of COPD.Methods:A descriptive nature research method was adopted.An interview outline was formulated based on the theoretical domain framework.From October to December 2024,15 medical staff from the respiratory department of a tertiary hospital in Shaanxi Province were selected for semi-structured interviews.The interview data were analyzed using the Colaizzi 7-step analysis method.Result:The analysis of this study found that the obstructive factors for medical staff to implement respiratory rehabilitation include five theoretical domains.The problems are respectively the lack of knowledge about respiratory rehabilitation and insufficient training intensity,the insufficient self-recognition of implementing respiratory rehabilitation,the low awareness rate of patients and the low cooperation degree,the insufficient provision of instruments and facilities,the lack of rehabilitation training venues and respiratory rehabilitation clinics,and the lack of scientific and standardized respiratory rehabilitation management processes.Conclusion:There are many obstructive factors affecting the implementation of respiratory rehabilitation by medical staff.Clinical managers should take corresponding measures,continuously improve the rehabilitation management strategies for COPD,and promote the clinical application of the best evidence for respiratory rehabilitation.
基金supported by the Key Technology R&D Program of China during the 12th Five-Year Plan period:Super-Class Scientific and Technical Thesaurus and Ontology Construction Faced the Foreign Scientific and Technical Literature (2011BAH10B01)
文摘The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was
基金Supported by the National Natural Science Foun-dation of China (60173058 ,70372024)
文摘With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.
文摘人工智能技术的迅猛发展为教育领域注入了新的活力,但其融入教学仍面临技术适配性不强、理论框架缺失及学习者认知发展关注不足等问题。本文以基于“浙大先生”的某国家级教学名师的“计算机体系结构”课程为例,基于领域学习模型MDL(Model of Domain Learning)和COST(Content-Others-Self-Task)教学设计框架,系统探讨人工智能深度融入教学的理论与实践路径。通过整合多模态数字资源与知识图谱、数字教师与虚拟学伴等人工智能工具,课程设计旨在促进学习者系统化知识的构建、个人专业兴趣的形成以及深度学习策略的掌握。研究指出,未来研究应进一步探索情感支持机制与复杂工程场景模拟,以推动人工智能与教育的深度融合与创新发展。
